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PubMed2025

Worldwide Innovative Network (WIN) Consortium in Personalized Cancer Medicine: Bringing next-generation precision oncology to patients.

The human genome project ushered in a genomic medicine era that was largely unimaginable three decades ago. Discoveries of druggable cancer drivers enabled biomarker-driven gene- and immune-targeted therapy and transformed cancer treatment. Minimizing treatment not expected to benefit, and toxicity-including financial and time-are important goals of modern oncology. The Worldwide Innovative Network (WIN) Consortium in Personalized Cancer Medicine founded by Drs. John Mendelsohn and Thomas Tursz provided a vision for innovation, collaboration and global impact in precision oncology. Through pursuit of transcriptomic signatures, artificial intelligence (AI) algorithms, global precision cancer medicine clinical trials and input from an international Molecular Tumor Board (MTB), WIN has led the way in demonstrating patient benefit from precision-therapeutics through N-of-1 molecularly-driven studies. WIN Next-Generation Precision Oncology (WINGPO) trials are being developed in the neoadjuvant, adjuvant or metastatic settings, incorporate real-world data, digital pathology, and advanced algorithms to guide MTB prioritization of therapy combinations for a diverse global population. WIN has pursued combinations that target multiple drivers/hallmarks of cancer in individual patients. WIN continues to be impactful through collaboration with industry, government, sponsors, funders, academic and community centers, patient advocates, and other stakeholders to tackle challenges including drug access, costs, regulatory barriers, and patient support. WIN's collaborative next generation of precision oncology trials will guide treatment selection for patients with advanced cancers through MTB and AI algorithms based on serial liquid and tissue biopsies and exploratory omics including transcriptomics, proteomics, metabolomics and functional precision medicine. Our vision is to accelerate the future of precision oncology care.

Humans↗
PubMed2006

A potential use of color ultrasound as a tool for reproductive management: New observations using color ultrasound scanning that were not possible with imaging only in black and white.

Ultrasonography (US) has been applied to the ovary and the uterus of domestic animals from the late 1980s, and established in 1990s as a practical tool for animal production. US made it possible to detect pregnancy at a very early stage and, most importantly, to observe the real-time dynamics of follicular development and hence the discovery of follicular waves. This has greatly contributed to our understanding of ovarian physiology and helped us to develop several "pin-point" protocols for hormonal treatment. While US may not seem to fit preconceived ideas of a "green" technology, it does not contravene environmental priorities, and it is non-invasive ("ethical") and non-hormonal ("clean"). Using the US technology that is now commercially available at a reasonable price, we are able to estimate the best timing for AI and this allows us to plan either the use of precisely-timed nutritional supplements for fetal development or an immediate 2nd AI service to achieve a better economic efficiency. During the last few years, we have also begun to be able to observe in detail the local blood flow in individual ovarian follicles and CL using color Doppler ultrasonography in the cow. From the series of observations, we have found that: 1) the change of blood supply to an individual follicle closely relates to the dynamics of follicular growth and atresia; 2) the local blood flow detected in the theca externa of mature follicles rapidly increases around the onset of LH surge and is most active before ovulation; 3) the blood supply to the developing CL increases in parallel with CL volume and plasma progesterone concentrations; and 4) the local blood flow surrounding the mature CL acutely increases prior to the onset of luteolysis in response to uterine as well as exogenous PGF(2alpha). It is now clear that color Doppler ultrasound is very useful for observing echogenicity with local blood flow thereby providing an easily obtained estimation of the physiological status of follicles, CLs and early conceptus. Widespread commercial application of color US will depend on further technological developments that reduce the cost and improve performance and ease-of-use. Overall, US is now a most effective non-invasive tool for managing reproduction, at the level of both the individual animal and the herd system. In particular, US can help us to clarify potential problems in high-producing dairy cattle during the postpartum period.

Animals↗
PubMed2003

Overexpression of the tumor autocrine motility factor receptor Gp78, a ubiquitin protein ligase, results in increased ubiquitinylation and decreased secretion of apolipoprotein B100 in HepG2 cells.

Apolipoprotein B100 (apoB) is a large (520-kDa) complex secretory protein; its secretion is regulated posttranscriptionally by several degradation pathways. The best described of these degradative processes is co-translational ubiquitinylation and proteasomal degradation of nascent apoB, involving the 70- and 90-kDa heat shock proteins and the multiple components of the proteasomal pathway. Ubiquitinylation involves several proteins, including ligases called E3s, that coordinate the covalent binding of ubiquitin to target proteins. The recent discovery that tumor autocrine motility factor receptor, also known as gp78, is an endoplasmic reticulum (ER)-associated E3, raised the possibility that this E3 might be involved in the ER-associated degradation of nascent apoB. In a series of experiments in HepG2 cells, we demonstrated that overexpression of gp78 was sufficient for increased ubiquitinylation and proteasomal degradation of apoB, with reduced secretion of apoB-lipoproteins. This action of gp78 was specific: overexpression of the protein did not affect secretion of either albumin or apolipoprotein AI. Furthermore, overexpression of a cytosolic E3, Itch, had no effect on apoB secretion. Finally, using an in vitro translation system, we demonstrated that gp78 led to increased ubiquitinylation and proteasomal degradation of apoB48. Together, these results indicate that an ER-associated protein, gp78, is a bona fide E3 ligase in the apoB ER-associated degradation pathway.

Apolipoprotein B-100↗
PubMed1987

New horizons in lipoprotein research.

The present decade was heralded by the identification of cDNA clones for apo-AI, HMG CoA reductase and the LDL receptor. Today we have descriptions of many other proteins involved in lipid metabolism and of the genes that code for them. Structure and function have been probed by techniques for protein blotting and by in vitro mutagenesis of proteins. The details of gene regulation are now beginning to be unravelled and we can expect exciting new developments in the understanding of how gene expression affects plasma lipoprotein levels. New and powerful techniques have been established for identifying known mutations and for detecting new mutations. Discovery of restriction fragment length polymorphisms have allowed the association between these DNA markers and particular genes involved in lipoprotein metabolism to be probed. The extent to which particular gene loci contribute to the variation in plasma cholesterol levels is being analysed using the methods of genetic epidemiology. With the advent of methods for establishing linkage and physical maps of the human genome, it is now possible to identify the genes responsible for any disorder in which clinical material can be assembled. From this rapidly advancing knowledge it must be anticipated that many new exciting diagnostic and therapeutic possibilities will emerge.

Apolipoproteins↗
PubMed2004

[Application of RNAi technology to knockdown gene expression in vivo in mammalians].

Post-transcriptional gene silencing (PTGS) initiated by dsRNA, which result in specific degradation of homologous mRNA, is called RNAi. The discovery of RNAi greatly intrigued researchers, and was followed by a flood of papers that described the phenomenon and mechanism of RNAi. More excitingly, RNAi has recently been developed into a new tool, showing promising role in reverse genetics, gene therapy and anti-viral infection. This review provides the progress of the application of RNAi technology in mammalian animals.

Animals↗
PubMed1992

Can we see living structure in a cell?

Colloid chemistry (kappa o lambda lambda alpha: glue, or gelatin) was introduced in 1861 after the discovery of protoplasm which exhibits gelatin-like properties. Some 80 years later, colloid chemistry (and with it, the concept of protoplasm) was largely abandoned. The membrane (pump) theory, according to which cell water and cell solute like K+ are free as in a dilute KCl solution, became dominant. Later studies revealed that rejecting the protoplasmic approach to cell physiology was not justified. Evidence against the membrane (pump) theory, on the other hand, has stood the test of time. In a new theory of the living cell called the association-induction (AI) hypothesis, the three major components of the living cell (water, proteins and K+) are closely associated; together they exist in a high-(negative)-energy-low entropy state called the living state. The bulk of cell water is adsorbed as polarized multilayers on some fully extended protein chains, and K+ is adsorbed singly on beta- and gamma-carboxyl groups carried on aspartic and glutamic residues of cell proteins. Extensive evidence in support of the AI hypothesis is reviewed. From an extension of the basic concepts of the AI hypothesis and the new knowledge on primary structure of the proteins, one begins to understand at long last what distinguishes gelatin from other proteins; in this new light, new definitions of protoplasm and of colloid chemistry have been introduced. With the return of the concept of protoplasm, living structure takes on renewed significance, linking cell anatomy to cell physiology. Finally, evidence is presented showing that electron microscopists have come close to seeing cell structure in its living state.

Animals↗
PubMed2003

Role of estrogen and androgen in pubertal skeletal physiology.

Since both estrogen and androgen are present in each sex, it has been difficult to discern the exact role that each sex steroid plays in skeletal physiology. However, studying clinical syndromes in which there is either only estrogen or androgen action has allowed us to gain insight into the unique role that each sex steroid plays in the growing skeleton. In complete androgen insensitivity syndrome (AIS) the only functional sex steroid receptor is that for estrogen. Effected XY females have a pubertal growth spurt that is typical of normal females, both in magnitude and timing. Individuals with AIS have a mild reduction in bone density but it is difficult to distinguish whether this is the result of androgen resistance or estrogen deficiency. These observations suggest that estrogen action only is sufficient to induce a normal pubertal growth spurt, epiphyseal maturation, and near normal bone mineral accretion in women. Until recently, the skeletal effects of estrogen were not thought to be of importance in the male. Conventional wisdom dictated that, in the male, testosterone mediated these skeletal changes. The notion that estrogen is of little importance in the male has been challenged by the recent discovery of two human syndromes in which estrogen action is lacking. In males with either estrogen resistance (inability to respond to circulating estrogen) or aromatase deficiency (inability to synthesize estradiol), as a result of the lack of estrogen action, a pubertal growth spurt does not appear to occur. Furthermore, complete epiphyseal maturation does not take place allowing for continued growth in adulthood and resultant tall stature. Finally normal bone mineral accretion does not take place resulting in severe osteoporosis. These findings indicate that estrogen plays a critical role in skeletal physiology of males as well as females.

Androgens↗
PubMed2026

Proteome-wide structural and interaction analysis using cross-linking mass spectrometry and its applications.

Deciphering the mechanisms of protein-protein interactions (PPIs) and protein structural changes within the native cellular environment is crucial for advancing drug discovery. In vivo chemical cross-linking coupled with mass spectrometry (XL-MS) captures weak, transient, and higher-order interactions that are often dysregulated under altered physiological conditions and remain challenging to detect using conventional methods. Applications of in vivo XL-MS range from targeted mapping of PPIs to large-scale identification of interactome networks within the cells. The integration of quantitative approaches further facilitates comparison across different physiological conditions. The recent incorporation of machine learning (ML) tools into XL-MS workflows is transforming the depth and efficiency of this technology. AI-driven algorithms now enable more accurate identification of cross-linked peptides and the mapping of interaction topologies. Furthermore, the synergistic coupling of in vivo XL-MS data with AI-assisted structural modeling platforms such as AlphaFold allows dynamic and high-throughput prediction of protein networks. This review discusses the broader applications of in vivo XL-MS in complex biological samples, ranging from organelles and cells to whole tissues, and highlights how AI integration is expanding structural biology toward a systems-level understanding of proteome architecture.

Mass Spectrometry↗
PubMed2004

Polymorphic cytochrome P450 2D6: humanized mouse model and endogenous substrates.

Cytochrome P450 2D6 (CYP2D6) is the first well-characterized polymorphic phase I drug-metabolizing enzyme, and more than 80 allelic variants have been identified for the CYP2D6 gene, located on human chromosome 22q13.1. Human debrisoquine and sparteine metabolism is subdivided into two principal phenotypes--extensive metabolizer and poor metabolizer--that arise from variant CYP2D6 genotypes. It has been estimated that CYP2D6 is involved in the metabolism and disposition of more than 20% of prescribed drugs, and most of them act in the central nervous system or on the heart. These drug substrates are characterized as organic bases containing one nitrogen atom with a distance about 5, 7, or 10 A from the oxidation site. Aspartic acid 301 and glutamic acid 216 were determined as the key acidic residues for substrate-enzyme binding through electrostatic interactions. CYP2D6 transgenic mice, generated using a lambda phage clone containing the complete wild-type CYP2D6 gene, exhibits enhanced metabolism and disposition of debrisoquine. This transgenic mouse line and its wild-type control are models for human extensive metabolizers and poor metabolizers, respectively, and would have broad application in the study of CYP2D6 polymorphism in drug discovery and development, and in clinical practice toward individualized drug therapy. Endogenous 5-methoxyindole- thylamines derived from 5-hydroxytryptamine were identified as high-affinity substrates of CYP2D6 that catalyzes their O-demethylations with high enzymatic capacity and specificity. Thus, polymorphic CYP2D6 may play an important role in the interconversions of these psychoactive tryptamines, including a crucial step in a serotonin-melatonin cycle.

Animals↗
PubMed2024

WilsonGenAI a deep learning approach to classify pathogenic variants in Wilson Disease.

BACKGROUND: Advances in Next Generation Sequencing have made rapid variant discovery and detection widely accessible. To facilitate a better understanding of the nature of these variants, American College of Medical Genetics and Genomics and the Association of Molecular Pathologists (ACMG-AMP) have issued a set of guidelines for variant classification. However, given the vast number of variants associated with any disorder, it is impossible to manually apply these guidelines to all known variants. Machine learning methodologies offer a rapid way to classify large numbers of variants, as well as variants of uncertain significance as either pathogenic or benign. Here we classify ATP7B genetic variants by employing ML and AI algorithms trained on our well-annotated WilsonGen dataset. METHODS: We have trained and validated two algorithms: TabNet and XGBoost on a high-confidence dataset of manually annotated, ACMG & AMP classified variants of the ATP7B gene associated with Wilson's Disease. RESULTS: Using an independent validation dataset of ACMG & AMP classified variants, as well as a patient set of functionally validated variants, we showed how both algorithms perform and can be used to classify large numbers of variants in clinical as well as research settings. CONCLUSION: We have created a ready to deploy tool, that can classify variants linked with Wilson's disease as pathogenic or benign, which can be utilized by both clinicians and researchers to better understand the disease through the nature of genetic variants associated with it.

Hepatolenticular Degeneration↗
PubMed2004

Pharmacologic elevation of high-density lipoproteins: recent insights on mechanism of action and atherosclerosis protection.

PURPOSE OF REVIEW: Despite the best efforts in reduction of low-density lipoprotein cholesterol, most cardiovascular events are not being prevented. Because high-density lipoprotein (HDL) promotes reverse cholesterol transport and other antiatherogenic effects, interventions aimed at raising HDL cholesterol or mimicking its beneficial effects may greatly improve treatment and prevention of cardiovascular disease. This article reviews the antiatherogenic effects of HDL, recent insights into the mechanisms of action of currently available, and emerging HDL-based therapies. RECENT FINDINGS: New insights into the basic science of HDL function and metabolism (such as the discovery of beta-chain ATP synthase as a hepatic catabolic HDL receptor) are further characterizing the importance of HDL in atheroprotection and identifying novel targets of drug development. Nicotinic acid, fibrates, statins, and thiazolidinediones not only increase HDL cholesterol but also alter HDL subpopulation size and composition. Furthermore, these drugs promote direct antiatherogenic effects of HDL (antioxidation, anti-inflammation, antithrombotic effects, endothelial stabilization). Emerging HDL-raising therapies (such as cholesteryl ester transfer protein inhibitors and 1,2-dimyristoyl-sn-glycero-phosphocholine) and novel interventions that mimic HDL's beneficial effects (such as apolipoprotein AImilano and apolipoprotein AI mimetic peptides) are proving beneficial in animal and human studies. SUMMARY: An understanding of the atheroprotective mechanisms of HDL is essential for the rational use of currently available drugs and directed development of new drugs. Increasing total HDL cholesterol may not be as important as increasing the functional properties of HDL. Cardiovascular disease treatment and prevention can be improved by combining current low-density lipoprotein-based strategies with effective HDL-based interventions.

Animals↗
PubMed2026

Leptospira-host interactions: advancing next-generation vaccines and diagnostics.

SUMMARYLeptospirosis, a widespread zoonotic disease caused by pathogenic Leptospira species, remains a major public health challenge, particularly in tropical and subtropical regions. Despite advances in understanding Leptospira biology and pathogenesis, effective disease control continues to be limited by the lack of rapid, early diagnostics, and broadly protective vaccines. This review comprehensively examines recent progress in deciphering Leptospira-host interactions, with emphasis on key virulence factors, immune-evasion mechanisms, and host immune responses that influence disease outcomes. Particular focus is placed on the molecular and cellular basis of adhesion, invasion, immune modulation, and persistent colonization. We further discuss the limitations of current vaccines and diagnostic approaches, and highlight how emerging technologies, including pan-genomics, proteomics, reverse vaccinology, immunoinformatics, and omics-based antigen discovery, are facilitating the development of next-generation vaccines and diagnostics. Finally, we outline major translational challenges and future perspectives for improving clinical management, surveillance, and prevention of leptospirosis. The concepts discussed in this review may also provide broader insights into vaccine and diagnostic development for other zoonotic bacterial infections.

Humans↗
PubMed2003

Role of biologic markers in patient selection and application to disease prevention.

Aromatase inhibitors (AIs) are now under investigation for the treatment of early stage breast cancer and for disease prevention as alternatives to standard treatment with tamoxifen. Currently identified genetic risk factors of breast cancer include BRCA-1/BRCA-2 mutations, ATM mutations, and history of high estrogen levels, as evidenced by plasma analyses and/or dense bones. To date, estrogen receptor (ER) and progesterone receptor (PgR) status has predictive value for determining response to therapy in patients with hormone receptor-positive breast cancer (ER+ and/or PgR+ tumors). Recent studies have shown AIs to be safer and more effective than tamoxifen in postmenopausal women with advanced disease. Some data suggest that letrozole may be a more effective treatment than tamoxifen for patients with ER+ and/or PgR+ early breast cancers expressing ErbB-1 and/or ErbB-2. Changes in cell proliferation markers (e.g., S-phase fraction and Ki67 antigen), plasma lipid levels, and the bone resorption marker C-terminal peptide are biomarkers that have been evaluated for preventive and prognostic value in breast cancer patients and normal volunteers. Results from biomarker screens can be used to define inclusion criteria for clinical trials and eventually to individualize treatment. Gene expression profiling (microarray analysis), i.e., genomic and proteomic studies, will probably advance the discovery of new biomarkers for breast cancer prevention and treatment.

Antineoplastic Agents↗
PubMed2026

Standardized Xenograft Models for Preclinical Cancer Research.

Xenograft models are the principal in vivo platform of preclinical oncology and the most established experimental link between cell culture and clinical investigation. From the carcinogen-exposed rabbit models of the early twentieth century through the current generation of humanized patient-derived xenograft (PDX) systems, these platforms have evolved in response to the demands of translational cancer research. This review critically examines the biological principles, methodological standards, and translational applications of the principal xenograft platforms in current use. Cell line-derived xenograft (CDX) models remain the most widely used and most cost-effective modality for preclinical efficacy testing, offering the reproducibility, scalability, and accessibility that have sustained their role across oncology drug development pipelines for decades. PDX models have emerged as the preferred platform for co-clinical trial design, predictive biomarker discovery, and personalized oncology applications, preserving the genomic landscape, intratumor heterogeneity, and histological architecture of the donor tumor across serial passages. The engraftment biology of PDX systems, including immunodeficient host strain selection, implantation site, tumor source, and passage biology, is reviewed, together with humanized and autologous humanized configurations that extend the platform to immune checkpoint inhibitors, bispecific T-cell engagers, and chimeric antigen receptor T (CAR-T) cell therapy evaluation. This review addresses preclinical-to-clinical translation as a function of immunological divergence, incomplete tumor microenvironment recapitulation, and standardization. Formal frameworks, including the PDX Model Minimal Information (PDX-MI) standard and the Minimal Information for Standardization of Humanized Mice (MISHUM), are examined alongside global biobank infrastructure and emerging AI-driven translational modeling approaches.

Animals↗
PubMed2026

AI-driven CRISPR screening: optimizing gene editing through automation and intelligent decision support.

BACKGROUND: CRISPR-based genetic screening has become a central methodology in functional genomics, enabling systematic interrogation of gene function, genetic interactions and context-dependent vulnerabilities at scale. However, the rapid expansion of screening modalities-including multi-condition designs, combinatorial perturbations, in vivo applications and single-cell readouts-has exposed fundamental limitations of heuristic-driven experimental design and post hoc statistical analysis. MAIN BODY: This Review synthesizes how artificial intelligence is reshaping CRISPR screening by introducing predictive, adaptive and system-level intelligence across the experimental lifecycle. We organize recent advances into two tightly coupled modules. First, machine learning and deep learning (ML/DL) methods optimize experimental design by learning context-dependent perturbation behavior, anticipating confounding effects and enabling iterative, information-efficient screening strategies. Second, large language model-agent (LLM-agent) systems complement these advances by externalizing scientific reasoning, integrating biological knowledge at scale and coordinating analysis and decision-making in human-in-the-loop workflows. CONCLUSIONS: Together, ML/DL and LLM-agent approaches reframe CRISPR screening from a static analytical pipeline into an intelligent experimental system, with important implications for robustness, scalability and biological discovery.

Artificial Intelligence↗
PubMed2002

[Screening of differentially expressed genes in the mouse hematopoietic stromal cells after long-term culture].

Hematopoietic stromal cells, being the essential ingredient of the hematopoietic microenvironment, play very important roles in the control and regulation of self-renewal, proliferation and differentiation of hematopoietic stem cells (HSC) via complex interactions of cell-cell, cell-humoral and cell-extracellular matrix. Evidence from in vivo experiment has proved that HSC derived from normal mice could reconstitute hematopoiesis of mice with HSC defects but failed to reconstitute hematopoiesis of those mice with microenvironment defects, showing the importance of hematopoietic microenvironment in the maintenance of hematopoiesis in vivo. A well-known long-term culture (LTC) system established by Dexter demonstrated in another way that stromal cell layer in the system could support ex vivo hematopoiesis for several months, even more than one year under the optimal conditions. It, however, has not been demonstrated that what is the key elements and in which way the ex vivo hematopoiesis could be maintained for so long time. As the inventions for the large-scale screening methodologies the suppression subtractive hybridization (SSH) was chosen for the screening differentially expressed genes expressed by LTC cultured stromal cells but not by the uncultured bone marrow cells (BMC). mRNA extracted from both cultured adherent cells (tester) and BMC (driver) were hybridized according to the protocol provided by CLONTECH. Total of 130 clones differentially expressed by cultured cells were randomly picked up and 106 ESTs were obtained after sequencing. They represent 26 identical or similar genes and 7 novel genes after the bioinformatics analysis. 5 of the novel genes with the entire open reading frame, without functional clues, have been cloned into the mammalian expression vectors and the functions of them in the control of proliferation and differentiation of HSC will be further exploring. The most interesting discovery is that 3 novel genes have signal peptides, implying the potential discovery of novel growth factors as 80% known growth factors have signal peptides. Our experimental results suggest that: (a) based on the results of subtractive efficiency, the SSH could be a reliable method to screen differentially expressed genes; (b) gene expression may be regulated by multiple factors, even conditioning-dependent, in this experiment the genes expressed by bone marrow stromal cells are LTC-cultivation inducible; (c) it is possible to find interesting genes or special gene after relatively large-scale screen.

Animals↗
PubMed2006

Selection of optimal adjuvant endocrine therapy for early-stage breast cancer.

Oophorectomy was found to cause regression of advanced breast cancer toward the end of the 19th century. Decades later, the discovery that estrogen plays a central role in this process eventually led to two important consequences: first, different modalities were developed to suppress or antagonize estrogen; and second, the ability to detect estrogen receptor in breast cancer tissue became a predictor of response to treatment--probably the best marker for response among all solid tumors. Tamoxifen, which works by competitively antagonizing hormonal receptors in breast cancer cells, has been for the past three decades the standard of care for adjuvant therapy for any woman with hormone receptor-positive early breast cancer, regardless of nodal status or menopausal setting. But as we strive to improve the utility of antagonizing or suppressing estrogen, new modalities are being developed. In the premenopausal setting, the advent of gonadotropin hormone-releasing hormone (also known as luteinizing hormone-releasing hormone) analogues has allowed for medical and reversible suppression of ovarian function. This method has already been proven as effective as chemotherapy in preventing recurrence, and ongoing trials are aiming to better define its role in the adjuvant setting. In the postmenopausal setting, aromatase inhibitors (AIs) have revolutionized the adjuvant treatment of hormone-responsive cancers of all stages. The current standard of care has come to include AIs, as an alternative, in sequence, of after 5 years of tamoxifen. Ongoing research continues to develop agents to overcome hormonal therapy resistance.

Adult↗
PubMed2002

Complexities in ETS-domain transcription factor function and regulation: lessons from the TCF (ternary complex factor) subfamily. The Colworth Medal Lecture.

The ETS-domain transcription factor family can be divided into a series of subfamilies. Elk-1 represents the founding member of the ternary complex factor (TCF) subfamily. By focusing on the TCF subfamily, we can demonstrate the complexities that exist in the function and regulation of ETS-domain transcription factors. This article focuses on Elk-1 in detail and summarizes the functions of other TCFs. The key themes covered include the domain structure of the TCFs, the mechanisms of complex formation with serum response factor, regulation of TCFs by mitogen-activated protein kinase cascades, and transcriptional regulatory properties of the TCFs. Finally, the emerging role of the TCFs in vivo is discussed. A picture is developing indicating that, while these proteins exhibit significant sequence and functional conservation, key differences in their structure and regulation are being identified which may relate to unique functions of these proteins in vivo.

Amino Acid Sequence↗