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The MYC family: three genes, one master switch for growth

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T ags: gene families, transcription factors, neuroblastoma, MYCN They switch on growth. They are amplified in tumours. And for decades they were called undruggable. Few gene families are as closely tied to cancer as the MYC family. Its three members, MYC , MYCN and MYCL , encode transcription factors that tell a cell when to grow, divide and build the biomass to do so. When that signal gets stuck on, the consequences are severe. What the MYC proteins do All three share a basic helix-loop-helix leucine zipper (bHLH-LZ) domain. To work, they pair up with a partner protein called MAX, and the MYC–MAX dimer binds E-box sequences (CACGTG) in DNA. From there it regulates a large programme of genes involved in ribosome biogenesis, metabolism, protein synthesis and cell cycle progression. MYC is less a single-target switch than an amplifier of the cell’s existing growth programme. Three siblings, three territories MYC is broadly expressed in proliferating cells and is deregulated in m...
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Why the YY-Plot is One of the Most Powerful Ways to Explore Gene Expression

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When researchers open a genomics dataset, one of the first questions they ask is deceptively simple: "How is my gene of interest expressed across all samples?" The answer often determines the next steps in a project—whether that means investigating a biomarker, validating experimental findings, or identifying patient subgroups. The R2 Genomics Analysis and Visualization Platform has been answering this question for researchers worldwide for many years with one of its signature visualizations: the YY-plot . Although it looks remarkably simple, the YY-plot is one of the fastest ways to uncover biological patterns that might otherwise remain hidden. Every sample, every patient, every data point Unlike summary graphs that compress data into averages or boxplots, the YY-plot displays every individual sample . Samples are automatically ordered from lowest to highest expression of the selected gene. The result is an intuitive landscape of expression levels where every dot represen...
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The galectin family: 15 glycan readers reshaping cancer biology

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T hey bind sugar. They talk to tumours. And they may be the next frontier in cancer immunotherapy. Every cell in your body is coated in a dense forest of sugar chains — glycans. These structures are not decoration. They are read, constantly, by a class of proteins called lectins. Among them, the galectins stand out: a family of 15 human genes whose products specifically recognise β-galactoside motifs and translate glycan patterns into cellular decisions about growth, survival, and immune response. In the language of glycobiology, galectins are glycan readers — they do not build or break sugar chains (that is the job of glycosyltransferase writers and glycosidase erasers), but they interpret them. And increasingly, it is clear that what they read in tumours spells trouble for the immune system. The family tree: three structural archetypes All 15 members share a conserved carbohydrate recognition domain (CRD), but differ in how many CRDs they carry and how those domains are arranged. T...
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The SOX Family: Master Regulators of Development

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 Few protein families in molecular biology are as versatile — or as consequential — as the SOX transcription factors. From the earliest moments of embryonic development to the maintenance of adult tissues, these proteins quietly orchestrate some of the most fundamental decisions a cell ever makes. What Are SOX Factors? SOX proteins take their name from S RY- b ox, a reference to SRY ( Sex-determining Region Y ), the founding member of the family discovered in 1990. SRY turned out to encode a transcription factor with a distinctive DNA-binding domain called the HMG (High Mobility Group) box. When researchers began scanning the genome for proteins sharing this domain, they found not one or two relatives, but an entire family — 19 members in humans, now classified into subgroups A through H. What all SOX proteins share is that HMG box: a roughly 80-amino-acid domain that grips the minor groove of DNA and bends it sharply, sometimes by as much as 70–85 degrees. This bending is not i...
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Unlocking Cancer Insights: Introducing the R2 Platform

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Every year, millions of people are diagnosed with cancer — a disease that, despite its name, is not one condition but thousands. Understanding why tumors behave differently from patient to patient is one of the most pressing challenges in modern medicine. A major breakthrough came with The Cancer Genome Atlas (TCGA), a landmark project that molecularly mapped over 30 types of cancer across thousands of patients. But having data is only half the battle. Making sense of it — quickly, reliably, and without needing a team of bioinformaticians — is where progress stalls. That's the problem R2 was built to solve. R2 is a free, browser-based platform that puts powerful cancer genomics analysis in the hands of any researcher or clinician, no coding required. Drawing on TCGA RNA-seq and clinical data from 31 cancer types, R2 lets you ask — and answer — complex biological questions in minutes. Here's what you can do with it: Compare gene activity across cancer types and patient g...
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A Multi-Omics Resource for Neuroblastoma Research: Molecular Profiles and Drug Response Data for Classical NB Cell Lines

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Neuroblastoma remains one of the most challenging pediatric cancers to treat. Despite decades of research, high-risk disease still carries a poor prognosis, and finding effective therapies requires a deep understanding of the molecular landscape driving each tumor. To support that mission, we are excited to announce the release of a comprehensive multi-omics dataset covering the most widely used classical neuroblastoma cell lines — an openly accessible resource designed to accelerate discovery across the field. What Is in the Dataset? This resource brings together multiple layers of molecular and pharmacological data for a panel of classical neuroblastoma cell lines. In one place, researchers can now access: Transcriptomics (mRNA expression) Genome-wide gene expression profiles capturing the transcriptional state of each cell line. These data allow researchers to explore pathway activity, subtype classification, and gene regulatory networks. DNA copy number variation Genome-scal...
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"From Molecule to Medicine" — Using Target Actionability Reviews to Bridge Data and Drug Development

 Most research stories end with a publication. The best ones end with a treatment. Between those two endpoints lies a long and difficult journey: from a statistically significant finding in a patient cohort, through mechanistic validation, to a druggable target, through preclinical models, to a clinical trial. It's a journey that requires not just good science, but an organised, evidence-based case for why this particular target, in this particular cancer, deserves the investment of a drug development programme. R2's Target Actionability Review (TAR) module is a tool built specifically to support that case-building process — and it is unlike almost anything else in a genomics platform. A TAR is a manually curated, structured literature review focused on a single gene target in a single cancer context. It brings together evidence from multiple domains: the genomic prevalence of alterations in the target, the functional evidence linking it to disease biology, the availability...
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