Metastasis is the leading cause of death in patients with malignant melanoma, yet the molecular and transcriptional mechanisms remain elusive. This study reveals a crucial role of the p53 homolog, TAp73α, in promoting melanoma metastasis. Using multi-omics approaches combining transcriptomics, proteomics, cistromics and 3D modeling, we discovered a paradigm-shifting mechanism by which TAp73α binds directly to HDAC2, disassembles the HDAC2/REST repressor complex and aberrantly triggers activation of the neuronal receptor GABBR2 in cancer cells. TAp73α-induced derepression of GABBR2 expression leads to upregulation of EMT markers, promotes cancer cell invasiveness and proliferation, and correlates with poor survival outcomes. Our findings redefine the function of p73 in cancer pathogenesis and identify the TAp73α-HDAC2/REST-GABBR2 axis as a novel driver of melanoma progression. These insights could guide future strategies on melanoma treatment.

The advent of immune checkpoint blockade (ICB) has transformed cancer immunotherapy, enabling remarkable long-term outcomes and improved survival, particularly with ICB combination treatments. However, clinical benefits remain confined to a subset of patients, and life-threatening immune-related adverse effects pose a significant challenge. This limited efficacy is attributed to cancer heterogeneity, which is mediated by ligand–receptor interactions, exosomes, secreted factors, and key transcription factors. Oncogenic regulators like E2F1 and MYC drive metastatic tumor environments and intertwine with immunoregulatory pathways, impairing T cell function and reducing immunotherapy effectiveness. To address these challenges, FDA-approved biomarkers, such as tumor mutational burden (TMB) and programmed cell death-ligand 1 (PD-L1) expression, help to identify patients most likely to benefit from ICB. Yet, current biomarkers have limitations, making treatment decisions difficult. Recently, T cells—the primary target of ICB—have emerged as promising biomarkers. This review explores the relationship between cancer drivers and immune response, and emphasizes the role of CD8+ T cells in predicting and monitoring ICB efficacy. Tumor-infiltrating CD8+ T cells correlate with positive clinical outcomes in many cancers, yet obtaining tumor tissue remains complex, limiting its practical use. Conversely, circulating T cell subsets are more accessible and have shown promise as predictive biomarkers. Specifically, memory and progenitor exhausted T cells are associated with favorable immunotherapy responses, while terminally exhausted T cells negatively correlate with ICB efficacy. Ultimately, combining biomarkers enhances predictive accuracy, as demonstrated by integrating TMB/PD-L1 expression with CD8+ T cell frequency. Computational models incorporating cancer and immune signatures could further refine patient stratification, advancing personalized immunotherapy.

Viral vectors are gene transfer tools assembled from the backbones of naturally occurring viruses [...]

Abstract Melanoma is a cancer that is metastatic, drug-refractory and fatal if managed late or inadequately. The transcription factor E2F1 is a key player in melanoma pathology, promoting metastatic traits like EMT, neoangiogenesis, chemoresistance and evasion of immune surveillance. Particularly, high levels of E2F1 trigger tumor progression by developing protein-protein interactions (PPI) with coregulators that enhance its potential to activate a prometastatic gene regulatory network (GRN). We aimed to investigate the extent to which E2F1-expressing melanoma cells influence the immune response. Methods: We combined transcriptomic approaches with bioinformatics and structural modeling to search for target genes involved in E2F1-activated immunomodulatory and prometastatic GRNs in aggressive melanoma. Immunoprecipitation and ChIP were performed to verify both PPI and protein-DNA interactions. Functional analyses, including qRT-PCR, immunoblotting and luciferase assays, were performed to verify expression and regulation of downstream targets. Additionally, we established a melanoma-immune cell coculture system with patient-derived CD4+ and CD8+ T cells. Cytokine arrays and ELISA were used for measurement of cytokine secretion to analyze the E2F1-induced tumor-immuno-crosstalk. Results: We identified an E2F1-dependent GRN with IL-6 as a central factor mediating EMT and immune regulation. Mechanistically, E2F1-induced activation and secretion of IL-6 leads to an autocrine inflammatory forward-feedback loop, which in turn further promotes invasiveness and EMT marker expression in melanoma cells. Interestingly, IL6 activated STAT3 associates with E2F1 in a structure-dependent manner, forming a complex that enhances IL-6 expression by binding to a composite E2F1:STAT3-responsive promoter element. Moreover, we observed that the E2F1-IL6 axis dispenses immunomodulatory effects on surrounding CD4+ and CD8+ T cells, further stimulating IL-6 release, but also leading to secretion of IL-10 into the TME. Although IL-10 has an immunosuppressive function, it also showed anti-metastatic properties in melanoma cells. Thus, in contrast to IL-6, IL-10 decreased cell motility and reduced the expression of Vim, Slug, and Snai1, while simultaneous knockdown of E2F1 increased these effects. The findings are supported by clinical data sets showing that melanoma patients who have high levels of E2F1 and IL-6 and low IL-10 exhibit poor survival. Conclusion: Our results unveil a novel gene regulatory program by which E2F1-associated IL-6 release induces the formation of an E2F1:STAT3 complex, resulting in a forward-feedback loop that promotes cancer invasion and regulates T cells response through intercellular cytokine signaling in the tumor microenvironment. Citation Format: Prabir Dhar, Krishna P. Singh, Shailendra K. Gupta, Dhanya Peringot, Alf Spitschak, Brigitte M. Pützer. E2F1-induced autocrine IL-6 inflammatory loop mediates cancer-immune cell crosstalk that regulates metastatic properties in melanoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6814.

Melanoma is a metastatic, drug-refractory cancer with the ability to evade immunosurveillance. Cancer immune evasion involves interaction between tumor intrinsic properties and the microenvironment. The transcription factor E2F1 is a key driver of tumor evolution and metastasis. To explore E2F1’s role in immune regulation in presence of aggressive melanoma cells, we established a coculture system and utilized transcriptome and cytokine arrays combined with bioinformatics and structural modeling. We identified an E2F1-dependent gene regulatory network with IL6 as a central hub. E2F1-induced IL-6 secretion unleashes an autocrine inflammatory feedback loop driving invasiveness and epithelial-to-mesenchymal transition. IL-6-activated STAT3 physically interacts with E2F1 and cooperatively enhances IL-6 expression by binding to an E2F1-STAT3-responsive promoter element. The E2F1-STAT3/IL-6 axis strongly modulates the immune niche and generates a crosstalk with CD4+ cells resulting in transcriptional changes of immunoregulatory genes in melanoma and immune cells that is indicative of an inflammatory and immunosuppressive environment. Clinical data from TCGA demonstrated that elevated E2F1, STAT3, and IL-6 correlate with infiltration of Th2, while simultaneously blocking Th1 in primary and metastatic melanomas. Strikingly, E2F1 depletion reduces the secretion of typical type-2 cytokines thereby launching a Th2-to-Th1 phenotype shift towards an antitumor immune response. The impact of activated E2F1-STAT3/IL-6 axis on melanoma-immune cell communication and its prognostic/therapeutic value was validated by mathematical modeling. This study addresses important molecular aspects of the tumor-associated microenvironment in modulating immune responses, and will contribute significantly to the improvement of future cancer therapies.

PDF file - 267K, Includes regulatory map construction data, core regulatory module, tumor cell population, model calibration, model simulations, and appropriate references

Mutual regulation of miR-885-5p by p73/DNp73.

Cancer cells have a remarkable ability to evade recognition and destruction by the immune system. At the same time, cancer has been associated with chronic inflammation, while certain autoimmune diseases predispose to the development of neoplasia. Although cancer immunotherapy has revolutionized antitumor treatment, immune-related toxicities and adverse events detract from the clinical utility of even the most advanced drugs, especially in patients with both, metastatic cancer and pre-existing autoimmune diseases. Here, the combination of multi-omics, data-driven computational approaches with the application of network concepts enables in-depth analyses of the dynamic links between cancer, autoimmune diseases, and drugs. In this review, we focus on molecular and epigenetic metastasis-related processes within cancer cells and the immune microenvironment. With melanoma as a model, we uncover vulnerabilities for drug development to control cancer progression and immune responses. Thereby, drug repurposing allows taking advantage of existing safety profiles and established pharmacokinetic properties of approved agents. These procedures promise faster access and optimal management for cancer treatment. Together, these approaches provide new disease-based and data-driven opportunities for the prediction and application of targeted and clinically used drugs at the interface of immune-mediated diseases and cancer towards next-generation immunotherapies.

PDF file - 48K, Topological properties of the E2F1-p73/DNp73-miR-205 network

Legends for supplementary figures S1, S2, and S3.

PDF file - 199K, Feedforward loops detected in the E2F1‐p73/DNp73‐miR‐205 regulatory map

PDF file - 106K, Model definition and parameters

Description of additional experimental procedures used in the study.

Melanoma presents increasing prevalence and poor outcomes. Progression to aggressive stages is characterized by overexpression of the transcription factor E2F1 and activation of downstream prometastatic gene regulatory networks (GRNs). Appropriate therapeutic manipulation of the E2F1-governed GRNs holds the potential to prevent metastasis however, these networks entail complex feedback and feedforward regulatory motifs among various regulatory layers, which make it difficult to identify druggable components. To this end, computational approaches such as mathematical modeling and virtual screening are important tools to unveil the dynamics of these signaling networks and identify critical components that could be further explored as therapeutic targets. Herein, we integrated a well-established E2F1-mediated epithelial-mesenchymal transition (EMT) map with transcriptomics data from E2F1-expressing melanoma cells to reconstruct a core regulatory network underlying aggressive melanoma. Using logic-based in silico perturbation experiments of a core regulatory network, we identified that simultaneous perturbation of Protein kinase B (AKT1) and oncoprotein murine double minute 2 (MDM2) drastically reduces EMT in melanoma. Using the structures of the two protein signatures, virtual screening strategies were performed with the FDA-approved drug library. Furthermore, by combining drug repurposing and computer-aided drug design techniques, followed by molecular dynamics simulation analysis, we identified two potent drugs (Tadalafil and Finasteride) that can efficiently inhibit AKT1 and MDM2 proteins. We propose that these two drugs could be considered for the development of therapeutic strategies for the management of aggressive melanoma.

PDF file - 33K, Fitting of the model to the experimental data

PDF file - 407K, E2F1-p73/DNp73-miR-205 regulatory map

We live in an unprecedented time in oncology. We have accumulated samples and cases in cohorts larger and more complex than ever before. New technologies are available for quantifying solid or liquid samples at the molecular level. At the same time, we are now equipped with the computational power necessary to handle this enormous amount of quantitative data. Computational models are widely used helping us to substantiate and interpret data. Under the label of systems and precision medicine, we are putting all these developments together to improve and personalize the therapy of cancer. In this review, we use melanoma as a paradigm to present the successful application of these technologies but also to discuss possible future developments in patient care linked to them. Melanoma is a paradigmatic case for disruptive improvements in therapies, with a considerable number of metastatic melanoma patients benefiting from novel therapies. Nevertheless, a large proportion of patients does not respond to therapy or suffers from adverse events. Melanoma is an ideal case study to deploy advanced technologies not only due to the medical need but also to some intrinsic features of melanoma as a disease and the skin as an organ. From the perspective of data acquisition, the skin is the ideal organ due to its accessibility and suitability for many kinds of advanced imaging techniques. We put special emphasis on the necessity of computational strategies to integrate multiple sources of quantitative data describing the tumour at different scales and levels.

Skeletal muscle tissue engineering aims at generating biological substitutes that restore, maintain or improve normal muscle function; however, the quality of cells produced by current protocols remains insufficient. Here, we developed a multifactor-based protocol that combines adenovector (AdV)-mediated MYOD expression, small molecule inhibitor and growth factor treatment, and electrical pulse stimulation (EPS) to efficiently reprogram different types of human-derived multipotent stem cells into physiologically functional skeletal muscle cells (SMCs). The protocol was complemented through a novel in silico workflow that allows for in-depth estimation and potentially optimization of the quality of generated muscle tissue, based on the transcriptomes of transdifferentiated cells. We additionally patch-clamped phenotypic SMCs to associate their bioelectrical characteristics with their transcriptome reprogramming. Overall, we set up a comprehensive and dynamic approach at the nexus of viral vector-based technology, bioinformatics, and electrophysiology that facilitates production of high-quality skeletal muscle cells and can guide iterative cycles to improve myo-differentiation protocols.

Institute of Experimental Gene Therapy and Cancer Research, Rostock University Medical Center, Rostock, Germany, Department Life, Light & Matter, University of Rostock, Rostock, Germany, Division of Cellular and Molecular Research, Humphrey Oei Institute of Cancer Research, National Cancer Centre Singapore, Singapore, Singapore, Cancer and Stem Cell Biology Program, Duke-NUS Medical School, Singapore, Singapore

The transcription factor p73 is a structural and functional homolog of TP53, the most famous and frequently mutated tumor-suppressor gene. The TP73 gene can synthesize an overwhelming number of isoforms via splicing events in 5 ' and 3 ' ends and alternative promoter usage. Although it originally came into the spotlight due to the potential of several of these isoforms to mimic p53 functions, it is now clear that TP73 has its own unique identity as a master regulator of multifaceted processes in embryonic development, tissue homeostasis, and cancer. This remarkable functional pleiotropy is supported by a high degree of mechanistic heterogeneity, which extends far-beyond the typical mode of action by transactivation and largely relies on the ability of p73 isoforms to form protein-protein interactions (PPIs) with a variety of nuclear and cytoplasmic proteins. Importantly, each p73 isoform carries a unique combination of functional domains and residues that facilitates the establishment of PPIs in a highly selective manner. Herein, we summarize the expanding functional repertoire of TP73 in physiological and oncogenic processes. We emphasize how TP73's ability to control neurodevelopment and neurodifferentiation is co-opted in cancer cells toward neoneurogenesis, an emerging cancer hallmark, whereby tumors promote their own innervation. By further exploring the canonical and non-canonical mechanistic patterns of p73, we apprehend its functional diversity as the result of a sophisticated and coordinated interplay of: (a) the type of p73 isoforms (b) the presence of p73 interaction partners in the cell milieu, and (c) the architecture of target gene promoters. We suppose that dysregulation of one or more of these parameters in tumors may lead to cancer initiation and progression by reactivating p73 isoforms and/or p73-regulated differentiation programs thereof in a spatiotemporally inappropriate manner. A thorough understanding of the mechanisms supporting p73 functional diversity is of paramount importance for the efficient and precise p73 targeting not only in cancer, but also in other pathological conditions where TP73 dysregulation is causally involved.