Non-muscle Myosin II reactivation and cytoskeletal remodelling as a new vulnerability in therapy-resistant melanoma

Trabajo presentado en el 3rd ASEICA Educational Symposium, celebrado en modalidad virtual del 23 al 25 de noviembre de 2021.MAPK-targeted therapies (MAPKi) and immune checkpoint blockers (ICB) improve survival of subsets of melanoma patients. However, therapy resistance is a persistent problem. Cross-resistance to MAPKi and ICB may be driven by common transcriptomic alterations in pathways controlling invasion and metastasis. Using phosphoproteomic and transcriptomic analyses, we find that adaptation to treatment and acquisition of resistance to MAPKi involve cytoskeletal remodelling and changes in levels in the ROCK-non-muscle Myosin II (NMII) pathway, which is essential for cancer invasion and metastasis. NMII activity is decreased shortly after MAPK is blocked. However, persister cells promptly restore NMII activity to increase survival, and this becomes a vulnerability, since survival of MAPKi- and ICB-resistant cells is highly dependent on ROCK-NMII. Efficacy of MAPKi and ICB can be improved by combination with ROCK inhibitors, which have a dual action by impairing melanoma cell survival (through induction of lethal reactive oxygen species and unresolved DNA damage) and reducing myeloid- and lymphoid-driven immunosuppression, ultimately overcoming cross-resistance in vivo. In human tumours, high ROCK-NMII levels identify MAPKi-, ICB-resistant melanomas, and treatment-naïve melanomas with worse prognosis. Therefore, a subset of MAPKi- and ICB-resistant melanomas is more susceptible to ROCK-NMII blockade, suggesting clinical opportunities for combination therapies

The Myosin II cytoskeleton as a new vulnerability in therapy-resistant melanoma

Trabajo presentado en VIB Conference: Tumor Heterogeneity, Plasticity and Therapy, celebrado en modalidad virtual del 05 al 06 de mayo de 2021.MAPK-targeted therapies (MAPKi) and immune checkpoint blockers (ICB) improve survival of subsets of melanoma patients. However, therapy resistance is a persistent problem. Cross-resistance to MAPKi and ICB has been suggested to be driven, in part, by common transcriptomic alterations in pathways controlling invasion and metastasis. We find that adaptation to treatment and acquisition of resistance to MAPKi involve cytoskeletal remodelling and changes in expression levels in the ROCK-Myosin II pathway, which plays a key role in cancer invasion and metastasis. Myosin II activity is decreased shortly after MAPK is blocked. However, resistant cells promptly restore Myosin II activity to increase survival, and this becomes a vulnerability, since survival of MAPKi- and ICB-resistant cells is highly dependent on ROCK-Myosin II. Efficacy of MAPKi and ICB can be improved by combination with ROCK inhibitors, which have a dual action by impairing melanoma cell survival (through induction of lethal reactive oxygen species and unresolved DNA damage) and myeloid- and lymphoiddriven immunosuppression, overcoming cross-resistance. In human tumours, high ROCK-Myosin II activity and their associated transcriptome identify MAPKi-, ICBresistant melanomas, and treatment-naïve melanomas with worse prognosis. Therefore, a subset of MAPKi- and ICB-resistant melanomas is intrinsically more susceptible to ROCK-Myosin II inhibition, suggesting clinical opportunities for combination therapies

The Myosin II cytoskeleton as a new vulnerability in therapy-resistant melanoma

Trabajo presentado en la EACR-AstraZeneca Virtual Conference ‘Drug Tolerant Persister Cells’, celebrada del 07 al 08 de diciembre de 2021.MAPK-targeted therapies (MAPKi) and immune checkpoint blockers (ICB) improve survival of subsets of melanoma patients. However, therapy resistance is a persistent problem. Cross-resistance to MAPKi and ICB may be driven by common transcriptomic alterations in pathways controlling invasion and metastasis. We find that adaptation to treatment and acquisition of resistance to MAPKi involve cytoskeletal remodelling and changes in expression levels in the ROCK-non-muscle Myosin II (NMII) pathway, which is essential for cancer invasion and metastasis. NMII activity is decreased shortly after MAPK is blocked. However, persister cells promptly restore NMII activity to increase survival, and this becomes a vulnerability, since survival of MAPKi- and ICB-resistant cells is highly dependent on ROCK-NMII. Efficacy of MAPKi and ICB can be improved by combination with ROCK inhibitors, which have a dual action by impairing melanoma cell survival (through induction of lethal reactive oxygen species and unresolved DNA damage) and reducing myeloid- and lymphoid-driven immunosuppression, ultimately overcoming cross-resistance. In human tumours, high ROCK-NMII levels identify MAPKi-, ICB-resistant melanomas, and treatment-naïve melanomas with worse prognosis. Therefore, a subset of MAPKi- and ICB-resistant melanomas is more susceptible to ROCK-NMII blockade, suggesting clinical opportunities for combination therapies

The Myosin II cytoskeleton as a new vulnerability in therapy-resistant melanoma

Trabajo presentado en el XIX Congreso de la Sociedad Española de Biología Celular, celebrado en Boadilla del Monte (España) del 26 al 29 de octubre de 2021.MAPK-targeted therapies (MAPKi) and immune checkpoint blockers (ICB) improve survival of subsets of melanoma patients. However, therapy resistance is a persistent problem. Cross-resistance to MAPKi and ICB has been suggested to be driven, in part, by common transcriptomic alterations in pathways controlling invasion and metastasis. We find that adaptation to treatment and acquisition of resistance to MAPKi involve cytoskeletal remodelling and changes in expression levels in the ROCK-Myosin II pathway, which plays a key role in cancer invasion and metastasis. Myosin II activity is decreased shortly after MAPK is blocked. However, resistant cells promptly restore Myosin II activity to increase survival, and this becomes a vulnerability, since survival of MAPKi- and ICB-resistant cells is highly dependent on ROCK-Myosin II. Efficacy of MAPKi and ICB can be improved by combination with ROCK inhibitors, which have a dual action by impairing melanoma cell survival (through induction of lethal reactive oxygen species, unresolved DNA damage and cell cycle arrest) and myeloid- and lymphoid-driven immunosuppression, ultimately overcoming cross-resistance. In human tumours, high ROCK-Myosin II activity and their associated transcriptome identify MAPKi-, ICB-resistant melanomas, and treatment-naïve melanomas with worse prognosis. Therefore, a subset of MAPKi- and ICB-resistant melanomas is intrinsically more susceptible to ROCK-Myosin II inhibition, suggesting clinical opportunities for combination therapies

Proteomics profiling of interactome dynamics by colocalisation analysis (COLA)

Localisation and protein function are intimately linked in eukaryotes, as proteins are localised to specific compartments where they come into proximity of other functionally relevant proteins. Significant co-localisation of two proteins can therefore be indicative of their functional association. We here present COLA, a proteomics based strategy coupled with a bioinformatics framework to detect protein–protein co-localisations on a global scale. COLA reveals functional interactions by matching proteins with significant similarity in their subcellular localisation signatures. The rapid nature of COLA allows mapping of interactome dynamics across different conditions or treatments with high precision.Cancer Research UK; BBSRC

The non-muscle Myosin II cytoskeleton as a new vulnerability in therapy-resistant melanoma

Trabajo presentado en el 19th International Congress of the Society For Melanoma Research, celebrado en Edimburgo (Escocia) del 17 al 20 de octubre de 2022.MAPK-targeted therapies (MAPKi) and immune checkpoint blockers (ICB) improve survival of subsets of melanoma patients. However, therapy resistance is a persistent problem. Cross-resistance to MAPKi and ICB may be driven by common transcriptomic alterations in pathways controlling invasion and metastasis. We find that adaptation to treatment and acquisition of resistance to MAPKi involve cytoskeletal remodelling and changes in expression levels in the ROCK-non-muscle Myosin II (NMII) pathway, which is essential for cancer invasion and metastasis. Persister cells overactivate NMII to increase survival, and this becomes a vulnerability, since survival of MAPKiand ICB-resistant cells is highly dependent on ROCK-NMII. Efficacy of MAPKi and ICB can be improved by combination with ROCK inhibitors, which have a dual action by impairing melanoma cell survival (through induction of lethal reactive oxygen species and unresolved DNA damage) and reducing myeloid- and lymphoiddriven immunosuppression, ultimately overcoming cross-resistance. In human tumours, high ROCK-NMII levels identify MAPKi-, ICB-resistant melanomas, and treatment-naïve melanomas with worse prognosis. Therefore, a subset of MAPKi- and ICB-resistant melanomas is more susceptible to ROCK-NMII blockade, suggesting clinical opportunities for combination therapies

Microenvironmental Heterogeneity Parallels Breast Cancer Progression: A Histology–Genomic Integration Analysis

<div><p>Background</p><p>The intra-tumor diversity of cancer cells is under intense investigation; however, little is known about the heterogeneity of the tumor microenvironment that is key to cancer progression and evolution. We aimed to assess the degree of microenvironmental heterogeneity in breast cancer and correlate this with genomic and clinical parameters.</p><p>Methods and Findings</p><p>We developed a quantitative measure of microenvironmental heterogeneity along three spatial dimensions (3-D) in solid tumors, termed the tumor ecosystem diversity index (EDI), using fully automated histology image analysis coupled with statistical measures commonly used in ecology. This measure was compared with disease-specific survival, key mutations, genome-wide copy number, and expression profiling data in a retrospective study of 510 breast cancer patients as a test set and 516 breast cancer patients as an independent validation set. In high-grade (grade 3) breast cancers, we uncovered a striking link between high microenvironmental heterogeneity measured by EDI and a poor prognosis that cannot be explained by tumor size, genomics, or any other data types. However, this association was not observed in low-grade (grade 1 and 2) breast cancers. The prognostic value of EDI was superior to known prognostic factors and was enhanced with the addition of <i>TP53</i> mutation status (multivariate analysis test set, <i>p</i> = 9 × 10⁻⁴, hazard ratio = 1.47, 95% CI 1.17–1.84; validation set, <i>p</i> = 0.0011, hazard ratio = 1.78, 95% CI 1.26–2.52). Integration with genome-wide profiling data identified losses of specific genes on 4p14 and 5q13 that were enriched in grade 3 tumors with high microenvironmental diversity that also substratified patients into poor prognostic groups. Limitations of this study include the number of cell types included in the model, that EDI has prognostic value only in grade 3 tumors, and that our spatial heterogeneity measure was dependent on spatial scale and tumor size.</p><p>Conclusions</p><p>To our knowledge, this is the first study to couple unbiased measures of microenvironmental heterogeneity with genomic alterations to predict breast cancer clinical outcome. We propose a clinically relevant role of microenvironmental heterogeneity for advanced breast tumors, and highlight that ecological statistics can be translated into medical advances for identifying a new type of biomarker and, furthermore, for understanding the synergistic interplay of microenvironmental heterogeneity with genomic alterations in cancer cells.</p></div

In silico tumor dissection pipeline for quantifying spatial diversity in the tumor ecosystem.

<p>(A) Flow diagram depicting the overall study design. (B) Schematic of our pipeline for quantifying spatial diversity in pathological samples. H&E sections are morphologically classified and divided into regions to be spatially scored. The number of clusters <i>k</i> in the regional scores is indicative of the number of sub-populations of cell types in the tumor regions. (C) Examples of tumor regions with low and high diversity scores using the Shannon diversity index, accounting for cancer cells (outlined in green), lymphocytes (blue), and stromal cells (red). Cell classification is automated by image analysis. (D) The 3-D landscape of cell diversity scores on an example H&E section; the <i>x-</i> and <i>y</i>-axes are the geometric axes of the image, and the <i>z</i>-axis is cell diversity computed on a region-by-region basis. (E) The distribution of regional scores in a tumor from the METABRIC study with two regional clusters identified using Gaussian mixture clustering (grey shading: histogram; dashed black line: density; solid black lines: mixture components/clusters).</p

Distribution of EDI scores and clinicopathological characteristics in breast tumors.

<p>Distribution of EDI scores and clinicopathological characteristics in breast tumors.</p