Dissecting the treatment-naive ecosystem of human melanoma brain metastasis

Biermann, Jana; Melms, Johannes C.; Amin, Amit Dipak; Wang, Yiping; Caprio, Lindsay; Karz, Alcida; Tagore, Somnath; Barrera, Irving; Ibarra-Arellano, Miguel A.; Andreatta, Massimo; Fullerton, Benjamin T.; Gretarsson, Kristjan H.; Sahu, Varun; Mangipudy, Vaibhav S.; Nguyen, Trang; Nair, Ajay; Rogava, Meri; Ho, Patricia; Koch, Peter; Banu, Matei; Humala, Nelson; Mahajan, Aayushi; Walsh, Zachary H; Shah, Shivem B.; Vaccaro, Daniel H.; Caldwell, Blake A.; Mu, Michael; Wünnemann, Florian; Chazotte, Margot; Berhe, Simon; Luoma, Adrienne; Driver, Joseph; Ingham, Matthew; Khan, Shaheer; Rapisuwon, Suthee; Slingluff, Craig L.; Eigentler, Thomas; Röcken, Martin; Carvajal, Richard D.; Atkins, Michael B.; Davies, Michael A.; Agustinus, Albert; Bakhoum, Samuel F.; Azizi, Elham; Siegelin, Markus D.; Lü, Chao; Carmona, Santiago J.; Hibshoosh, Hanina; Ribas, Antoni; Canoll, Peter; Bruce, Jeffrey N.; Bi, Wenya Linda; Agrawal, Praveen; Schapiro, Denis; Hernando, Eva; Macosko, Evan Z.; Chen, Fei; Schwartz, Gary K.; Izar, Benjamin

doi:10.1016/j.cell.2022.06.007

Cited by 85 publications

(81 citation statements)

References 122 publications

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“…Ecad high MBM featured a proliferative and likely drug-naïve and/or drug-responsible phenotype and GSEA suggests that this subgroup but not Ecad low /NGFR high tumors probably depends on oxidative phosphorylation (OXPHOS) as previously delineated 87 . Our hypothesis is strengthened by the uncovering of molecular features of drug-naïve MBM by Rabbie et al 88 and Biermann et al 89 , showing that this set of MBM expressed Ecad-associated genes such as ABCB5 or pigmentation-related factors such as MLANA , PMEL or DCT found in either of the studies (Fig. 9b ).…”

Section: Discussionsupporting

confidence: 55%

Decoding molecular programs in melanoma brain metastases

et al. 2022

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Melanoma brain metastases (MBM) variably respond to therapeutic interventions; thus determining patient’s prognosis. However, the mechanisms that govern therapy response are poorly understood. Here, we use a multi-OMICS approach and targeted sequencing (TargetSeq) to unravel the programs that potentially control the development of progressive intracranial disease. Molecularly, the expression of E-cadherin (Ecad) or NGFR, the BRAF mutation state and level of immune cell infiltration subdivides tumors into proliferative/pigmented and invasive/stem-like/therapy-resistant irrespective of the intracranial location. The analysis of MAPK inhibitor-naive and refractory MBM reveals switching from Ecad-associated into NGFR-associated programs during progression. NGFR-associated programs control cell migration and proliferation via downstream transcription factors such as SOX4. Moreover, global methylome profiling uncovers 46 differentially methylated regions that discriminate BRAFmut and wildtype MBM. In summary, we propose that the expression of Ecad and NGFR sub- classifies MBM and suggest that the Ecad-to-NGFR phenotype switch is a rate-limiting process which potentially indicates drug-response and intracranial progression states in melanoma patients.

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Section: Discussionsupporting

confidence: 55%

Decoding molecular programs in melanoma brain metastases

et al. 2022

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“…Finally, we evaluated the scalability of Smoother-guided data imputation and deconvolution on datasets with higher spatial resolution. Using the Slide-seq2 data of human melanoma brain metastasis 23 , we confirmed that Smoother, benefiting from the modular design and implementation, can enhance spatial patterns and provide accurate cell-type mappings to tens of thousands of locations while maintaining high computational efficiency ( Supplementary Fig. 16 ).…”

Section: Mainmentioning

confidence: 62%

“…We preprocessed the Slide-seqV2 data of melanoma brain metastasis (MBM) and extracranial melanoma metastasis (ECM) and the paired scRNA-seq data following the original publication 23 using the R package Seurat 34 . Functional signature scores were calculated by averaging the expression of genes involved in the corresponding pathway.…”

Section: Extract Spatial Patterns In the Metastatic Melanoma Slide-se...mentioning

confidence: 99%

Smoother: A Unified and Modular Framework for Incorporating Structural Dependency in Spatial Omics Data

Reynier

et al. 2022

Preprint

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Spatial omics technologies, such as spatial transcriptomics, allow the identification of spatially organized biological processes, while presenting computational challenges for existing analysis approaches that ignore spatial dependencies. Here we introduce Smoother, a unified and modular framework that integrates positional information into non-spatial models via spatial priors and losses. In simulated and real datasets, we show that Smoother enables spatially aware data imputation, cell-type deconvolution, and dimensionality reduction with high accuracy.

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“…For example, melanoma cells have been shown to re-instate neural crest-specific transcription factors that may provide an adaptive, survival advantage in the brain microenvironment 16,37–39 . Notably, while one recent study has found that AXL and EMT-like melanoma cells are enriched in melanoma brain metastases, another recent study found that brain metastases were instead enriched in neuronal-lineage genes and melanocytic state markers such as MITF and SOX10 40,41 . Most likely, melanoma phenotypic plasticity produces a spectrum of different lineage states that interact cooperatively to maintain tumor survival, persistence, and invasion as they compete for various niches in the brain microenvironment (i.e., perivascular positioning).…”

Section: Discussionmentioning

confidence: 98%

Melanoma cells appropriate pericyte:endothelial cell crosstalk during perivascular invasion in the brain

Riedstra

Wang

Patel

et al. 2022

Preprint

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Post brain colonization, cancer cells may adhere to and spread along the abluminal surface of the vasculature providing advantageous access to oxygen, nutrients, and vessel-derived paracrine factors. For example, brain-tropic melanoma cells are well-known to invade along or within blood vessels at the invasive front, but the molecular mechanisms that guide this process are not well-characterized. We have used melanoma cells of different phenotypic states (melanocytic versus mesenchymal) to characterize different modes of perivascular invasion in the brain. We find that Sox9hi mesenchymal state melanoma cells undergo pericyte-like spreading along brain blood vessels via a Snail1-dependent process; in contrast, Sox10hi melanocytic state melanoma form proliferative, perivascular clusters. Snai1 deletion in mesenchymal state melanoma cells diminishes Tgfβ-induced expression of Pdgfrβ which impairs Tgfβ/Pdgf ligand driven motility along the brain microvasculature and dramatically reduces perivascular dispersal of melanoma cells throughout the brain post-colonization. These data suggest that, depending on their transcriptional/phenotypic state, some melanoma cells may appropriate signals that typically mediate endothelial cell:pericyte cross talk as an adaptive mechanism for maintaining vessel proximity and motility in the brain microenvironment.

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Dissecting the treatment-naive ecosystem of human melanoma brain metastasis

Cited by 85 publications

References 122 publications

Decoding molecular programs in melanoma brain metastases

Decoding molecular programs in melanoma brain metastases

Smoother: A Unified and Modular Framework for Incorporating Structural Dependency in Spatial Omics Data

Melanoma cells appropriate pericyte:endothelial cell crosstalk during perivascular invasion in the brain

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