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Transcriptome-guided resolution of tumor microenvironment interactions in pheochromocytoma and paraganglioma subtypes

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Abstract

Background

Pheochromocytomas and paragangliomas (PCPG) are rare catecholamine-secreting endocrine tumors deriving from chromaffin cells of the embryonic neural crest. Although distinct molecular PCPG subtypes have been elucidated, certain characteristics of these tumors have yet to be fully examined, namely the tumor microenvironment (TME). To further understand tumor–stromal interactions in PCPG subtypes, the present study deconvoluted bulk tumor gene expression to examine ligand–receptor interactions.

Methods

RNA-sequencing data primary solid PCPG tumors were derived from The Cancer Genome Atlas (TCGA). Tumor purity was estimated using two robust algorithms. The tumor purity estimates and bulk tumor expression values allowed for non-negative linear regression to predict the average expression of each gene in the stromal and tumor compartments for each PCPG molecular subtype. The predicted expression values were then used in conjunction with a previously curated ligand–receptor database and scoring system to evaluate top ligand–receptor interactions.

Results

Across all PCPG subtypes compared to normal samples, tumor-to-tumor signaling between bone morphogenic proteins 7 (BMP7) and 15 (BMP15) and cognate receptors ACVR2B and BMPR1B was increased. In addition, tumor-to-stroma signaling was enriched for interactions between predicted tumor-originating delta-like ligand 3 (DLL3) and predicted stromal NOTCH receptors. Stroma-to-tumor signaling was enriched for interactions between ephrins A1 and A4 with ephrin receptors EphA5, EphA7, and EphA8. Pseudohypoxia subtype tumors displayed increased predicted stromal expression of genes related to immune-exhausted T-cell response, including those for inhibitory receptors HAVCR2 and CTLA4.

Conclusion

The current exploratory study predicted stromal and tumor through compartmental deconvolution and yielded previously unrecognized interactions and putative biomarkers in PCPG.

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Availability of data and materials

All data used in the present study are publicly available at the referenced data repositories.

Code availability

All analyses were performed with R and Python programming language. Code is available upon request.

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Funding

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Authors and Affiliations

  1. Cooper Medical School at Rowan University, 401 Broadway, Camden, NJ, 08103, USA

    S. Batchu & O. S. Henry

  2. Coriell Institute, Camden, NJ, USA

    J. Madzo

  3. Department of Surgery, Cooper University Hospital, Camden, NJ, USA

    A. Hakim, U. Atabek, F. R. Spitz & Y. K. Hong

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  1. S. Batchu
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  2. A. Hakim
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  3. O. S. Henry
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  4. J. Madzo
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  7. Y. K. Hong
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Contributions

SB: conceptualization, methodology, software, visualization, investigation. JM: methodology. AH, OSH: writing reviewing and editing. UA, FRS, YKH: writing, reviewing, editing, investigation.

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Correspondence to S. Batchu.

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Supplementary Information

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40618_2021_1729_MOESM1_ESM.png

Supplementary file1 (PNG 325 KB) Supplementary Figure 1. A Clustering reproduced TCGA subtypes which were used for downstream compartment-specific gene deconvolution. B Consensus CDF shows that the consensus cumulative distribution indicated that four clusters approached the maximum consensus.

40618_2021_1729_MOESM2_ESM.png

Supplementary file2 (PNG 66 KB) Supplementary Figure 2. A Correlation plot of the two purity predicting methods and consensus purity representing the average. B Distribution of predicted and consensus tumor purity estimates.

40618_2021_1729_MOESM3_ESM.png

Supplementary file3 (PNG 166 KB) Supplementary Figure 3. A As a positive control, previously validated stromal and immune cell–specific genes (Yoshihara et al. 2013) were predicted to have higher expression in the stroma of each subtype. B Protein expression was inferred for tumor and stroma compartments in using reverse phase protein array (RPPA) data and compared to deconvolved RNA-sequencing (RNA-seq) expression data. Strong concordance is visible between the predicted mRNA and protein expression profiles.

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Batchu, S., Hakim, A., Henry, O.S. et al. Transcriptome-guided resolution of tumor microenvironment interactions in pheochromocytoma and paraganglioma subtypes. J Endocrinol Invest 45, 989–998 (2022). https://doi.org/10.1007/s40618-021-01729-8

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