8574 Single cell multiomics suggests tumor cell energy metabolism heterogeneity in non-functioning gonadotroph pituitary adenomas

Abstract Disclosure: F.M. Ruf-Zamojski: None. Z. Zhang: None. W. Cheng: None. G.R. Smith: None. M. Zamojski: None. N. Mendelev: None. Y. Ge: None. D. Marrero-Rodríguez: None. K. Taniguchi-Ponciano: None. C.L. Andoniadou: None. E. Zaslavsky: None. X. Chen: None. O.G. Troyanskaya: None. M. Mercado: None. S.C. Sealfon: None. Pituitary adenomas cause hormonal dysregulation and severe morbidity. The absence of clear biomarkers for prognosis/treatment and the high risk of recurrence make management challenging. Non-functioning gonadotroph pituitary adenomas (NFPAs) represent proliferation of gonadotroph lineage cells without an increase in secretion of gonadotropins. Detection is often delayed until mass effects cause visual defects. Higher resolution molecular study may improve classification, diagnosis, treatment, and provide insight into adenoma biology. We analyzed four NFPAs using unbiased genome-wide same-cell single nucleus 10X Genomics multiome assay (transcriptome and chromatin accessibility) to define individual cell identity/states in comparison with normal gonadotrope cell references from twelve age/sex-matched human post-mortem pituitaries. In total, we generated high quality multiomics single-cell data for 33,832 adenoma cells and 5,451 normal gonadotropes. We identified tumor, immune, vascular, and proliferative cells confirming cellular heterogeneity. Multidimensional scaling analysis using Manhattan distances between cell types showed that NFPA gonadotropes were closer in gene expression to healthy gonadotropes among all pituitary cell types. In addition, we observed differences in the macrophage and endothelial cell populations between tumors and healthy pituitaries. Next, we studied gene regulatory circuitry (regulated gene, modulating transcription factor and its chromatin interaction site) using the new Control of Regulation Extracted from Multiomics Assays (CREMA, [1]) multiome analysis method which showed high variation between normal and tumor gonadotropes. Within each adenoma, the NFPA tumor cells encompassed two main subgroups of cells, one group (GT+ marker tumor cells) expressing established gonadotrope markers and another group not (GT- marker tumor cells). GT+ and GT- tumor cells formed a cluster distinct from healthy gonadotropes. GT+ and GT- tumor cells differed by their level of expression of mitochondrial genes, suggesting decreased aerobic capacity associated with the GT- tumor subgroup. Interestingly, differential analyses between the healthy and the NFPA gonadotropes from same-cell multiome data highlighted dissimilar gene expression and chromatin accessibility patterns.Our newly collected single cell data characterize the difference between NFPA tumor cells and normal gonadotrope cells. Our results suggest a Warburg-effect like difference in aerobic respiratory capacity among tumor cells within the same pituitary adenoma. Overall, this study brings new insights into the molecular characteristics of NFPAs, including tumor cell heterogeneity, and represents a new resource for the field. [1] PMID: 38084892. Presentation: 6/1/2024

Authors

Institutions

Publication Details

Journal
Journal of the Endocrine Society
Published
2024-10-01
DOI
https://doi.org/10.1210/jendso/bvae163.1334
Primary Topic
Pituitary Gland Disorders and Treatments
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

8574 Single cell multiomics suggests tumor cell energy metabolism heterogeneity in non-functioning gonadotroph pituitary adenomas

Moisés Mercado, Cynthia L. Andoniadou, Olga G. Troyanskaya, Elena Zaslavsky et al.
Journal of the Endocrine Society
Pituitary Gland Disorders and Treatments
article

8574 Single cell multiomics suggests tumor cell energy metabolism heterogeneity in non-functioning gonadotroph pituitary adenomas

Moisés Mercado, Cynthia L. Andoniadou, Olga G. Troyanskaya, Elena Zaslavsky, Daniel Marrero–Rodríguez, Wenxuan Cheng, Stuart C. Sealfon, Natalia Mendelev, Keiko Taniguchi‐Ponciano, Michel Zamojski, Zhihui Zhang, Yubin Ge, G R Smith, F M Ruf-Zamojski, Xi Chen
article en

Abstract

Abstract Disclosure: F.M. Ruf-Zamojski: None. Z. Zhang: None. W. Cheng: None. G.R. Smith: None. M. Zamojski: None. N. Mendelev: None. Y. Ge: None. D. Marrero-Rodríguez: None. K. Taniguchi-Ponciano: None. C.L. Andoniadou: None. E. Zaslavsky: None. X. Chen: None. O.G. Troyanskaya: None. M. Mercado: None. S.C. Sealfon: None. Pituitary adenomas cause hormonal dysregulation and severe morbidity. The absence of clear biomarkers for prognosis/treatment and the high risk of recurrence make management challenging. Non-functioning gonadotroph pituitary adenomas (NFPAs) represent proliferation of gonadotroph lineage cells without an increase in secretion of gonadotropins. Detection is often delayed until mass effects cause visual defects. Higher resolution molecular study may improve classification, diagnosis, treatment, and provide insight into adenoma biology. We analyzed four NFPAs using unbiased genome-wide same-cell single nucleus 10X Genomics multiome assay (transcriptome and chromatin accessibility) to define individual cell identity/states in comparison with normal gonadotrope cell references from twelve age/sex-matched human post-mortem pituitaries. In total, we generated high quality multiomics single-cell data for 33,832 adenoma cells and 5,451 normal gonadotropes. We identified tumor, immune, vascular, and proliferative cells confirming cellular heterogeneity. Multidimensional scaling analysis using Manhattan distances between cell types showed that NFPA gonadotropes were closer in gene expression to healthy gonadotropes among all pituitary cell types. In addition, we observed differences in the macrophage and endothelial cell populations between tumors and healthy pituitaries. Next, we studied gene regulatory circuitry (regulated gene, modulating transcription factor and its chromatin interaction site) using the new Control of Regulation Extracted from Multiomics Assays (CREMA, [1]) multiome analysis method which showed high variation between normal and tumor gonadotropes. Within each adenoma, the NFPA tumor cells encompassed two main subgroups of cells, one group (GT+ marker tumor cells) expressing established gonadotrope markers and another group not (GT- marker tumor cells). GT+ and GT- tumor cells formed a cluster distinct from healthy gonadotropes. GT+ and GT- tumor cells differed by their level of expression of mitochondrial genes, suggesting decreased aerobic capacity associated with the GT- tumor subgroup. Interestingly, differential analyses between the healthy and the NFPA gonadotropes from same-cell multiome data highlighted dissimilar gene expression and chromatin accessibility patterns.Our newly collected single cell data characterize the difference between NFPA tumor cells and normal gonadotrope cells. Our results suggest a Warburg-effect like difference in aerobic respiratory capacity among tumor cells within the same pituitary adenoma. Overall, this study brings new insights into the molecular characteristics of NFPAs, including tumor cell heterogeneity, and represents a new resource for the field. [1] PMID: 38084892. Presentation: 6/1/2024

Journal of the Endocrine SocietyVol. 8(Supplement_1)
Cedars-Sinai Medical Center (US), Mexican Social Security Institute (MX), King's College London (GB), Princeton University (US), Hospital de Especialidades (MX), Flatiron Health (United States) (US), Flatiron Institute (US), Technische Universität Dresden (DE), Icahn School of Medicine at Mount Sinai (US)
Good health and well-being
Openalex Percentile: Top 72%
Pituitary Gland Disorders and Treatments
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.