Spatial transcriptomics reveal PI3K-AKT and metabolic alterations in aggressive, treatment-resistant lactotroph pituitary neuroendocrine tumors

Abstract

Clinically aggressive lactotroph pituitary neuroendocrine tumors (PitNET) are invasive tumors with an unusually rapid growth rate despite maximally tolerated doses of dopamine agonist (DA). We aimed to unravel the molecular heterogeneity of lactotroph PitNET and to identify biomarkers of aggressiveness and resistance to pharmacological treatment. A total of 13 patients harboring DA-resistant lactotroph PitNET were included in this study. Visium Spatial Transcriptomics (ST), whole transcriptome sequencing (WTS), and whole exome sequencing (WES) were performed in tumors from 4 of these patients; WTS and WES was carried out in 5; tumors from two patients underwent ST and WES and tumors from two other patients underwent only ST. Tumors were classified as null or partial responders according to their response to DA treatment. The eight PitNET analyzed by ST exhibited significant intratumoral heterogeneity, with clones showing alterations in PI3K/AKT and lipid metabolism pathways, particularly inositol phosphate, glycerophospholipid, and sphingolipid metabolism. The cell-cell communication analysis showed FGF-FGFR ligand receptor interaction whilst the transcription factors RXRA and CREM showed participation in both groups. A trajectory exploration was performed by including all PitNET together in a single analysis to determine whether there was a tendency or molecular pathway showing a differentiation pattern that would guide the transition from a partially responsive PitNET to a completely unresponsive one. We did not observe any such pattern. All of these findings were corroborated in the cohort of DA-resistant PitNETs in which only bulk WTS and WES were performed. The bulk WTS corroborated lipid metabolism and PI3K-AKT pathway alteration in PitNET, whereas the WES showed only SF3β1 and TP53 variants in one tumor each. Our work suggests that the PI3K/AKT pathway may constitute a molecular target at which to aim therapeutic strategies designed to treat aggressive and DA-resistant lactotroph PitNET.

Keywords: Aggressive PitNET; Cabergoline; Lactotroph PitNET; Pharmacological resistant; Prolactinoma; Resistant; Spatial transcriptomic.

Fig. 1

Panels a-h) Different cell clusters that comprise tumor mass and the cell deconvolution of each tumor analyzed by spatial transcriptomics. They are organized by their response to pharmacological therapy as completely unresponsive and partially responsive. Tumor complexity increases as response to therapy worsens. Tumor cluster range from 3 to 10 cell clusters. The tumor that was treated primarily with cabergoline showed the lowest number of clusters (a), the partially responsive tumors showed five and eight cell clusters and finally the completely unresponsive tumors showed five, six, seven, eight and ten cell clusters. Tumors are mainly comprised by tumor cells, stem cells, macrophages and endothelial cells, as noted by gene expression deconvolution, H&E analysis and immunohistochemistry

Fig. 2

Panels a) and b) portray the UMAP and heatmap of the spots comprising all analyzed tumors clustered by sample, showing shared gene expression profiles as most samples group close together, whereas c) and d) depict the UMAP and heatmap clustering by therapy response, again showing shared gene expression profiles as most samples group close together. Panels e-f) show the altered pathways in null and partial responders, respectively

Fig. 3

Panel a) Bubble plot of the altered metabolic pathways. Tumors from totally unresponsive patients showed alterations in inositol phosphate, glycerolipid, and pyruvate metabolism. Tumors from partially responsive patients displayed representation of fatty acid elongation, fatty acid degradation and ether lipid metabolism. The metabolism of nucleic acid precursors such as pyrimidine metabolism and pentose phosphate pathways are represented in both lesions. Panels b-i) show the spots with lipid metabolism from the null and partially responsive lesions

Fig. 4

Panels a-h) show the cell-cell interaction networks among clusters from all analyzed PitNET, showing COL6A1-CD44, FGF9-FGFR1, HSPG2-DAG1, MIF-CD74, APP-CD74 and PTN-NCL

Fig. 5

Panels a) and b) show the PI3K-AKT and fatty acid metabolism gene expression in bulk RNAseq from therapy resistant tumor showing expression in both null and partial responders. Panel c) Metaflux analysis results showing mostly alteration in lipid metabolism