Genes · 2024
LCM-RNAseq Highlights Intratumor Heterogeneity and a lncRNA Signature from Archival Tissues of GH-Secreting PitNETs.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Cis Luca, Nanni Simona, Gessi Marco, Bianchi Antonio, De Martino Sara, Pecci Valeria, Bonvissuto Davide, Carlino Angela, Giacò Luciano, Rindi Guido, Sette Claudio, Grassi Claudio, Gaetano Carlo, Pontecorvi Alfredo, Farsetti Antonella
Аннотация
BACKGROUND: This study explores the potential for hidden variations within seemingly uniform regions of growth hormone-secreting pituitary neuroendocrine tumors (GH-PitNETs). We employed archived tissue samples using Laser Capture Microdissection Sequencing (LCM-RNAseq) to probe the molecular landscape of these tumors at a deeper level.
METHODS: A customized protocol was developed to extract, process, and sequence small amounts of RNA from formalin-fixed, paraffin-embedded (FFPE) tissues derived from five patients with GH-secreting PitNETs and long-term follow-up (≥10 years). This approach ensured precise isolation of starting material of enough quality for subsequent sequencing.
RESULTS: The LCM-RNAseq analysis revealed a surprising level of diversity within seemingly homogeneous tumor regions. Interestingly, the 30 most highly expressed genes included the well-known long noncoding RNA (lncRNA) MALAT1. We further validated the levels of MALAT1 and of other tumor-associated lncRNAs using digital droplet PCR.
CONCLUSIONS: This study demonstrates the potential of LCM-RNAseq to unlock hidden molecular diversity within archived pituitary tumor samples. By focusing on specific cell populations, we identified lncRNAs expressed at different levels within the tumors, potentially offering new insights into the complex biology of GH-secreting PitNETs. This evidence prompts further research into the role of lncRNAs in pituitary neuroendocrine tumor aggressiveness and personalized treatment strategies.
METHODS: A customized protocol was developed to extract, process, and sequence small amounts of RNA from formalin-fixed, paraffin-embedded (FFPE) tissues derived from five patients with GH-secreting PitNETs and long-term follow-up (≥10 years). This approach ensured precise isolation of starting material of enough quality for subsequent sequencing.
RESULTS: The LCM-RNAseq analysis revealed a surprising level of diversity within seemingly homogeneous tumor regions. Interestingly, the 30 most highly expressed genes included the well-known long noncoding RNA (lncRNA) MALAT1. We further validated the levels of MALAT1 and of other tumor-associated lncRNAs using digital droplet PCR.
CONCLUSIONS: This study demonstrates the potential of LCM-RNAseq to unlock hidden molecular diversity within archived pituitary tumor samples. By focusing on specific cell populations, we identified lncRNAs expressed at different levels within the tumors, potentially offering new insights into the complex biology of GH-secreting PitNETs. This evidence prompts further research into the role of lncRNAs in pituitary neuroendocrine tumor aggressiveness and personalized treatment strategies.