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The transcriptional landscape of metastatic hormone-naïve prostate cancer

ABSTRACT: Background Metastatic hormone-naïve prostate cancer (mHNPC) is an infrequent form of this tumour type that is characterized by metastasis at the time of diagnosis and accounts for 50% of prostate cancer-related deaths. Despite the extensive characterization of localized and metastatic castration resistant prostate cancer (mCRPC), the molecular characteristics of mHNPC remain largely unexplored. Results Here we provide the first extensive transcriptomics characterization of mHNPC. We generated discovery and validation bulk and single-cell RNA-Seq datasets and performed integrative computational analysis in combination with experimental studies. Our results provide unprecedented evidence of the distinctive transcriptional profile of mHNPC and identify stroma remodelling as a predominant feature of these tumours. Importantly, we discover a central role for the transcription factor SOX11 in triggering a heterotypic communication that is associated to the acquisition of metastatic properties. Conclusions Our study will constitute an invaluable resource for a profound understanding of mHNPC that can influence patient management.

INSTRUMENT(S): timsTOF Pro

ORGANISM(S): Homo Sapiens (human)

DISEASE(S): Prostate Adenocarcinoma

SUBMITTER: Mikel Azkargorta

LAB HEAD: Felix Elortza

PROVIDER: PXD063665 | Pride | 2025-05-07

REPOSITORIES: Pride

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			Action	DRS
	221216_221212A_Natalia_10_S1-A10_1_6838.d.rar	Other
	221216_221212A_Natalia_11_S1-A11_1_6839.d.rar	Other
	221216_221212A_Natalia_12_S1-A12_1_6840.d.rar	Other
	221216_221212A_Natalia_13_S1-B1_1_6841.d.rar	Other
	221216_221212A_Natalia_14_S1-B2_1_6842.d.rar	Other

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Project description:Achieved biospecimens annotated with patient clinical characteristics are unique resources for translational research. However, RNA extracted from the achieved tissues is often degraded. RNA degradation can have a significant impact on the measure of transcript abundance that can lead to an increase rate of erroneous differentially expressed genes. Here, we are presenting the transcript integrity number (TIN) algorithm to measure the RNA degradation at transcript level. When applied to RNA-seq datasets generated from human brain Glioblastome cell line, human peripheral blood mononuclear cells, and metastatic castration resistant prostate cancer (mCRPC) clinical tissues, TIN provided a more reliable and more sensitive measure of RNA degradation than RIN, as demonstrated by much higher concordance with the RNA fragment size estimated from read pairs. More importantly, when comparing 10 mCRPC samples with lower RNA quality to another 10 samples with higher RNA quality, we demonstrated that calibrating gene quantification with TIN scores could mitigate RNA degradation effects and greatly improve gene expression analysis. The detected differentially expressed genes before TIN correction were predominantly ribosomal genes. However, when we adjusted gene quantifications with the corresponding TIN scores, we found differentially expressed genes were highly enriched in prostate cancer specific pathways. When further evaluating the performance of TIN correction using synthetic spike-in transcripts with predetermined abundance in RNA-seq data generated from Sequencing Control Consortium (SEQC), we found TIN adjustment had a better control of false positives and false negatives (sensitivity = 0.89, specificity = 0.91), as compared to gene expression analysis results without TIN correction (sensitivity =0.98, specificity = 0.50). RNA sequencing of 20 bone-metastatic castration resistant prostate cancer (mCRPC) using Illumina HiSeq 2500. Out of 20 mCRPC samples, 10 samples have relative low RNA integrity and another 10 samples have relative higher RNA integrity as measured by Agilent RIN score.

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The transcriptional landscape of metastatic hormone-naïve prostate cancer

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