Dataset Information

Identification of a 5-gene Signature Panel for the Prediction of Prostate Cancer Progression

ABSTRACT: Quantitative proteomics analysis was performed on two samples of localized prostate tumors from one patient (R40) and eight samples from metastatic prostate cancer sites. One sample from the right lung, one sample from the peritoneal lymph node, and two samples from the mediastinal lymph node were collected from one patient (R43). One sample from the liver and one sample from kidney were collected from another patient (R45). One sample from the periaortic lymph node and one sample from the dura were collected from another patient (R55).

INSTRUMENT(S): LTQ Orbitrap Elite

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Lung, Liver, Lymph Node, Dura Mater, Kidney

DISEASE(S): Prostate Cancer

SUBMITTER: Sharon Pitteri

LAB HEAD: Sharon Pitteri

PROVIDER: PXD056300 | Pride | 2024-11-21

REPOSITORIES: pride

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Identification of a 5-gene signature panel for the prediction of prostate cancer progression.

Shen Michelle M García-Marqués Fernando F Muruganantham Arvind A Liu Shiqin S White James Robert JR Bermudez Abel A Rice Meghan A MA Thompson Kelsey K Chen Chun-Liang CL Hung Chia-Nung CN Zhang Zhao Z Huang Tim H TH Liss Michael A MA Pienta Kenneth J KJ Pitteri Sharon J SJ Stoyanova Tanya T

British journal of cancer 20241014 11

<h4>Background</h4>Despite nearly 100% 5-year survival for localised prostate cancer, the survival rate for metastatic prostate cancer significantly declines to 32%. Thus, it is crucial to identify molecular indicators that reflect the progression from localised disease to metastatic prostate cancer.<h4>Methods</h4>To search for molecular indicators associated with prostate cancer metastasis, we performed proteomic analysis of rapid autopsy tissue samples from metastatic prostate cancer (N = 8) ...[more]

PMID: 39402324

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Project description:Lymph node metastasis is a poor prognosis indicator in esophageal cancer. Although tumor spreading currently forms the main basis for therapy selection, the molecular mechanisms underlying the metastatic pathway remain insufficiently understood. Several studies aimed to investigate these mechanisms but focused mainly on regulatory patterns in the tumors themselves and/or the invaded lymph nodes. To date no study has yet investigated the potential changes on transcription level, which take place within the yet non-invaded niche. Here we provide a comprehensive description of these regulations in patients. In this study the transcriptomic profiles of regional lymph nodes were determined for two patient groups: patients classified as pN1 (metastasis) or pN0 (no metastasis) respectively. All investigated lymph nodes, also those from pN1 patients, were still free of metastasis. The gene expression data was obtained via microarray analysis. Top candidates were validated via PCR and immunohistochemistry. The results show that regional lymph nodes of pN1 patients differ decisively from those of pN0 patients – even before metastasis has taken place. In the pN0 group distinct immune response patterns were observed. In contrast, lymph nodes of the pN1 group exhibited a clear profile of reduced immune response and reduced proliferation, but increased apoptosis, enhanced hypoplasia and morphological conversion processes. DKK1 was the most significant gene associated with the molecular mechanisms taking place in lymph nodes of patients suffering from metastasis (pN1). We assume that the two molecular profiles observed constitute two different stages of a progressive disease. Finally we suggest that DKK1 might play an important role within the mechanisms leading to lymph node metastasis. First, samples were classified according to the principal status of the patients exhibiting (pN1 group) or non-exhibiting (pN0 group) metastasis in regional lymph nodes. The comparison of pN1 and pN0 patients should highlight the general differences in regulations that might lead to or prevent from metastasis. Second, two lymph node samples were collected from each patient, one node located close to the tumor (regional) and the second node distant to the tumor. While the distant nodes served as reference sample the regional nodes were investigated for transcriptional regulations. Key to the work presented here is that all nodes investigated were made sure to be still metastasis free, independent of the patients’ pN1/pN0 classification and of the location relative to the tumor. This should allow the identification of early changes occurring prior to metastasis homing.

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	MET04_02.raw_20181126_Byonic_database.xlsx	Xlsx