Dataset Information

Proteomic Characterization of Prostate Cancer to Distinguish Nonmetastasizing and Metastasizing Primary Tumors and Lymph Node Metastases.

ABSTRACT: Patients with metastatic prostate cancer (PCa) have a poorer prognosis than patients with organ-confined tumors. We strove to uncover the proteome signature of primary PCa and associated lymph node metastases (LNMs) in order to identify proteins that may indicate or potentially promote metastases formation. We performed a proteomic comparative profiling of PCa tissue from radical prostatectomy (RPE) of patients without nodal metastases or relapse at the time of surgical resection (n=5) to PCa tissue from RPE of patients who suffered from nodal relapse (n=5). For the latter group, we also included patient-matched tissue of the nodal metastases. All samples were formalin fixed and paraffin embedded. We identified and quantified more than 1200 proteins by liquid chromatography tandem mass spectrometry with subsequent label-free quantification. An increase of ribosomal or proteasomal proteins in LNM (compared to corresponding PCa) became apparent, while extracellular matrix components rather decreased. Immunohistochemistry (IHC) corroborated accumulation of poly-(ADP-ribose)-polymerase 1 and N-myc-downstream-regulated-gene 3, alpha/beta hydrolase domain-containing protein 11, and protein phosphatase slingshot homolog 3 in LNM. These findings strengthen the present interest in examining PARP inhibitors for the treatment of aggressive PCa. IHC also corroborated increased abundance of retinol dehydrogenase 11 in metastasized primary PCa compared to organ-confined PCa. Generally, metastasizing primary tumors were characterized by an enrichment of proteins involved in cellular lipid metabolic processes with concomitant decrease of cell adhesion proteins. This study highlights the usefulness of a combined proteomic-IHC approach to explore novel aspects in tumor biology. Our initial results open novel opportunities for follow-up studies.

SUBMITTER: Muller AK

PROVIDER: S-EPMC5735259 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Proteomic Characterization of Prostate Cancer to Distinguish Nonmetastasizing and Metastasizing Primary Tumors and Lymph Node Metastases.

Müller Ann-Kathrin AK Föll Melanie M Heckelmann Bianca B Kiefer Selina S Werner Martin M Schilling Oliver O Biniossek Martin L ML Jilg Cordula Annette CA Drendel Vanessa V

Neoplasia (New York, N.Y.) 20171214 2

Patients with metastatic prostate cancer (PCa) have a poorer prognosis than patients with organ-confined tumors. We strove to uncover the proteome signature of primary PCa and associated lymph node metastases (LNMs) in order to identify proteins that may indicate or potentially promote metastases formation. We performed a proteomic comparative profiling of PCa tissue from radical prostatectomy (RPE) of patients without nodal metastases or relapse at the time of surgical resection (n=5) to PCa ti ...[more]

PMID: 29248718

Similar Datasets

Project description:BackgroundThe essential roles of the tumor microenvironment (TME) have been recognized during the initiation and progression of primary lung adenocarcinoma (LUAD). The aim of the present study was to delineate the immune landscape in both primary cancer and matched lymph node metastasis from a cohort of locally advanced stage LUAD patients with distinct outcomes.MethodsFormalin-fixed, paraffin-embedded samples were collected from 36 locally advanced LUAD patients. Transcriptome data of the tumor immune microenvironment were resolved using an immune oncology panel RNA sequencing platform. Bioinformatics approaches were used to determine the differentially expressed genes (DEGs), dysregulated pathways, and immune cell fraction between patients with early recurrence (ER) and late recurrence (LR).ResultsHere, we showed that in primary cancer tissues, 23 DEGs were obtained between patients with ER and LR. Functional analysis revealed that the LR in LUAD patients may be associated with enriched gene sets belonging to the antigen presentation and MHC protein complex, innate immune response, and IFN-γ signaling pathways. Next, the transcriptome data were adopted to quantify immune cell fractions, indicating that high infiltration of mast cells and neutrophils was correlated with ER. Interestingly, similar findings were observed in metastatic lymph nodes from patients suffering from ER or LR. By analyzing the shared immune features of primary cancers and lymphatic metastases, we unraveled the prognostic value and joint utility of two DEGs, CORO1A and S100A8.ConclusionsIn LUAD, the enrichment in antigen presentation, MHC protein complex, and IFN-γ signaling, and low infiltration of neutrophils in primary or metastatic nodules may be indications for a favorable prognosis. Integrated with bioinformatics approaches, transcriptome data of immune-related genes from formalin-fixed, paraffin-embedded (FFPE) samples can effectively profile the landscape of the tumor immune microenvironment and help predict clinical outcomes.

Project description:BackgroundPatients with breast cancer presenting with single lymph node metastasis (from a sentinel node) experience prolonged survival compared to patients with multiple lymph node metastases (≥3). However, little information is available on the genetic and immunological characteristics of breast cancer metastases within the regional lymph nodes as they progress from the sentinel lymph node (SLN) downstream to multiple regional lymph nodes (MLNs).MethodsGenomic profiling was performed using a next-generation sequencing panel covering 520 cancer-related genes in the primary tumour and metastatic lymph nodes of 157 female patients with breast cancer. We included primary tumours, metastatic lymph nodes and adjacent clinically normal lymph nodes (20 patients from the SLN group and 28 patients from the MLNs group) in the whole transcriptome analysis.FindingsThe downstream metastatic lymph nodes (P = 0.029) and the primary breast tumours (P = 0.011) had a higher frequency of PIK3CA mutations compared to the SLN metastasis. We identified a distinct group of 14 mutations from single sentinel node metastasis and a different group of 15 mutations from multiple nodal metastases. Only 4 distinct mutations (PIK3CA, CDK4, NFKBIA and CDKN1B) were conserved in metastases from both lymph node settings. The tumour mutational burden (TMB) was significantly lower in single nodal metastasis compared to the paired primary breast cancer (P = 0.0021), while the decline in TMB did not reach statistical significance in the MLNs group (P = 0.083). In the gene set enrichment analysis, we identified 4 upregulated signatures in both primary tumour and nodal metastases from the MLNs group, including 3 Epithelial-mesenchymal transition(EMT) signatures and 1 angiogenesis signature. Both the CD8/Treg ratio and the CD8/EMT ratio were significantly higher in adjacent normal lymph nodes from patients with a single metastasis in the SLN compared with samples from the MLNs group (P = 0.045 and P = 0.023, respectively). This suggests that the immune defence from the MLNs patients might have a less favourable microenvironment, thus permitting multiple lymph nodes metastasis.InterpretationSingle lymph node metastases and multiple lymph node metastases have significant differences in their molecular profiles and immune profiles. The findings are associated with more aggressive tumour characteristics and less favourable immune charactoristics in patients with multiple nodal metastases compared to those with a single metastasis in the sentinel node.FundingThis work was supported by funds from High-level Hospital Construction Project (DFJH201921), the National Natural Science Foundation of China (81902828 and 82002928), the Fundamental Research Funds for the Central Universities (y2syD2192230), and the Medical Scientific Research Foundation of Guangdong Province (B2019039).

Project description:BACKGROUND:Papillary Thyroid Cancer (PTC) is the most prevalent type of endocrine cancer. Its incidence has rapidly increased in recent decades but little is known regarding its complete microRNA transcriptome (miRNome). In addition, there is a need for molecular biomarkers allowing improved PTC diagnosis. METHODS:We performed small RNA deep-sequencing of 3 PTC, their matching normal tissues and lymph node metastases (LNM). We designed a new bioinformatics framework to handle each aspect of the miRNome: whole expression profiles, isomiRs distribution, non-templated additions distributions, RNA-editing or mutation. Results were validated experimentally by qRT-PCR on normal samples, tumors and LNM from 14 independent patients and in silico using the dataset from The Cancer Genome Atlas (small RNA deepsequencing of 59 normal samples, 495 PTC, and 8 LNM). RESULTS:We performed small RNA deep-sequencing of 3 PTC, their matching normal tissues and lymph node metastases (LNM). We designed a new bioinformatics framework to handle each aspect of the miRNome: whole expression profiles, isomiRs distribution, non-templated additions distributions, RNA-editing or mutation. Results were validated experimentally by qRT-PCR on normal samples, tumors and LNM from 14 independent patients and in silico using the dataset from The Cancer Genome Atlas (small RNA deep-sequencing of 59 normal samples, 495 PTC, and 8 LNM). We confirmed already described up-regulations of microRNAs in PTC, such as miR-146b-5p or miR-222-3p, but we also identified down-regulated microRNAs, such as miR-7-5p or miR-30c-2-3p. We showed that these down-regulations are linked to the tumorigenesis process of thyrocytes. We selected the 14 most down-regulated microRNAs in PTC and we showed that they are potential biomarkers of PTC samples. Nevertheless, they can distinguish histological classical variants and follicular variants of PTC in the TCGA dataset. In addition, 12 of the 14 down-regulated microRNAs are significantly less expressed in aggressive PTC compared to non-aggressive PTC. We showed that the associated aggressive expression profile is mainly due to the presence of the BRAF V600E mutation. In general, primary tumors and LNM presented similar microRNA expression profiles but specific variations like the down-regulation of miR-7-2-3p and miR-30c-2-3p in LNM were observed. Investigations of the 5p-to-3p arm expression ratios, non-templated additions or isomiRs distributions revealed no major implication in PTC tumorigenesis process or LNM appearance. CONCLUSIONS:Our results showed that down-regulated microRNAs can be used as new potential common biomarkers of PTC and to distinguish main subtypes of PTC. MicroRNA expressions can be linked to the development of LNM of PTC. The bioinformatics framework that we have developed can be used as a starting point for the global analysis of any microRNA deep-sequencing data in an unbiased way.

Dataset Information

Proteomic Characterization of Prostate Cancer to Distinguish Nonmetastasizing and Metastasizing Primary Tumors and Lymph Node Metastases.

Publications

Proteomic Characterization of Prostate Cancer to Distinguish Nonmetastasizing and Metastasizing Primary Tumors and Lymph Node Metastases.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets