Dataset Information

LC-MS/MS analysis of human thyroid cystic fluid and thyroid cancer cell secreted proteins

ABSTRACT: Thyroid ultrasound and ultrasound-guided fine-needle aspiration (USG/FNA) biopsy are currently used for diagnosing papillary thyroid carcinoma (PTC), but their detection limit could be improved by combining other biomarkers. To discover novel PTC biomarkers, we herein applied a GeLC-MS/MS strategy to analyze the proteome profiles of serum-abundant-protein-depleted FNA cystic fluid from benign and PTC patients, as well as two PTC cell line secretomes. From them, we identified 346, 488, and 2105 proteins, respectively. Comparative analysis revealed that 191 proteins were detected in the PTC but not the benign cystic fluid samples, and thus may represent potential PTC biomarkers. Among these proteins, 101 were detected in the PTC cell line secretomes, and seven of them (NPC2, CTSC, AGRN, GPNMB, DPP4, ERAP2, and SH3BGRL3) were reported in public PTC transcriptome datasets as having 4681 elevated mRNA expression in PTC. Immunoblot analysis confirmed the elevated expression levels of five proteins (NPC2, CTSC, GPNMB, DPP4, and ERAP2) in PTC versus benign cystic fluids. Immunohistochemical studies from near 100 pairs of PTC tissue and their adjacent non-tumor counterparts further showed that AGRN (n = 98), CTSC (n = 99), ERAP2 (n = 98) and GPNMB (n = 100) were significantly (p<0.05) overexpressed in PTC and higher expression levels of AGRN and CTSC were also significantly associated with metastasis and poor prognosis of PTC patients. Collectively, our results indicate that an integrated analysis of FNA cystic fluid proteome, cancer cell secretome and tissue transcriptome datasets represents a useful strategy for efficiently discovering novel PTC biomarker candidates.

INSTRUMENT(S): LTQ Orbitrap

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Chia-Chun Wu

LAB HEAD: Jau Song Yu

PROVIDER: PXD007532 | Pride | 2018-03-21

REPOSITORIES: Pride

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Publications

Integrated analysis of fine-needle-aspiration cystic fluid proteome, cancer cell secretome, and public transcriptome datasets for papillary thyroid cancer biomarker discovery.

Wu Chia-Chun CC Lin Jen-Der JD Chen Jeng-Ting JT Chang Chih-Min CM Weng Hsiao-Fen HF Hsueh Chuen C Chien Hui-Ping HP Yu Jau-Song JS

Oncotarget 20180104 15

Thyroid ultrasound and ultrasound-guided fine-needle aspiration (USG/FNA) biopsy are currently used for diagnosing papillary thyroid carcinoma (PTC), but their detection limit could be improved by combining other biomarkers. To discover novel PTC biomarkers, we herein applied a GeLC-MS/MS strategy to analyze the proteome profiles of serum-abundant-protein-depleted FNA cystic fluid from benign and PTC patients, as well as two PTC cell line secretomes. From them, we identified 346, 488, and 2105 p ...[more]

PMID: 29552294

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Project description:The biology underlying nodal metastasis is poorly understood. Transcriptome profiling has helped to characterize both primary tumors seeding nodal metastasis and the metastasis themselves. The interpretation of these data, however, is not without ambiguities. Here we profiled the transcriptomes of 17 papillary thyroid cancer (PTC) nodal metastases, associated primary tumors and primary tumors from N0 patients. We also included patient-matched normal thyroid and lymph node samples as controls to address some limits of previous studies. We found that the transcriptomes of patient-matched primary tumors and metastases were more similar than of unrelated metastases/primary pairs, a result also reported in other organ systems, and that part of this similarity reflected patient background. We found that the comparison of patient-matched primary tumors and metastases was heavily confounded by the presence of lymphoid tissues in the metastasis samples. An original data adjustment procedure was developed to circumvent this problem. It revealed a differential expression of stroma-related gene expression signatures also regulated in other organ systems. The comparison of N0 vs. N+ primary tumors uncovered a signal irreproducible across independent PTC datasets. This signal was also detectable when comparing the normal thyroid tissues adjacent to N0 and N+ tumors, suggesting a cohort specific bias also likely to be present in previous studies with similar statistical power. Classification of N0 vs. N+ yielded an accuracy of 63%, but additional statistical controls not presented in previous studies, revealed that this is likely to occur by chance alone. To address this issue, we used large datasets from The Cancer Genome Atlas and showed that N0 vs. N+ classification rates could not be reached randomly for most cancers. Yet, it was significant, but of limited accuracy (<70%) for thyroid, breast and head and neck cancers. We profiled the transcriptomes of 11 primary PTCs with no detectable nodal invasion, 17 primary PTCs with nodal invasion and 17 patient-matched nodal metastases. We also profiled a number of control samples. These included 24 patient-matched normal thyroid tissues (11 from N0, 13 from N+ patients), and 4 normal lymph nodes; technical and biological replicates including additional nodal metastasis for 3 patients, adjacent blocks for 5 primary tumors, 4 normal thyroid tissues and 1 nodal metastasis.

Dataset Information

LC-MS/MS analysis of human thyroid cystic fluid and thyroid cancer cell secreted proteins

Publications

Integrated analysis of fine-needle-aspiration cystic fluid proteome, cancer cell secretome, and public transcriptome datasets for papillary thyroid cancer biomarker discovery.

Similar Datasets

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