To address the increasing need for detecting and validating protein biomarkers in clinical specimens,mass spectrometry(MS)-based targeted proteomic techniques,including the selected reaction monitoring(SRM),parallel r...To address the increasing need for detecting and validating protein biomarkers in clinical specimens,mass spectrometry(MS)-based targeted proteomic techniques,including the selected reaction monitoring(SRM),parallel reaction monitoring(PRM),and massively parallel dataindependent acquisition(DIA),have been developed.For optimal performance,they require the fragment ion spectra of targeted peptides as prior knowledge.In this report,we describe a MS pipeline and spectral resource to support targeted proteomics studies for human tissue samples.To build the spectral resource,we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker.We then applied the workflow to generate DPHL,a comprehensive DIA pan-human library,from 1096 data-dependent acquisition(DDA)MS raw files for 16 types of cancer samples.This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer(PCa)patients.Thereafter,PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated.As a second application,the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma(DLBCL)patients and 18 healthy control subjects.Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM.These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery.DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.展开更多
Dear editors,Colorectal cancer(CRC)is the second leading cause of cancer deaths in developed countries[1].The malignant transformation from small clumps to cancer takes about 10 years[2].This study aimed to characteri...Dear editors,Colorectal cancer(CRC)is the second leading cause of cancer deaths in developed countries[1].The malignant transformation from small clumps to cancer takes about 10 years[2].This study aimed to characterize proteomic dynamics associated with CRC development and progres-sion,and identify novel therapeutic targets for intercepting the underlying oncogenic processes.We have optimized pressure cycling technology(PCT)coupled with data-independent acquisition mass spectrometry(DIA-MS)for robust and reproducible proteomic analysis of biopsy-level formalin-fixed paraffin-embedded(FFPE)tissues[3].展开更多
基金supported by the National Natural Science Foundation of China(Grant No.81972492)National Science Fund for Young Scholars(Grant No.21904107)+7 种基金Zhejiang Provincial Natural Science Foundation for Distinguished Young Scholars(Grant No.LR19C050001)Hangzhou Agriculture and Society Advancement Program(Grant No.20190101A04)Westlake Startup Grantresearch funds from the National Cancer Centre Singapore and Singapore General Hospital,Singaporethe National Key R&D Program of China(Grant No.2016YFC0901704)Zhejiang Innovation Discipline Project of Laboratory Animal Genetic Engineering(Grant No.201510)the Netherlands Cancer Society(Grant No.NKI 2014-6651)The Netherlands Organization for Scientific Research(NWO)-Middelgroot(Grant No.91116017)
文摘To address the increasing need for detecting and validating protein biomarkers in clinical specimens,mass spectrometry(MS)-based targeted proteomic techniques,including the selected reaction monitoring(SRM),parallel reaction monitoring(PRM),and massively parallel dataindependent acquisition(DIA),have been developed.For optimal performance,they require the fragment ion spectra of targeted peptides as prior knowledge.In this report,we describe a MS pipeline and spectral resource to support targeted proteomics studies for human tissue samples.To build the spectral resource,we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker.We then applied the workflow to generate DPHL,a comprehensive DIA pan-human library,from 1096 data-dependent acquisition(DDA)MS raw files for 16 types of cancer samples.This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer(PCa)patients.Thereafter,PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated.As a second application,the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma(DLBCL)patients and 18 healthy control subjects.Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM.These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery.DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.
基金supported by the National Key Research and Development Program of China(Grant No.2017YFC0908200),National Natural Science Founda-tion of China(Grant No.81972270,81972492,32027801,21904107),the Zhejiang Provincial Science Foundation for Distinguished Young Scholars(Grant No.LR19C050001),Hangzhou Agriculture and Society Advancement Program(Grant No.20190101A04)and 2019 Zhejiang University Academic Award for Outstanding Doctoral Candidates to YK.S(Grant No.2019071).
文摘Dear editors,Colorectal cancer(CRC)is the second leading cause of cancer deaths in developed countries[1].The malignant transformation from small clumps to cancer takes about 10 years[2].This study aimed to characterize proteomic dynamics associated with CRC development and progres-sion,and identify novel therapeutic targets for intercepting the underlying oncogenic processes.We have optimized pressure cycling technology(PCT)coupled with data-independent acquisition mass spectrometry(DIA-MS)for robust and reproducible proteomic analysis of biopsy-level formalin-fixed paraffin-embedded(FFPE)tissues[3].
