Computational and Structural Biotechnology Journal
How can proteomic measurement and integration with other omics contribute complementary information to precision oncology?
This narrative review surveys mass spectrometry, aptamer-based assays, proximity extension assays, protein microarrays and combined single-cell methods. It explains how proteomic measurements and computational integration may reveal molecular subtypes, biomarkers, primary-tumor signatures and treatment-related biology. Figures 1-3 and Table 1 organize technologies, analysis and published application examples. The article is a synthesis of earlier research, so application-specific efficacy and accuracy estimates should be traced to their original studies. The review highlights costs, specimen availability and the need for integrated analysis as practical constraints.
Zhaokai Zhou, Ruiqi Zhang, Aoyang Zhou, Jinxiang Lv, Shuang Chen, Haijiao Zou, Ge Zhang, Ting Lin, Zhan Wang, Yuyuan Zhang, Siyuan Weng, Xinwei Han, Zaoqu Liu. Proteomics appending a complementary dimension to precision oncotherapy. Computational and Structural Biotechnology Journal. 2024. https://doi.org/10.1016/j.csbj.2024.04.044
Proteomics appending a complementary dimension to precision oncotherapy
Narrative review of proteomic measurement technologies, data integration and potential oncology applications; it reports no new clinical cohort or pooled treatment effect.
These are review-structure counts, not pooled patient denominators or newly measured performance.
Secondary technical overview; no head-to-head accuracy comparison is performed.
Source locator: Proteomics analysis technology subsections; Fig. 1A-D
Methodological synthesis of earlier studies rather than a newly trained integrative model.
| Measure | Value |
|---|---|
| illustrated integration methods | TieDIE, PCA and NMF |
| overview locator | Fig. 1E and Fig. 3 |
Source locator: Proteomics data analysis and integration; Fig. 1E; Future directions for proteomics pairing with other omics; Fig. 3
Published examples are summarized; clinical utility is not established collectively by this review.
| Measure | Value |
|---|---|
| application-summary table | Table 1 |
| illustrative application figure | Fig. 2 |
Source locator: Proteomics in precision oncotherapy subsections; Fig. 2; Table 1; Conclusions
It covers mass spectrometry, aptamer-based assays, proximity extension assays, protein microarrays and combined single-cell techniques.
Evidence: KF1
Integration connects protein measurements with other molecular layers; the review illustrates approaches including TieDIE, PCA and NMF.
Evidence: KF2
The review discusses molecular subtyping, primary-site identification, biomarkers, mechanisms and immunotherapy applications using published examples.
Evidence: KF3
| Row ID | Component | Context | Finding | Evidence Level | Scope | Source Locator | Evidence refs |
|---|---|---|---|---|---|---|---|
| evidence-kf1 | The review distinguishes major proteomic assay families and their measurement principles. | Secondary technical overview; no head-to-head accuracy comparison is performed. | technology subsection groups: 5: mass spectrometry, aptamers, proximity extension assay, protein microarrays, combined single-cell techniques | Secondary synthesis of published proteomics studies | An overview of assay principles and integration strategies. | Proteomics analysis technology subsections; Fig. 1A-D | KF1 |
| evidence-kf2 | Proteomic data integration is presented as a way to connect molecular layers and protein-network behavior. | Methodological synthesis of earlier studies rather than a newly trained integrative model. | illustrated integration methods: TieDIE, PCA and NMF; overview locator: Fig. 1E and Fig. 3 | Secondary synthesis of published proteomics studies | Secondary contextualization of published precision-oncology examples. | Proteomics data analysis and integration; Fig. 1E; Future directions for proteomics pairing with other omics; Fig. 3 | KF2 |
| evidence-kf3 | The review organizes potential oncology uses including subtyping, primary-site identification, biomarkers and immunotherapy. | Published examples are summarized; clinical utility is not established collectively by this review. | application-summary table: Table 1; illustrative application figure: Fig. 2 | Secondary synthesis of published proteomics studies | Secondary contextualization of published precision-oncology examples. | Proteomics in precision oncotherapy subsections; Fig. 2; Table 1; Conclusions | KF3 |
It covers mass spectrometry, aptamer-based assays, proximity extension assays, protein microarrays and combined single-cell techniques.
Evidence: KF1
Integration connects protein measurements with other molecular layers; the review illustrates approaches including TieDIE, PCA and NMF.
Evidence: KF2
The review discusses molecular subtyping, primary-site identification, biomarkers, mechanisms and immunotherapy applications using published examples.
Evidence: KF3
No. It is a narrative synthesis; quantitative claims about individual biomarkers or therapies should be checked against the original primary studies.
Evidence: KF3
Study-level author-maintained evidence summary. Not participant-level data and not a ready-to-pool meta-analysis dataset. For formal citation, use the original article DOI.
Download study-level evidence CSV (UTF-8)Formula safety: cells starting with =, +, -, @ (after leading whitespace), or tab/CR/LF are prefixed with an apostrophe. Treat all cells as text; remove only that safety prefix when recovering the original string.
These records identify the same original work; database inclusion is not evidence of scientific validity or clinical benefit.