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Fig 1.

Characteristics of post-translational modifications (PTMs) in single-cell RNA sequencing (scRNA-seq) of osteosarcoma (OS).

(A) Batch effects were mitigated using the CellCycleScoring function. (B) A UMAP plot visualizes 49 distinct cell subpopulations. (C, D) UMAP plots depict the distributions of 7 major cell types. (C) PTMs activity scores across individual cells in scRNA-seq data. (D) Results of spot clustering analysis in ST data. (E) PTMs activity scores across individual cells in scRNA-seq data.

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Fig 2.

Pseudotemporal and intercellular communication analyses.

(A) Developmental heatmap of PTMs in osteoblastic cells, illustrating temporal progression (left to right) and expression levels (low: blue; high: red). (B) Classification of osteoblastic cells into normal and OS groups. (C) Classification into PTMs-high (PTMshighos) and PTMs-low (PTMslowos) subgroups. (D, E) Pseudotemporal trajectory analyses of osteoblastic cells, with the developmental starting point at the left root. (F) Branch-specific progression mapping within the PTMs score+ osteoblastic cell subpopulation.

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Fig 3.

The ST, spatial gene score, and spatial PTMs map of OS.

(A, B) High-resolution tissue images of OS, highlighting distinct cell clusters identified via scRNA-seq. Clusters are classified based on PTMs scores, dividing osteoblastic cells into PTMshigh and PTMslow groups, with spatial distribution mapped onto tissue images. (C, D) Spatial interactions between PTMshigh/PTMslow osteoblastic cells and other cell types within the core region. (E, F) Spatial interactions within a 5-unit radius. (G, H) Spatial interactions within a 15-unit radius.

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Fig 4.

Constructing and validating consensus machine learning-derived post-translational modification gene signature (CMDPTMS) in OS.

(A) C-index of each model across cohorts, ranked by average C-index in validation cohorts. (B-D) AUC values for 1-year, 3-year, and 5-year predictions across cohorts, ranked by average AUC in validation cohorts.

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Fig 5.

Evaluation of prognostic model performance.

(A) Venn diagram showing overlapping features among the top five prognostic models based on C-index and AUC values at 1-, 3-, and 5-year intervals. (B) C-index distribution of the StepCox[forward] + Ridge survival model across cohorts. (C) Temporal discrimination accuracy of the model assessed via 1-, 3-, and 5-year AUC values. (D) ROC curves at 1-, 3-, and 5-year intervals evaluating predictive performance in distinct datasets.

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Fig 6.

Tumor microenvironment (TME)-related molecular characteristics in high- and low-CMDPTMS patients.

(A) Comparison of TME immune cell type signatures. (B) Distribution of immune suppression signatures. (C) Distribution of immune exclusion signatures. (D) Comparative analysis of immunotherapy biomarkers. (E, F) Differences in tumor mutational burden (TMB). (G, H) Survival analysis integrating CMDPTMS with TMB.

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Fig 7.

Therapeutic response prediction.

(A) Correlation between CMDPTMS and therapeutic response prediction. (B, C) Correlation and differential analysis of drug sensitivity for potential drugs screened from PRISM and CTRP datasets.

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Fig 8.

ScRNA-seq and ST profiles of core genes in OS.

(A) Bubble plots depicting core gene expression across cell types in scRNA-seq data. (B) UMAP plots illustrate core gene distribution and expression in different cell types. (C) Violin plots showing core gene expression across cell types in ST data.

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