Q-omics provides the consensus-scored SPP2 profile across patient tissues and cancer cell-line models. SPP2 expression is associated with patient survival in 15 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, SPP2 is differentially expressed in 5, with the highest sampling consensus in LIHC. Additionally, SPP2 protein abundance shows 18,417 significant protein co-abundance associations, with the highest sampling consensus in CCRCC. Together, these results highlight HNSC, LIHC, and CCRCC as cancer lineages where SPP2 shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for SPP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SPP2 survival associations across molecular data types. SPP2 RNA expression shows survival associations in the most cancer types (15), followed by mutation status (2) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SPP2 RNA expression–survival associations across cancer types. High SPP2 expression shows unfavorable associations in HNSC, BRCA, CHOL, BLCA and ESCA, but favorable associations in LIHC. The HNSC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify HNSC as the clearest survival context for SPP2 RNA expression.
This table summarizes SPP2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5, while mass-spec protein shows differences in 9. The strongest signals are observed in LIHC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for SPP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SPP2 shows lower tumor expression in LIHC and CHOL and higher tumor expression in LUAD, LUSC and HNSC. The LIHC box plot shows higher SPP2 RNA expression in normal versus tumor tissue (log2 FC = −3.146, t-test p < 0.001).
This table shows molecular features associated with SPP2 in patient tissues and cancer cell lines. In patient samples, SPP2 shows the broadest associations at the RNA and protein expression levels, with CCRCC recurring as the lineage with the largest associated feature set. In cancer cell lines, SPP2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BREAST.
