Q-omics provides the consensus-scored SDCBP profile across patient tissues and cancer cell-line models. SDCBP expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, SDCBP is differentially expressed in 13, with the highest sampling consensus in KIRP. Additionally, SDCBP protein abundance shows 20,852 significant protein co-abundance associations, with the highest sampling consensus in UCEC. Together, these results highlight UVM, KIRP, and UCEC as cancer lineages where SDCBP 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 SDCBP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SDCBP survival associations across molecular data types. SDCBP RNA expression shows survival associations in the most cancer types (25), followed by mutation status (1) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SDCBP RNA expression–survival associations across cancer types. High SDCBP expression shows unfavorable associations in UVM, HNSC, LUAD, LGG, LUSC and KICH. The UVM 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 UVM as the clearest survival context for SDCBP RNA expression.
This table summarizes SDCBP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 4. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SDCBP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SDCBP shows lower tumor expression in THCA, LUAD and KICH and higher tumor expression in KIRP, HNSC and LIHC. The KIRP box plot shows higher SDCBP RNA expression in tumor versus normal tissue (log2 FC = +0.938, t-test p < 0.001).
This table shows molecular features associated with SDCBP in patient tissues and cancer cell lines. In patient samples, SDCBP shows the broadest associations at the RNA and protein expression levels, with UCEC recurring as the lineage with the largest associated feature set. In cancer cell lines, SDCBP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BREAST.
