Q-omics provides the consensus-scored SPCS3 profile across patient tissues and cancer cell-line models. SPCS3 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, SPCS3 is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, SPCS3 protein abundance shows 27,242 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UCEC, KIRC, and GBM as cancer lineages where SPCS3 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 SPCS3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SPCS3 survival associations across molecular data types. SPCS3 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (2) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SPCS3 RNA expression–survival associations across cancer types. High SPCS3 expression shows unfavorable associations in UVM, LGG, CESC and PAAD, but favorable associations in UCEC and KIRC. The UCEC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify UCEC as the clearest survival context for SPCS3 RNA expression.
This table summarizes SPCS3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 7. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SPCS3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SPCS3 shows lower tumor expression in THCA and LUSC and higher tumor expression in KIRC, LIHC, HNSC and BRCA. The KIRC box plot shows higher SPCS3 RNA expression in tumor versus normal tissue (log2 FC = +0.509, t-test p < 0.001).
This table shows molecular features associated with SPCS3 in patient tissues and cancer cell lines. In patient samples, SPCS3 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, SPCS3 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 URINARY_TRACT and BONE.
