Q-omics provides the consensus-scored SPCS2 profile across patient tissues and cancer cell-line models. SPCS2 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, SPCS2 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, SPCS2 protein abundance shows 22,302 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight UVM, HNSC, and PDAC as cancer lineages where SPCS2 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 SPCS2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SPCS2 survival associations across molecular data types. SPCS2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (1) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SPCS2 RNA expression–survival associations across cancer types. High SPCS2 expression shows unfavorable associations in UVM, ACC, KICH and KIRP, but favorable associations in STAD and OV. 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 SPCS2 RNA expression.
This table summarizes SPCS2 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 5. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SPCS2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SPCS2 shows lower tumor expression in THCA and higher tumor expression in HNSC, KIRC, LIHC, BLCA and STAD. The HNSC box plot shows higher SPCS2 RNA expression in tumor versus normal tissue (log2 FC = +0.676, t-test p < 0.001).
This table shows molecular features associated with SPCS2 in patient tissues and cancer cell lines. In patient samples, SPCS2 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, SPCS2 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 BREAST and BLOOD_Lymphoma.
