Q-omics provides the consensus-scored SV2C profile across patient tissues and cancer cell-line models. SV2C expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SV2C is differentially expressed in 13, with the highest sampling consensus in STAD. Additionally, SV2C RNA expression shows 16,119 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRC, STAD, and THYM as cancer lineages where SV2C 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 SV2C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SV2C survival associations across molecular data types. SV2C RNA expression shows survival associations in the most cancer types (19), followed by mutation status (7) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SV2C RNA expression–survival associations across cancer types. High SV2C expression shows unfavorable associations in ACC, UVM and DLBC, but favorable associations in KIRC, THCA and SCLC. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for SV2C RNA expression.
This table summarizes SV2C tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13. The strongest signals are observed in BRCA for RNA.
This table ranks reproducible tumor–normal expression differences for SV2C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SV2C shows lower tumor expression in STAD, BRCA, COAD, LUAD and THCA and higher tumor expression in PRAD. The STAD box plot shows higher SV2C RNA expression in normal versus tumor tissue (log2 FC = −0.420, t-test p = .004).
This table shows molecular features associated with SV2C in patient tissues and cancer cell lines. In patient samples, SV2C shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, SV2C RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and SKIN.
