Q-omics provides the consensus-scored SV2B profile across patient tissues and cancer cell-line models. SV2B expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, SV2B is differentially expressed in 11, with the highest sampling consensus in THCA. Additionally, SV2B RNA expression shows 20,641 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight BLCA, THCA, and GBM as cancer lineages where SV2B 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 SV2B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SV2B survival associations across molecular data types. SV2B RNA expression shows survival associations in the most cancer types (21), followed by mutation status (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SV2B RNA expression–survival associations across cancer types. High SV2B expression shows unfavorable associations in BLCA, MESO, UCEC, OV and LUAD, but favorable associations in ESCA. The BLCA 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 BLCA as the clearest survival context for SV2B RNA expression.
This table summarizes SV2B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in THCA for RNA.
This table ranks reproducible tumor–normal expression differences for SV2B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SV2B shows lower tumor expression in THCA, COAD, BRCA, KIRC, UCEC and READ. The THCA box plot shows higher SV2B RNA expression in normal versus tumor tissue (log2 FC = −0.464, t-test p < 0.001).
This table shows molecular features associated with SV2B in patient tissues and cancer cell lines. In patient samples, SV2B 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, SV2B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BONE.
