Q-omics provides the consensus-scored VDAC2 profile across patient tissues and cancer cell-line models. VDAC2 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, VDAC2 is differentially expressed in 12, with the highest sampling consensus in BLCA. Additionally, VDAC2 protein abundance shows 22,022 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LUAD, BLCA, and GBM as cancer lineages where VDAC2 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 VDAC2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes VDAC2 survival associations across molecular data types. VDAC2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible VDAC2 RNA expression–survival associations across cancer types. High VDAC2 expression shows unfavorable associations in LUAD, HNSC, ACC, LIHC and BLCA, but favorable associations in KIRC. The LUAD 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 LUAD as the clearest survival context for VDAC2 RNA expression.
This table summarizes VDAC2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 6. The strongest signals are observed in BLCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for VDAC2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. VDAC2 shows lower tumor expression in BLCA and THCA and higher tumor expression in LIHC, LUSC, LUAD and CHOL. The BLCA box plot shows higher VDAC2 RNA expression in normal versus tumor tissue (log2 FC = −0.625, t-test p < 0.001).
This table shows molecular features associated with VDAC2 in patient tissues and cancer cell lines. In patient samples, VDAC2 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, VDAC2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and UPPER_AERODIGESTIVE_TRACT.
