Q-omics provides the consensus-scored ABCC6 profile across patient tissues and cancer cell-line models. ABCC6 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ABCC6 is differentially expressed in 11, with the highest sampling consensus in KICH. Additionally, ABCC6 RNA expression shows 18,087 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight KIRC, KICH, and LUAD as cancer lineages where ABCC6 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 ABCC6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ABCC6 survival associations across molecular data types. ABCC6 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (7) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ABCC6 RNA expression–survival associations across cancer types. High ABCC6 expression shows unfavorable associations in UVM, SCLC and HNSC, but favorable associations in KIRC, KIRP and LIHC. 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 ABCC6 RNA expression.
This table summarizes ABCC6 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 4. The strongest signals are observed in LUAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ABCC6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ABCC6 shows lower tumor expression in KICH, LUAD, LUSC, COAD and BRCA and higher tumor expression in KIRC. The KICH box plot shows higher ABCC6 RNA expression in normal versus tumor tissue (log2 FC = −2.581, t-test p < 0.001).
This table shows molecular features associated with ABCC6 in patient tissues and cancer cell lines. In patient samples, ABCC6 shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, ABCC6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Leukemia.
