Q-omics provides the consensus-scored ABHD17C profile across patient tissues and cancer cell-line models. ABHD17C expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, ABHD17C is differentially expressed in 16, with the highest sampling consensus in KIRC. Additionally, ABHD17C RNA expression shows 19,415 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and KIRC as cancer lineages where ABHD17C 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 ABHD17C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ABHD17C survival associations across molecular data types. ABHD17C RNA expression shows survival associations in the most cancer types (26), followed by mutation status (3) 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 ABHD17C RNA expression–survival associations across cancer types. High ABHD17C expression shows unfavorable associations in ACC, MESO, THYM and UVM, but favorable associations in LUSC and BLCA. The ACC 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 ACC as the clearest survival context for ABHD17C RNA expression.
This table summarizes ABHD17C tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for ABHD17C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ABHD17C shows lower tumor expression in KIRC and KIRP and higher tumor expression in THCA, STAD, LIHC and LUAD. The KIRC box plot shows higher ABHD17C RNA expression in normal versus tumor tissue (log2 FC = −1.972, t-test p < 0.001).
This table shows molecular features associated with ABHD17C in patient tissues and cancer cell lines. In patient samples, ABHD17C shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, ABHD17C RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and LARGE_INTESTINE.
