Q-omics provides the consensus-scored C18orf32 profile across patient tissues and cancer cell-line models. C18orf32 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in SCLC. Among the 18 cancer types available for tumor–normal comparison, C18orf32 is differentially expressed in 10, with the highest sampling consensus in THCA. Additionally, C18orf32 protein abundance shows 21,389 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight SCLC, THCA, and PDAC as cancer lineages where C18orf32 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 C18orf32 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes C18orf32 survival associations across molecular data types. C18orf32 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (2) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible C18orf32 RNA expression–survival associations across cancer types. High C18orf32 expression shows unfavorable associations in SCLC and UVM, but favorable associations in KIRC, MESO, THYM and PAAD. The SCLC 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 SCLC as the clearest survival context for C18orf32 RNA expression.
This table summarizes C18orf32 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 4. The strongest signals are observed in THCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for C18orf32. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. C18orf32 shows lower tumor expression in THCA, COAD, KIRP, LUSC and READ and higher tumor expression in LIHC. The THCA box plot shows higher C18orf32 RNA expression in normal versus tumor tissue (log2 FC = −1.170, t-test p < 0.001).
This table shows molecular features associated with C18orf32 in patient tissues and cancer cell lines. In patient samples, C18orf32 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, C18orf32 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and LUNG_SCLC.
