Q-omics provides the consensus-scored C12orf43 profile across patient tissues and cancer cell-line models. C12orf43 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in SCLC. Among the 18 cancer types available for tumor–normal comparison, C12orf43 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, C12orf43 RNA expression shows 18,535 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight SCLC, HNSC, and ACC as cancer lineages where C12orf43 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 C12orf43 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes C12orf43 survival associations across molecular data types. C12orf43 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (2) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible C12orf43 RNA expression–survival associations across cancer types. High C12orf43 expression shows unfavorable associations in LIHC, MESO and ACC, but favorable associations in SCLC, KIRC and BRCA. The SCLC 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 SCLC as the clearest survival context for C12orf43 RNA expression.
This table summarizes C12orf43 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 4. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for C12orf43. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. C12orf43 shows lower tumor expression in THCA and higher tumor expression in HNSC, KIRC, LIHC, KIRP and STAD. The HNSC box plot shows higher C12orf43 RNA expression in tumor versus normal tissue (log2 FC = +0.703, t-test p < 0.001).
This table shows molecular features associated with C12orf43 in patient tissues and cancer cell lines. In patient samples, C12orf43 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, C12orf43 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BLOOD_Lymphoma.
