intraflagellar transport 46Genealiases: C11orf2 · C11orf60 · CFAP32 · FAP32
Q-omics provides the consensus-scored IFT46 profile across patient tissues and cancer cell-line models. IFT46 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, IFT46 is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, IFT46 RNA expression shows 20,087 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, KICH, and ACC as cancer lineages where IFT46 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 IFT46 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IFT46 survival associations across molecular data types. IFT46 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (3) 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 IFT46 RNA expression–survival associations across cancer types. High IFT46 expression shows unfavorable associations in KICH and ACC, but favorable associations in KIRC, BRCA, UCEC and KIRP. 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 IFT46 RNA expression.
This table summarizes IFT46 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 LUAD for protein.
This table ranks reproducible tumor–normal expression differences for IFT46. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IFT46 shows lower tumor expression in KICH, THCA, KIRP and LUAD and higher tumor expression in CHOL and COAD. The KICH box plot shows higher IFT46 RNA expression in normal versus tumor tissue (log2 FC = −1.447, t-test p < 0.001).
This table shows molecular features associated with IFT46 in patient tissues and cancer cell lines. In patient samples, IFT46 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, IFT46 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and SOFT_TISSUE.
