intraflagellar transport 52Genealiases: C20orf9 · CGI-53 · NGD2 · NGD5
Q-omics provides the consensus-scored IFT52 profile across patient tissues and cancer cell-line models. IFT52 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, IFT52 is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, IFT52 RNA expression shows 19,160 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and HNSC as cancer lineages where IFT52 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 IFT52 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IFT52 survival associations across molecular data types. IFT52 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IFT52 RNA expression–survival associations across cancer types. High IFT52 expression shows unfavorable associations in ACC, MESO, LIHC, KICH and LGG, but favorable associations in BRCA. 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 IFT52 RNA expression.
This table summarizes IFT52 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 5. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for IFT52. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IFT52 shows lower tumor expression in THCA and KICH and higher tumor expression in HNSC, LIHC, COAD and KIRP. The HNSC box plot shows higher IFT52 RNA expression in tumor versus normal tissue (log2 FC = +0.873, t-test p < 0.001).
This table shows molecular features associated with IFT52 in patient tissues and cancer cell lines. In patient samples, IFT52 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, IFT52 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 OESOPHAGUS and BLOOD_Leukemia.
