Q-omics provides the consensus-scored IFT27 profile across patient tissues and cancer cell-line models. IFT27 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, IFT27 is differentially expressed in 10, with the highest sampling consensus in LIHC. Additionally, IFT27 protein abundance shows 33,832 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, LIHC, and GBM as cancer lineages where IFT27 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 IFT27 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IFT27 survival associations across molecular data types. IFT27 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (3) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IFT27 RNA expression–survival associations across cancer types. High IFT27 expression shows unfavorable associations in KIRC, ACC and KICH, but favorable associations in UCEC, BLCA and KIRP. The KIRC 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 KIRC as the clearest survival context for IFT27 RNA expression.
This table summarizes IFT27 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 11. The strongest signals are observed in LIHC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for IFT27. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IFT27 shows lower tumor expression in THCA and KICH and higher tumor expression in LIHC, CHOL, HNSC and BLCA. The LIHC box plot shows higher IFT27 RNA expression in tumor versus normal tissue (log2 FC = +1.190, t-test p < 0.001).
This table shows molecular features associated with IFT27 in patient tissues and cancer cell lines. In patient samples, IFT27 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, IFT27 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
