Q-omics provides the consensus-scored OIT3 profile across patient tissues and cancer cell-line models. OIT3 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, OIT3 is differentially expressed in 13, with the highest sampling consensus in KIRP. Additionally, OIT3 protein abundance shows 16,121 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, KIRP, and GBM as cancer lineages where OIT3 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 OIT3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OIT3 survival associations across molecular data types. OIT3 RNA expression shows survival associations in the most cancer types (21), 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 OIT3 RNA expression–survival associations across cancer types. High OIT3 expression shows unfavorable associations in MESO, but favorable associations in KIRC, LUAD, OV, GBM and READ. 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 OIT3 RNA expression.
This table summarizes OIT3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 6. The strongest signals are observed in THCA for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for OIT3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. OIT3 shows lower tumor expression in KIRP, LIHC and LUSC and higher tumor expression in THCA, HNSC and KIRC. The KIRP box plot shows higher OIT3 RNA expression in normal versus tumor tissue (log2 FC = −1.664, t-test p < 0.001).
This table shows molecular features associated with OIT3 in patient tissues and cancer cell lines. In patient samples, OIT3 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, OIT3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and LIVER.
