Q-omics provides the consensus-scored CRIP3 profile across patient tissues and cancer cell-line models. CRIP3 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, CRIP3 is differentially expressed in 7, with the highest sampling consensus in LIHC. Additionally, CRIP3 RNA expression shows 16,691 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ACC, LIHC, and UVM as cancer lineages where CRIP3 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 CRIP3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CRIP3 survival associations across molecular data types. CRIP3 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CRIP3 RNA expression–survival associations across cancer types. High CRIP3 expression shows unfavorable associations in UCEC, UVM and LAML, but favorable associations in ACC, SKCM and KIRP. The ACC 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 ACC as the clearest survival context for CRIP3 RNA expression.
This table summarizes CRIP3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for CRIP3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CRIP3 shows lower tumor expression in BRCA, PRAD and THCA and higher tumor expression in LIHC, KIRC and UCEC. The LIHC box plot shows higher CRIP3 RNA expression in tumor versus normal tissue (log2 FC = +2.171, t-test p < 0.001).
This table shows molecular features associated with CRIP3 in patient tissues and cancer cell lines. In patient samples, CRIP3 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, CRIP3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
