Q-omics provides the consensus-scored CRISP2 profile across patient tissues and cancer cell-line models. CRISP2 expression is associated with patient survival in 16 of 34 cancer types, with the highest sampling consensus in STAD. Among the 18 cancer types available for tumor–normal comparison, CRISP2 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, CRISP2 RNA expression shows 6,098 significant pathway-activity associations, with the highest sampling consensus in HNSC. Together, these results highlight STAD, KIRC, and HNSC as cancer lineages where CRISP2 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 CRISP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CRISP2 survival associations across molecular data types. CRISP2 RNA expression shows survival associations in the most cancer types (16), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CRISP2 RNA expression–survival associations across cancer types. High CRISP2 expression shows unfavorable associations in STAD, UCEC, COAD and ACC, but favorable associations in CESC and MESO. The STAD 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 STAD as the clearest survival context for CRISP2 RNA expression.
This table summarizes CRISP2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for CRISP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CRISP2 shows lower tumor expression in KIRC, HNSC, KIRP, LUSC, KICH and UCEC. The KIRC box plot shows higher CRISP2 RNA expression in normal versus tumor tissue (log2 FC = −1.023, t-test p < 0.001).
This table shows molecular features associated with CRISP2 in patient tissues and cancer cell lines. In patient samples, CRISP2 shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, CRISP2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LUNG_SCLC.
