Q-omics provides the consensus-scored KSR2 profile across patient tissues and cancer cell-line models. KSR2 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, KSR2 is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, KSR2 protein abundance shows 18,755 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LUAD, KIRC, and GBM as cancer lineages where KSR2 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 KSR2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes KSR2 survival associations across molecular data types. KSR2 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (9) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible KSR2 RNA expression–survival associations across cancer types. High KSR2 expression shows unfavorable associations in THYM and LIHC, but favorable associations in LUAD, LGG, BRCA and PAAD. The LUAD Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify LUAD as the clearest survival context for KSR2 RNA expression.
This table summarizes KSR2 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 4. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for KSR2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. KSR2 shows lower tumor expression in KIRC, KICH, THCA and KIRP and higher tumor expression in HNSC and BLCA. The KIRC box plot shows higher KSR2 RNA expression in normal versus tumor tissue (log2 FC = −1.417, t-test p < 0.001).
This table shows molecular features associated with KSR2 in patient tissues and cancer cell lines. In patient samples, KSR2 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, KSR2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in CNS and LUNG_SCLC.
