Q-omics provides the consensus-scored TESK2 profile across patient tissues and cancer cell-line models. TESK2 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, TESK2 is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, TESK2 RNA expression shows 19,503 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight HNSC, KICH, and ACC as cancer lineages where TESK2 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 TESK2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TESK2 survival associations across molecular data types. TESK2 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (5) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TESK2 RNA expression–survival associations across cancer types. High TESK2 expression shows unfavorable associations in KICH and UCEC, but favorable associations in HNSC, LUAD, KIRC and BRCA. The HNSC 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 HNSC as the clearest survival context for TESK2 RNA expression.
This table summarizes TESK2 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 3. The strongest signals are observed in KICH for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for TESK2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TESK2 shows lower tumor expression in KICH, COAD, LUAD, READ and KIRP and higher tumor expression in BLCA. The KICH box plot shows higher TESK2 RNA expression in normal versus tumor tissue (log2 FC = −1.449, t-test p < 0.001).
This table shows molecular features associated with TESK2 in patient tissues and cancer cell lines. In patient samples, TESK2 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, TESK2 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 SKIN and BLOOD_Leukemia.
