Q-omics provides the consensus-scored TEX30 profile across patient tissues and cancer cell-line models. TEX30 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, TEX30 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, TEX30 RNA expression shows 19,792 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KICH, KIRC, and ACC as cancer lineages where TEX30 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 TEX30 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TEX30 survival associations across molecular data types. TEX30 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (2) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TEX30 RNA expression–survival associations across cancer types. High TEX30 expression shows unfavorable associations in KICH, ACC, MESO, UVM and LUAD, but favorable associations in KIRC. The KICH 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 KICH as the clearest survival context for TEX30 RNA expression.
This table summarizes TEX30 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 4. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for TEX30. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TEX30 shows lower tumor expression in KICH and higher tumor expression in KIRC, HNSC, BLCA, COAD and STAD. The KIRC box plot shows higher TEX30 RNA expression in tumor versus normal tissue (log2 FC = +0.478, t-test p < 0.001).
This table shows molecular features associated with TEX30 in patient tissues and cancer cell lines. In patient samples, TEX30 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, TEX30 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and UPPER_AERODIGESTIVE_TRACT.
