Q-omics provides the consensus-scored TEX9 profile across patient tissues and cancer cell-line models. TEX9 expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, TEX9 is differentially expressed in 8, with the highest sampling consensus in KICH. Additionally, TEX9 RNA expression shows 20,378 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight KIRC, KICH, and KIRP as cancer lineages where TEX9 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 TEX9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TEX9 survival associations across molecular data types. TEX9 RNA expression shows survival associations in the most cancer types (18), followed by mutation status (6) 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 TEX9 RNA expression–survival associations across cancer types. High TEX9 expression shows unfavorable associations in KICH, SCLC and LIHC, but favorable associations in KIRC, OV and KIRP. The KIRC 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 KIRC as the clearest survival context for TEX9 RNA expression.
This table summarizes TEX9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 1. The strongest signals are observed in KICH for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for TEX9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TEX9 shows lower tumor expression in KICH and LUSC and higher tumor expression in LIHC, CHOL, BLCA and BRCA. The KICH box plot shows higher TEX9 RNA expression in normal versus tumor tissue (log2 FC = −1.847, t-test p < 0.001).
This table shows molecular features associated with TEX9 in patient tissues and cancer cell lines. In patient samples, TEX9 shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, TEX9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BLOOD_Leukemia.
