Q-omics provides the consensus-scored CSTA profile across patient tissues and cancer cell-line models. CSTA expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in LUSC. Among the 18 cancer types available for tumor–normal comparison, CSTA is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, CSTA protein abundance shows 31,484 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LUSC, KIRC, and GBM as cancer lineages where CSTA 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 CSTA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CSTA survival associations across molecular data types. CSTA RNA expression shows survival associations in the most cancer types (23), followed by mutation status (2) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CSTA RNA expression–survival associations across cancer types. High CSTA expression shows unfavorable associations in LGG, UVM and KIRC, but favorable associations in LUSC, HNSC and DLBC. The LUSC 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 LUSC as the clearest survival context for CSTA RNA expression.
This table summarizes CSTA 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 10. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CSTA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CSTA shows lower tumor expression in LUAD, BRCA and HNSC and higher tumor expression in KIRC, KIRP and LUSC. The KIRC box plot shows higher CSTA RNA expression in tumor versus normal tissue (log2 FC = +2.200, t-test p < 0.001).
This table shows molecular features associated with CSTA in patient tissues and cancer cell lines. In patient samples, CSTA 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, CSTA 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 PANCREAS and BLOOD_Leukemia.
