Q-omics provides the consensus-scored STARD9 profile across patient tissues and cancer cell-line models. STARD9 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, STARD9 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, STARD9 RNA expression shows 20,769 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight HNSC, KIRC, and UVM as cancer lineages where STARD9 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 STARD9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes STARD9 survival associations across molecular data types. STARD9 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible STARD9 RNA expression–survival associations across cancer types. High STARD9 expression shows unfavorable associations in BLCA, LUSC, LGG, KIRP and ACC, but favorable associations in HNSC. 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 STARD9 RNA expression.
This table summarizes STARD9 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 1. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for STARD9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. STARD9 shows lower tumor expression in BLCA, LUAD, LUSC and COAD and higher tumor expression in KIRC and HNSC. The KIRC box plot shows higher STARD9 RNA expression in tumor versus normal tissue (log2 FC = +0.739, t-test p < 0.001).
This table shows molecular features associated with STARD9 in patient tissues and cancer cell lines. In patient samples, STARD9 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, STARD9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Leukemia.
