Q-omics provides the consensus-scored SLC4A9 profile across patient tissues and cancer cell-line models. SLC4A9 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, SLC4A9 is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, SLC4A9 RNA expression shows 16,936 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight LIHC, KIRC, and UVM as cancer lineages where SLC4A9 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 SLC4A9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SLC4A9 survival associations across molecular data types. SLC4A9 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SLC4A9 RNA expression–survival associations across cancer types. High SLC4A9 expression shows unfavorable associations in LIHC, UVM and COAD, but favorable associations in KICH, MESO and ACC. The LIHC 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 LIHC as the clearest survival context for SLC4A9 RNA expression.
This table summarizes SLC4A9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 2. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SLC4A9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SLC4A9 shows lower tumor expression in KIRC, KIRP, KICH, COAD and LUAD and higher tumor expression in LIHC. The KIRC box plot shows higher SLC4A9 RNA expression in normal versus tumor tissue (log2 FC = −3.768, t-test p < 0.001).
This table shows molecular features associated with SLC4A9 in patient tissues and cancer cell lines. In patient samples, SLC4A9 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, SLC4A9 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_Lymphoma and LARGE_INTESTINE.
