Q-omics provides the consensus-scored SLC4A1AP profile across patient tissues and cancer cell-line models. SLC4A1AP expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, SLC4A1AP is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, SLC4A1AP protein abundance shows 27,986 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight BLCA, HNSC, and LSCC as cancer lineages where SLC4A1AP 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 SLC4A1AP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SLC4A1AP survival associations across molecular data types. SLC4A1AP RNA expression shows survival associations in the most cancer types (20), followed by mutation status (4) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SLC4A1AP RNA expression–survival associations across cancer types. High SLC4A1AP expression shows unfavorable associations in BLCA, LIHC, ACC, MESO and HNSC, but favorable associations in KIRC. The BLCA 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 BLCA as the clearest survival context for SLC4A1AP RNA expression.
This table summarizes SLC4A1AP 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 6. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SLC4A1AP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SLC4A1AP shows lower tumor expression in KICH and higher tumor expression in HNSC, BLCA, LUAD, LIHC and STAD. The HNSC box plot shows higher SLC4A1AP RNA expression in tumor versus normal tissue (log2 FC = +0.842, t-test p < 0.001).
This table shows molecular features associated with SLC4A1AP in patient tissues and cancer cell lines. In patient samples, SLC4A1AP shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, SLC4A1AP 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 SKIN and UPPER_AERODIGESTIVE_TRACT.
