Q-omics provides the consensus-scored SAAL1 profile across patient tissues and cancer cell-line models. SAAL1 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, SAAL1 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, SAAL1 protein abundance shows 27,134 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KICH, HNSC, and LSCC as cancer lineages where SAAL1 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 SAAL1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SAAL1 survival associations across molecular data types. SAAL1 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (3) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SAAL1 RNA expression–survival associations across cancer types. High SAAL1 expression shows unfavorable associations in KICH, ACC, LIHC, MESO and LUAD, but favorable associations in READ. The KICH 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 KICH as the clearest survival context for SAAL1 RNA expression.
This table summarizes SAAL1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SAAL1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SAAL1 shows higher tumor expression in HNSC, KIRC, LIHC, LUSC, STAD and LUAD. The HNSC box plot shows higher SAAL1 RNA expression in tumor versus normal tissue (log2 FC = +1.134, t-test p < 0.001).
This table shows molecular features associated with SAAL1 in patient tissues and cancer cell lines. In patient samples, SAAL1 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, SAAL1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and BLOOD_Leukemia.
