Q-omics provides the consensus-scored SLPI profile across patient tissues and cancer cell-line models. SLPI expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SLPI is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, SLPI protein abundance shows 23,811 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight KIRC, and LUAD as cancer lineages where SLPI 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 SLPI — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SLPI survival associations across molecular data types. SLPI RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SLPI RNA expression–survival associations across cancer types. High SLPI expression shows unfavorable associations in KIRC, OV, KIRP and SKCM, but favorable associations in ACC and MESO. The KIRC 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 KIRC as the clearest survival context for SLPI RNA expression.
This table summarizes SLPI 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 8. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SLPI. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SLPI shows lower tumor expression in KIRC, HNSC, KICH, LUAD and LUSC and higher tumor expression in THCA. The KIRC box plot shows higher SLPI RNA expression in normal versus tumor tissue (log2 FC = −4.532, t-test p < 0.001).
This table shows molecular features associated with SLPI in patient tissues and cancer cell lines. In patient samples, SLPI shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, SLPI 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 BONE and OVARY.
