Q-omics provides the consensus-scored SLF2 profile across patient tissues and cancer cell-line models. SLF2 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, SLF2 is differentially expressed in 10, with the highest sampling consensus in KIRP. Additionally, SLF2 RNA expression shows 22,011 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and KIRP as cancer lineages where SLF2 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 SLF2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SLF2 survival associations across molecular data types. SLF2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (8) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SLF2 RNA expression–survival associations across cancer types. High SLF2 expression shows unfavorable associations in ACC and LIHC, but favorable associations in KIRC, SCLC, UCS and THYM. The ACC 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 ACC as the clearest survival context for SLF2 RNA expression.
This table summarizes SLF2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, 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 SLF2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SLF2 shows lower tumor expression in KICH and higher tumor expression in KIRP, KIRC, HNSC, LIHC and STAD. The KIRP box plot shows higher SLF2 RNA expression in tumor versus normal tissue (log2 FC = +0.830, t-test p < 0.001).
This table shows molecular features associated with SLF2 in patient tissues and cancer cell lines. In patient samples, SLF2 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, SLF2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Leukemia.
