Q-omics provides the consensus-scored SLIT2 profile across patient tissues and cancer cell-line models. SLIT2 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, SLIT2 is differentially expressed in 15, with the highest sampling consensus in BLCA. Additionally, SLIT2 protein abundance shows 20,079 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight BLCA, and PDAC as cancer lineages where SLIT2 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 SLIT2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SLIT2 survival associations across molecular data types. SLIT2 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (12) 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 SLIT2 RNA expression–survival associations across cancer types. High SLIT2 expression shows unfavorable associations in BLCA, ACC, UVM and MESO, but favorable associations in UCS and ESCA. 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 SLIT2 RNA expression.
This table summarizes SLIT2 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 4. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SLIT2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SLIT2 shows lower tumor expression in BLCA, KIRC, COAD, LUAD, LUSC and UCEC. The BLCA box plot shows higher SLIT2 RNA expression in normal versus tumor tissue (log2 FC = −2.890, t-test p < 0.001).
This table shows molecular features associated with SLIT2 in patient tissues and cancer cell lines. In patient samples, SLIT2 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, SLIT2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in STOMACH and SKIN.
