Q-omics provides the consensus-scored SREBF1 profile across patient tissues and cancer cell-line models. SREBF1 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, SREBF1 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, SREBF1 RNA expression shows 15,914 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight MESO, KIRC, and UVM as cancer lineages where SREBF1 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 SREBF1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SREBF1 survival associations across molecular data types. SREBF1 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (8) 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 SREBF1 RNA expression–survival associations across cancer types. High SREBF1 expression shows unfavorable associations in MESO, BLCA and UVM, but favorable associations in SCLC, UCEC and BRCA. The MESO Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .004). Together, the overview and detailed table identify MESO as the clearest survival context for SREBF1 RNA expression.
This table summarizes SREBF1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SREBF1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SREBF1 shows higher tumor expression in KIRC, THCA, STAD, KICH, COAD and BLCA. The KIRC box plot shows higher SREBF1 RNA expression in tumor versus normal tissue (log2 FC = +1.232, t-test p < 0.001).
This table shows molecular features associated with SREBF1 in patient tissues and cancer cell lines. In patient samples, SREBF1 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, SREBF1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in CNS and LARGE_INTESTINE.
