Q-omics provides the consensus-scored CSF1 profile across patient tissues and cancer cell-line models. CSF1 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, CSF1 is differentially expressed in 16, with the highest sampling consensus in KIRC. Additionally, CSF1 RNA expression shows 17,067 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight SKCM, KIRC, and UVM as cancer lineages where CSF1 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 CSF1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CSF1 survival associations across molecular data types. CSF1 RNA expression shows survival associations in the most cancer types (19), 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 CSF1 RNA expression–survival associations across cancer types. High CSF1 expression shows unfavorable associations in KIRC, LIHC and LAML, but favorable associations in SKCM, HNSC and ACC. The SKCM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify SKCM as the clearest survival context for CSF1 RNA expression.
This table summarizes CSF1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for CSF1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CSF1 shows lower tumor expression in COAD, LUSC, BLCA, BRCA and KICH and higher tumor expression in KIRC. The KIRC box plot shows higher CSF1 RNA expression in tumor versus normal tissue (log2 FC = +1.312, t-test p < 0.001).
This table shows molecular features associated with CSF1 in patient tissues and cancer cell lines. In patient samples, CSF1 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, CSF1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BONE.
