Q-omics provides the consensus-scored CRLF1 profile across patient tissues and cancer cell-line models. CRLF1 expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, CRLF1 is differentially expressed in 9, with the highest sampling consensus in LIHC. Additionally, CRLF1 RNA expression shows 15,425 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRP, LIHC, and THYM as cancer lineages where CRLF1 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 CRLF1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CRLF1 survival associations across molecular data types. CRLF1 RNA expression shows survival associations in the most cancer types (18), followed by mutation status (2) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CRLF1 RNA expression–survival associations across cancer types. High CRLF1 expression shows unfavorable associations in KIRP, ACC and OV, but favorable associations in ESCA, LGG and HNSC. The KIRP 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 KIRP as the clearest survival context for CRLF1 RNA expression.
This table summarizes CRLF1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 7. The strongest signals are observed in LIHC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for CRLF1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CRLF1 shows lower tumor expression in KIRC and higher tumor expression in LIHC, THCA, LUAD, CHOL and KICH. The LIHC box plot shows higher CRLF1 RNA expression in tumor versus normal tissue (log2 FC = +0.914, t-test p < 0.001).
This table shows molecular features associated with CRLF1 in patient tissues and cancer cell lines. In patient samples, CRLF1 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, CRLF1 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 BLOOD_Leukemia and LARGE_INTESTINE.
