Q-omics provides the consensus-scored SRBD1 profile across patient tissues and cancer cell-line models. SRBD1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SRBD1 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, SRBD1 RNA expression shows 21,329 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, HNSC, and ACC as cancer lineages where SRBD1 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 SRBD1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SRBD1 survival associations across molecular data types. SRBD1 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (5) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SRBD1 RNA expression–survival associations across cancer types. High SRBD1 expression shows unfavorable associations in ACC, MESO and HNSC, but favorable associations in KIRC, ESCA and GBM. The KIRC 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 KIRC as the clearest survival context for SRBD1 RNA expression.
This table summarizes SRBD1 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 4. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for SRBD1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SRBD1 shows lower tumor expression in THCA and KICH and higher tumor expression in HNSC, LIHC, STAD and BLCA. The HNSC box plot shows higher SRBD1 RNA expression in tumor versus normal tissue (log2 FC = +0.636, t-test p < 0.001).
This table shows molecular features associated with SRBD1 in patient tissues and cancer cell lines. In patient samples, SRBD1 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, SRBD1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and SOFT_TISSUE.
