Q-omics provides the consensus-scored WASHC1 profile across patient tissues and cancer cell-line models. WASHC1 expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, WASHC1 is differentially expressed in 10, with the highest sampling consensus in LIHC. Additionally, WASHC1 protein abundance shows 23,613 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, LIHC, and PDAC as cancer lineages where WASHC1 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 WASHC1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes WASHC1 survival associations across molecular data types. WASHC1 RNA expression shows survival associations in the most cancer types (18), followed by 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 WASHC1 RNA expression–survival associations across cancer types. High WASHC1 expression shows unfavorable associations in KIRC, ACC, LIHC, ESCA, COAD and PRAD. The KIRC 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 KIRC as the clearest survival context for WASHC1 RNA expression.
This table summarizes WASHC1 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 5. The strongest signals are observed in LIHC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for WASHC1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. WASHC1 shows lower tumor expression in UCEC and higher tumor expression in LIHC, HNSC, STAD, CHOL and KIRP. The LIHC box plot shows higher WASHC1 RNA expression in tumor versus normal tissue (log2 FC = +1.177, t-test p < 0.001).
This table shows molecular features associated with WASHC1 in patient tissues and cancer cell lines. In patient samples, WASHC1 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, WASHC1 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 SOFT_TISSUE and UPPER_AERODIGESTIVE_TRACT.
