Q-omics provides the consensus-scored CSGALNACT2 profile across patient tissues and cancer cell-line models. CSGALNACT2 expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, CSGALNACT2 is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, CSGALNACT2 RNA expression shows 20,059 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRP, HNSC, and ACC as cancer lineages where CSGALNACT2 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 CSGALNACT2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CSGALNACT2 survival associations across molecular data types. CSGALNACT2 RNA expression shows survival associations in the most cancer types (29), followed by mutation status (6) 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 CSGALNACT2 RNA expression–survival associations across cancer types. High CSGALNACT2 expression shows unfavorable associations in KIRP, ACC, MESO, BLCA and SCLC, but favorable associations in KIRC. The KIRP Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KIRP as the clearest survival context for CSGALNACT2 RNA expression.
This table summarizes CSGALNACT2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 4. The strongest signals are observed in HNSC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for CSGALNACT2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CSGALNACT2 shows lower tumor expression in KICH and LUSC and higher tumor expression in HNSC, KIRC, COAD and LIHC. The HNSC box plot shows higher CSGALNACT2 RNA expression in tumor versus normal tissue (log2 FC = +2.176, t-test p < 0.001).
This table shows molecular features associated with CSGALNACT2 in patient tissues and cancer cell lines. In patient samples, CSGALNACT2 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, CSGALNACT2 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 PANCREAS and LARGE_INTESTINE.
