doublecortinGenealiases: DBCN · DC · LISX · SCLH · XLIS
Q-omics provides the consensus-scored DCX profile across patient tissues and cancer cell-line models. DCX expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, DCX is differentially expressed in 10, with the highest sampling consensus in THCA. Additionally, DCX protein abundance shows 15,975 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LUAD, THCA, and GBM as cancer lineages where DCX 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 DCX — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DCX survival associations across molecular data types. DCX RNA expression shows survival associations in the most cancer types (25), followed by mutation status (8) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DCX RNA expression–survival associations across cancer types. High DCX expression shows unfavorable associations in LUAD, ACC and UVM, but favorable associations in ESCA, LGG and PAAD. The LUAD 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 LUAD as the clearest survival context for DCX RNA expression.
This table summarizes DCX 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 1. The strongest signals are observed in THCA for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for DCX. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DCX shows lower tumor expression in THCA, COAD, BRCA and HNSC and higher tumor expression in LIHC and KIRC. The THCA box plot shows higher DCX RNA expression in normal versus tumor tissue (log2 FC = −0.037, t-test p < 0.001).
This table shows molecular features associated with DCX in patient tissues and cancer cell lines. In patient samples, DCX shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, DCX 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 SKIN and SOFT_TISSUE.
