Q-omics provides the consensus-scored CCNL2P1 profile across patient tissues and cancer cell-line models. CCNL2P1 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, CCNL2P1 is differentially expressed in 7, with the highest sampling consensus in THCA. Additionally, CCNL2P1 RNA expression shows 21,541 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight SKCM, THCA, and LSCC as cancer lineages where CCNL2P1 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 CCNL2P1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CCNL2P1 survival associations across molecular data types. CCNL2P1 RNA expression shows survival associations in the most cancer types (21). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CCNL2P1 RNA expression–survival associations across cancer types. High CCNL2P1 expression shows unfavorable associations in OV, ACC and ESCA, but favorable associations in SKCM, LGG and UCS. The SKCM 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 SKCM as the clearest survival context for CCNL2P1 RNA expression.
This table summarizes CCNL2P1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7. The strongest signals are observed in BRCA for RNA.
This table ranks reproducible tumor–normal expression differences for CCNL2P1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CCNL2P1 shows lower tumor expression in THCA and LUSC and higher tumor expression in BRCA, STAD, PRAD and LIHC. The THCA box plot shows higher CCNL2P1 RNA expression in normal versus tumor tissue (log2 FC = −0.123, t-test p < 0.001).
This table shows molecular features associated with CCNL2P1 in patient tissues and cancer cell lines. In patient samples, CCNL2P1 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set.
