Q-omics provides the consensus-scored CINP profile across patient tissues and cancer cell-line models. CINP expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, CINP is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, CINP RNA expression shows 18,797 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight HNSC, and ACC as cancer lineages where CINP 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 CINP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CINP survival associations across molecular data types. CINP RNA expression shows survival associations in the most cancer types (28), followed by mutation status (5) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CINP RNA expression–survival associations across cancer types. High CINP expression shows unfavorable associations in HNSC, UVM, ACC, UCS, STAD and KICH. The HNSC 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 HNSC as the clearest survival context for CINP RNA expression.
This table summarizes CINP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for CINP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CINP shows lower tumor expression in THCA and higher tumor expression in HNSC, LIHC, COAD, UCEC and BLCA. The HNSC box plot shows higher CINP RNA expression in tumor versus normal tissue (log2 FC = +0.603, t-test p < 0.001).
This table shows molecular features associated with CINP in patient tissues and cancer cell lines. In patient samples, CINP 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, CINP 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 BREAST and UPPER_AERODIGESTIVE_TRACT.
