Q-omics provides the consensus-scored SAMD1 profile across patient tissues and cancer cell-line models. SAMD1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, SAMD1 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, SAMD1 protein abundance shows 25,321 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, HNSC, and LSCC as cancer lineages where SAMD1 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 SAMD1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SAMD1 survival associations across molecular data types. SAMD1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (2) 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 SAMD1 RNA expression–survival associations across cancer types. High SAMD1 expression shows unfavorable associations in ACC, KIRC, LIHC, MESO, KIRP and SARC. The ACC 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 ACC as the clearest survival context for SAMD1 RNA expression.
This table summarizes SAMD1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for SAMD1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SAMD1 shows higher tumor expression in HNSC, KIRP, BLCA, THCA, COAD and LIHC. The HNSC box plot shows higher SAMD1 RNA expression in tumor versus normal tissue (log2 FC = +1.265, t-test p < 0.001).
This table shows molecular features associated with SAMD1 in patient tissues and cancer cell lines. In patient samples, SAMD1 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, SAMD1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and LUNG_SCLC.
