KIF18A belongs to the Kinesin family, which participates in the occurrence and progression of tumors. However, few pan-cancer analyses have been performed on KIF18A to date. We used multiple public databases such as TIMER, The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Human Protein Atlas (HPA) to explore KIF18A mRNA expression in 33 tumors. We performed immunohistochemistry on liver cancer and pancreatic cancer tissue and corresponding normal tissues to examine the expression of KIF18A protein. Univariate Cox regression and Kaplan–Meier survival analysis were applied to detect the effect of KIF18A on overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) of patients with these tumors. Subsequently, we explored KIF18A gene alterations in different tumor tissues using cBioPortal. The relationship between KIF18A and clinical characteristics, tumor microenvironment (TME), immune regulatory genes, immune checkpoints, tumor mutational burden (TMB), microsatellite instability (MSI), mismatch repairs (MMRs), DNA methylation, RNA methylation, and drug sensitivity was applied for further study using the R language. Gene Set Enrichment Analysis (GSEA) was utilized to explore the molecular mechanism of KIF18A. Bioinformatic analysis and immunohistochemical experiments confirmed that KIF18A was up-regulated in 27 tumors and was correlated with the T stage, N stage, pathological stage, histological grade, and Ki-67 index in many cancers. The overexpression of KIF18A had poor OS, DSS, and PFI in adrenocortical carcinoma (ACC), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), brain lower-grade glioma (LGG), liver cancer (LIHC), lung adenocarcinoma (LUAD), and pancreatic cancer (PAAD). Univariate and multivariate regression analysis confirmed KIF18A as an independent prognostic factor for LIHC and PAAD. The mutation frequency of KIF18A is the highest in endometrial cancer. KIF18A expression levels were positively associated with immunocyte infiltration, immune regulatory genes, immune checkpoints, TMB, MSI, MMRs, DNA methylation, RNA methylation, and drug sensitivity in certain cancers. In addition, we discovered that KIF18A participated in the cell cycle at the single-cell level and GSEA analysis for most cancers. These findings suggested that KIF18A could be regarded as a latent prognostic marker and a new target for cancer immunological therapy.

Background RNA methylation is a crucial in many biological functions, and its aberrant regulation is associated with cancer progression. N6-Methyladenosine (m6A), 5-Methylcytosine (m5C), N1-methyladenosine (m1A) are common modifications of RNA methylation. However, the effect of methylation of m6A/m5C/m1A in hepatocellular carcinoma (HCC) remains unclear. Method The transcriptome datasets, clinic information, and mutational data of 48 m6A/m5C/m1A regulator genes were acquired from the TCGA database, and the prognostic hazard model was established by univariate and Least absolute shrinkage and selection operator (Lasso) regression. The multivariate regression was performed to determine whether the risk score was an independent prognostic indicator. Kaplan–Meier survival analysis and ROC curve analysis were used to evaluate the predictive ability of the risk model. Decision curve analysis（DCA）analysis was conducted to estimate the clinical utility of the risk model. We further analyzed the association between risk score and functional enrichment, tumor immune microenvironment, and somatic mutation. Result The four-gene (YTHDF1, YBX1, TRMT10C, TRMT61A) risk signature was constructed. The high-risk group had shorter overall survival (OS) than the low-risk group. Univariate and multivariate regression analysis indicated that risk score was an independent prognostic indicator. Risk scores in male group, T3 + T4 group and Stage III + IV group were higher in female group, T1 + T2 group and stage I + II group. The AUC values for 1-, 2-, and 3-year OS in the TCGA dataset were 0.764, 0.693, and 0.689, respectively. DCA analysis showed that the risk score had a higher clinical net benefit in 1- and 2-year OS than other clinical features.The risk score was positively related to some immune cell infiltration and most immune checkpoints. Conclusion We developed a novel m6A/m5C/m1A regulator genes' prognostic model, which could be applied as a latent prognostic tool for HCC and might guide the choice of immunotherapies.

Non-SMC condensin I complex subunit D2 (NCAPD2) is overexpressed in some malignant tumors. However, there are few studies on the function of NCAPD2 in pan-cancer. We used the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Human Protein Atlas (HPA), and UALCAN to analyze NCAPD2 expression and promoter methylation levels in 33 tumors and normal samples. We performed immunohistochemistry (IHC) on liver cancer and corresponding normal tissues to examine NCAPD2 protein expression in LIHC. Kaplan-Meier survival and univariate regression analyses were performed to explore the pan-cancer clinical significance of NCAPD2. Moreover, correlative analysis between NCAPD2 expression and clinical characteristics, immune cell infiltration, immune checkpoints, immune regulators, tumor mutation burden (TMB), microsatellite instability (MSI), ribonucleic acid (RNA) methylation regulators, and drug sensitivity was conducted using data from TCGA. We also investigated the effects of NCAPD2 expression on immunotherapy efficacy and prognosis. Gene set enrichment analysis (GSEA) was conducted using NCAPD2. Bioinformatic analysis showed that NCAPD2 was overexpressed in most tumors and correlated with the clinical characteristics of some cancers. IHC results demonstrated that NCAPD2 protein expression was higher in LIHC than in normal liver. NCAPD2 expression was linked with T stage, clinical stage, and histologic grade in LIHC. Overexpression of NCAPD2 resulted in poor overall survival, and disease-specific survival in adrenocortical carcinoma, kidney renal papillary cell carcinoma, brain lower grade glioma, liver hepatocellular carcinoma, lung adenocarcinoma, mesothelioma, pancreatic adenocarcinoma, sarcoma, skin cutaneous melanoma, and uterine corpus endometrial carcinoma. NCAPD2 was considered an independent biomarker by Cox regression in LIHC. The time ROC curve demonstrated that the survival rate of 1-, 3-, and 5-year OS and DSS in LIHC was above 0.6. The expression of NCAPD2 was significantly correlated with immune cell infiltration, immune checkpoints, TMB, MSI, and RNA methylation regulators in several tumors. NCAPD2 had a high predictive value for immunotherapy efficiency in certain tumors. In our study, drugs sensitive to NCAPD2 protein were screened by sensitivity analysis. GSEA analysis showed that NCAPD2 mainly participated in the G2M checkpoint, mitotic spindle, and KRAS-signaling. NCAPD2 may act as a prognostic molecular marker in most cancers.