Background. EF-hand domain-containing protein D2 (EFHD2) has recently been reported to participate in initiation of cancer. More evidence indicates that EFHD2 plays an important role in tumors, but the pan-cancer analysis of EFHD2 is still very limited. Methods. In this study, we downloaded the original mRNA expression data and SNP data of 33 kinds of tumor data. The gene expression data of different tissues were downloaded from the GTEX database, combined with TCGA data and corrected to calculate the difference of gene expression. The data of total survival time (OS) and progression-free survival (PFS) of TCGA patients were downloaded from the Xena database to further survey the relationship between the EFHD2 expression and prognosis. The CIBERSORT algorithm was used to analyze the RNA-seq data of 33 kinds of cancer patients in different subgroups. In this study, NCI-60 drug sensitivity data and RNA-seq data were downloaded to explore the relationship between genes and common antineoplastic drug sensitivity through correlation analysis. In this study, GSEA analysis was carried out from the Molecular Signature database through the packages of “clusterprofiler” and “enrichplot.” By comparing the differences of signal pathways between high and low gene expression groups, the possible molecular mechanism of prognostic differences among 33 kinds of tumors was determined. Results. Our results indicated that EFHD2 was highly expressed in 23 kinds of tumors. In addition, EFHD2 was associated with stage in many kinds of tumors. The expression of EFHD2 was closely related to the OS of 12 kinds of cancer patients. In addition, Kaplan-Meier- (KM-) plot survival analysis indicated that the high expression of EFHD2 was related to the poor OS of 5 kinds of cancer, and the expression of EFHD2 was closely related to the PFI of 5 kinds of cancer patients. The expression of EFHD2 was closely related to immune infiltration, among which 18 cancers were significantly correlated with CD8T cells, 14 cancers were significantly correlated with T regulatory (Tregs) cells, 15 cancers were significantly correlated with CD4 memory activated Tcells, and EFHD2 was significantly correlated with common tumor-related regulatory genes such as TGF beta signaling, TNFA signaling, hypoxia, scorch death, DNA repair, autophagy, and iron death-related genes. The expression level of EFHD2 was significantly correlated with each tumor of TMB, including STAD, SARC, ACC, THYM, KICH, THCA, and TGCT. In MSI, there were significant differences in THYM, STAD, THCA, and TGCT. We used the CellMiner database to explore the sensitivity between EFHD2 gene and common antineoplastic drugs and found that the prediction of high expression of EFHD2 was related to the resistance of many antineoplastic drugs. In renal cell carcinoma, the high expression of EFHD2 is mainly concentrated in ALLOGRAFT_REJECTION, REACTIVE_OXYGEN_SPECIES_PATHWAY, INTERFERON_GAMMA_RESPONSE, IL6_JAK_STAT3_SIGNALING, INTERFERON_ALPHA_RESPONSE, and other signal pathways. GO results showed that the genes were mainly enriched in response to interferon-gamma, antigen processing and presentation, cellular response to interferon-gamma, and other pathways. KEGG results demonstrated that EFHD2 was mainly rich in phagosome, Epstein-Barr virus infection, Staphylococcus aureus infection, and other pathways. The results of Kaplan-Meier survival analysis demonstrated that the high expression of EFHD2 was significantly related to the poor prognosis. Conclusion. Our findings highlight the predictive value of EFHD2 in cancer and provide a potential research direction for elucidating the role of EFHD2 in tumorigenesis and drug resistance.