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Simple Summary: Recognized as a promising target for anti-cancer treatment, PGF has the potential to overcome resistance to existing angiogenesis inhibitors. In this study, we aimed to identify target indications for PGF across various cancer types using bioinformatics analysis. We analyzed PGF gene function, molecular pathways, protein interactions, gene expression, mutations, survival prognosis, and tumor immune infiltration associated with PGF. The identified target diseases for PGF inhibitors included adrenocortical carcinoma, kidney cancers, liver hepatocellular carcinoma, stomach adenocarcinoma, and uveal melanoma. These findings highlight the potential of targeting PGF as a therapeutic strategy in these specific cancer types. The expression of the placental growth factor (PGF) in cancer cells and the tumor microenvironment can contribute to the induction of angiogenesis, supporting cancer cell metabolism by ensuring an adequate blood supply. Angiogenesis is a key component of cancer metabolism as it facilitates the delivery of nutrients and oxygen to rapidly growing tumor cells. PGF is recognized as a novel target for anti-cancer treatment due to its ability to overcome resistance to existing angiogenesis inhibitors and its impact on the tumor microenvironment. We aimed to integrate bioinformatics evidence using various data sources and analytic tools for target-indication identification of the PGF target and prioritize the indication across various cancer types as an initial step of drug development. The data analysis included PGF gene function, molecular pathway, protein interaction, gene expression and mutation across cancer type, survival prognosis and tumor immune infiltration association with PGF. The overall evaluation was conducted given the totality of evidence, to target the PGF gene to treat the cancer where the PGF level was highly expressed in a certain tumor type with poor survival prognosis as well as possibly associated with poor tumor infiltration level. PGF showed a significant impact on overall survival in several cancers through univariate or multivariate survival analysis. The cancers considered as target diseases for PGF inhibitors, due to their potential effects on PGF, are adrenocortical carcinoma, kidney cancers, liver hepatocellular carcinoma, stomach adenocarcinoma, and uveal melanoma. [ABSTRACT FROM AUTHOR]

Aim: To evaluate the anticancer efficacy of CKD-516, a novel vascular-disrupting agent, alone and in combination with doxorubicin in the treatment of hepatocellular carcinoma (HCC)., Materials and Methods: In mice bearing luciferized HCC cells, therapeutic efficacy was assessed for seven days after single administration of CKD-516, doxorubicin, or combination of CKD-516 and doxorubicin., Results: Bioluminescence-imaging (BLI) signals in the CKD-516 group abruptly decreased initially, but recovered at seven days after treatment. BLI signals in the doxorubicin group gradually decreased over the 7-day period. In the combination group, BLI signals were abruptly reduced and remained suppressed for the 7-day period. On histopathological examination, CKD-516-treated tumors showed extensive central necrosis, whereas the peripheral layers remained viable. Doxorubicin-treated tumors showed mild and scattered necrosis. Tumors from the combination group showed more extensive central and peripheral necrosis, with smaller viable peripheral layers than the CKD-516 group., Conclusion: Combination therapy can have additive effects for treatment of HCC compared with CKD-516 or doxorubicin monotherapy.