Legumain affects the PI3K/AKT tumor progression pathway in retinoblastoma

Lysosome-targeting and legumain-triggered 68Ga-labeled probe for enhanced tumor PET imaging

Legumain is overexpressed in diverse tumors, serving as a significant tumor biomarker. Our study aimed to develop a new positron emission tomography (PET) probe [68Ga]Ga-NOTA-SF-AANM for imaging the expression level of legumain in vivo. The radio-labeling of [68Ga]Ga-NOTA-SF-AANM was accomplished within 15 min. The probe has good stability in vitro. NOTA-SF-AANM exhibited rapid response to recombinant human legumain enzyme, enabling intramolecular condensation cyclization. Cellular uptake and lysosomal co-localization experiments demonstrated that the probe was able to differentiate specifically between MDA-MB-468 and PC-3 cancer cells with varying degrees of legumain expression. PET imaging displayed a significant and persistent signal (3.59 ± 0.30 %ID/mL at 60 min) in MDA-MB-468 tumors, while PC-3 tumors exhibited lower radioactivity (1.08 ± 0.35 %ID/mL at 60 min), further validating the specific targeting of [68Ga]Ga-NOTA-SF-AANM towards legumain. [68Ga]Ga-NOTA-SF-AANM is a promising tool for precise diagnosis of legumain-related diseases due to its advantages in radio-labeling and accurate monitoring of legumain expression levels.

Establishment and validation of a novel lysosome-related gene signature for predicting prognosis and immune landscape in hepatocellular carcinoma

BACKGROUND

Recent studies have shown that lysosomes not only provide energy for tumor cell growth, but also participate in the occurrence and development of malignant tumors by regulating various ways of tumor cell death. However, the role of lysosome associated genes (LSAGs) in hepatocellular carcinoma (HCC) remains unclear.

METHODS

Transcriptome data and clinical data of HCC were downloaded from the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases. We identified differential expression of LSAGs by comparing tumor tissue with normal liver tissue. Subsequently, we used univariate COX analysis and least absolute shrinkage and selection operator (LASSO) COX regression to construct the prognostic feature of LSAGs. Kaplan-Meier survival curve and receiver operating characteristic curve were used to evaluate the predictive ability of LSAGs feature. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for functional enrichment analysis of risk differential genes. The relationship between LSAGs score and tumor microenvironment and chemotherapy drug sensitivity was analyzed. Finally, the cellular communication of tumor cells with high and low expression of model LSAGs was explored.

RESULTS

We identified sixteen prognostic associated LSAGs, four of which were selected to construct prognostic feature of LSAGs. Patients in the low LSAGs group had a better prognosis than those in the high LSAGs group. GO and KEGG analyses showed that risk differential genes were enriched in leukocyte migration, cytokine-cytokine receptor interaction and PI3K-Akt signaling pathway. The group with low LSAGs score had lower immune score. Patients in the high LSAGs group were more sensitive to drugs for chemotherapy. In addition, tumor cells with high expression of model LSAGs showed stronger association with immune cells through the interleukin-2 (IL2), fibroblast growth factor (FGF), adiponectin, and bone morphogenetic proteins (BMP) signaling pathways.

CONCLUSION

We established a LSAGs signature that had the ability to predict clinical prognosis and immune landscape, proposing potential therapeutic targets for HCC.