Construction of diagnostic models for the progression of hepatocellular carcinoma using machine learning.

Liver cancer is one of the most prevalent forms of cancer worldwide. A significant proportion of patients with hepatocellular carcinoma (HCC) are diagnosed at advanced stages, leading to unfavorable treatment outcomes. Generally, the development of HCC occurs in distinct stages. However, the diagnostic and intervention markers for each stage remain unclear. Therefore, there is an urgent need to explore precise grading methods for HCC. Machine learning has emerged as an effective technique for studying precise tumor diagnosis. In this research, we employed random forest and LightGBM machine learning algorithms for the first time to construct diagnostic models for HCC at various stages of progression. We categorized 118 samples from GSE114564 into three groups: normal liver, precancerous lesion (including chronic hepatitis, liver cirrhosis, dysplastic nodule), and HCC (including early stage HCC and advanced HCC). The LightGBM model exhibited outstanding performance (accuracy = 0.96, precision = 0.96, recall = 0.96, F1-score = 0.95). Similarly, the random forest model also demonstrated good performance (accuracy = 0.83, precision = 0.83, recall = 0.83, F1-score = 0.83). When the progression of HCC was categorized into the most refined six stages: normal liver, chronic hepatitis, liver cirrhosis, dysplastic nodule, early stage HCC, and advanced HCC, the diagnostic model still exhibited high efficacy. Among them, the LightGBM model exhibited good performance (accuracy = 0.71, precision = 0.71, recall = 0.71, F1-score = 0.72). Also, performance of the LightGBM model was superior to that of the random forest model. Overall, we have constructed a diagnostic model for the progression of HCC and identified potential diagnostic characteristic gene for the progression of HCC.

Double-Layered Hollow Mesoporous Cuprous Oxide Nanoparticles for Double Drug Sequential Therapy of Tumors.

Cancer stem cells (CSCs) are one of the determinants of tumor heterogeneity and are characterized by self-renewal, high tumorigenicity, invasiveness, and resistance to various therapies. To overcome the resistance of traditional tumor therapies resulting from CSCs, a strategy of double drug sequential therapy (DDST) for CSC-enriched tumors is proposed in this study and is realized utilizing the developed double-layered hollow mesoporous cuprous oxide nanoparticles (DL-HMCONs). The high drug-loading contents of camptothecin (CPT) and all-trans retinoic acid (ATRA) demonstrate that the DL-HMCON can be used as a generic drug delivery system. ATRA and CPT can be sequentially loaded in and released from CPT3@ATRA3@DL-HMCON@HA. The DDST mechanisms of CPT3@ATRA3@DL-HMCON@HA for CSC-containing tumors are demonstrated as follows: 1) the first release of ATRA from the outer layer induces differentiation from CSCs with high drug resistance to non-CSCs with low drug resistance; 2) the second release of CPT from the inner layer causes apoptosis of non-CSCs; and 3) the third release of Cu+ from DL-HMCON itself triggers the Fenton-like reaction and glutathione depletion, resulting in ferroptosis of non-CSCs. This CPT3@ATRA3@DL-HMCON@HA is verified to possess high DDST efficacy for CSC-enriched tumors with high biosafety.

MRI-Guided Tumor Therapy Based on Synergy of Ferroptosis, Immunosuppression Reversal and Disulfidptosis.

Triple negative breast cancer (TNBC) cells have a high demand for oxygen and glucose to fuel their growth and spread, shaping the tumor microenvironment (TME) that can lead to a weakened immune system by hypoxia and increased risk of metastasis. To disrupt this vicious circle and improve cancer therapeutic efficacy, a strategy is proposed with the synergy of ferroptosis, immunosuppression reversal and disulfidptosis. An intelligent nanomedicine GOx-IA@HMON@IO is successfully developed to realize this strategy. The Fe release behaviors indicate the glutathione (GSH)-responsive degradation of HMON. The results of titanium sulfate assay, electron spin resonance (ESR) spectra, 5,5'-Dithiobis-(2-nitrobenzoic acid (DTNB) assay and T1 -weighted magnetic resonance imaging (MRI) demonstrate the mechanism of the intelligent iron atom (IA)-based cascade reactions for GOx-IA@HMON@IO, generating robust reactive oxygen species (ROS). The results on cells and mice reinforce the synergistic mechanisms of ferroptosis, immunosuppression reversal and disulfidptosis triggered by the GOx-IA@HMON@IO with the following steps: 1) GSH peroxidase 4 (GPX4) depletion by disulfidptosis; 2) IA-based cascade reactions; 3) tumor hypoxia reversal; 4) immunosuppression reversal; 5) GPX4 depletion by immunotherapy. Based on the synergistic mechanisms of ferroptosis, immunosuppression reversal and disulfidptosis, the intelligent nanomedicine GOx-IA@HMON@IO can be used for MRI-guided tumor therapy with excellent biocompatibility and safety.

A STING pathway-activatable contrast agent for MRI-guided tumor immunoferroptosis synergistic therapy.

The immunotherapy efficiency of stimulator of interferon genes (STING)-activatable drugs (e.g., 7-ethyl-10-hydroxycamptothecin, SN38) is limited by their non-specificity to tumor cells and the slow excretion of the DNA-containing exosomes from the treated cancer cells. The efficacy of tumor ferroptosis therapy is always limited by the elimination of lipid peroxides (LPO) by the pathways of glutathione peroxidase 4 (GPX4), dihydroorotate dehydrogenase (DHODH) and ferroptosis suppressor protein 1(FSP1). To solve these problems, in this study, we developed a STING pathway-activatable contrast agent (i.e., FeGd-HN@TA-Fe2+-SN38 nanoparticles) for magnetic resonance imaging (MRI)-guided tumor immunoferroptosis synergistic therapy. The remarkable in vivo MRI performance of FeGd-HN@TA-Fe2+-SN38 is attributed to its high accumulation at tumor location, the high relaxivities of FeGd-HN core, and the pH-sensitive TA-Fe2+-SN38 layer. The effectiveness and biosafety of the immunoferroptosis synergistic therapy induced by FeGd-HN@TA-Fe2+-SN38 are demonstrated by the in vivo investigations on the 4T1 tumor-bearing mice. The mechanisms of in vivo immunoferroptosis synergistic therapy by FeGd-HN@TA-Fe2+-SN38 are demonstrated by measurements of in vivo ROS, LPO, GPX4 and SLC7A11 levels, the intratumor matured DCs and CD8+ T cells, the protein expresion of STING and IRF-3, and the secretion of IFN-ß and IFN-γ.