In this study, we developed a new prognostic model for glioblastoma (GBM) based on an integrated machine learning algorithm. We used univariate Cox regression analysis to identify prognostic genes by combining six GBM cohorts. Based on the prognostic genes, 10 machine learning algorithms were integrated into 117 algorithm combinations, and the artificial intelligence prognostic signature (AIPS) with the greatest average C-index was chosen. The AIPS was compared with 10 previously published models by univariate Cox analysis and the C-index. We compared the differences in prognosis, tumor immune microenvironment (TIME), and immunotherapy sensitivity between the high and low AIPS score groups. The AIPS based on the random survival forest algorithm with the highest average C-index (0.868) was selected. Compared with the previous 10 prognostic models, our AIPS has the highest C-index. The AIPS was closely linked to the clinical features of GBM. We discovered that patients in the low score group had improved prognoses, a more active TIME, and were more sensitive to immunotherapy. Finally, we verified the expression of several key genes by western blotting and immunohistochemistry. We identified an ideal prognostic signature for GBM, which might provide new insights into stratified treatment approaches for GBM patients.

Cancer is a global health issue that requires ongoing therapeutic advances. This review provides an overview of recent treatment strategies focusing on novel pathways in cancer therapy. Emerging research has unveiled promising targets that go beyond traditional modalities, offering new avenues for precision medicine and improved patient outcomes. One key area of innovation lies in targeted therapies directed at specific molecular pathways implicated in cancer progression. The identification of novel biomarkers has paved the way for the development of precision medicines tailored to individual patient profiles. Immunotherapy has also revolutionised cancer treatment by using the immune system to identify and remove cancer cells. Moreover, advancements in epigenetic therapies and RNA-based interventions demonstrate unprecedented potential in modulating gene expression and disrupting cancer-specific signalling pathways. We have discussed the pathophysiology of cancer, different immune checkpoint inhibitors, and targeted therapies in signalling therapies. The epigenetic modulators, such as Histone deacetylase (HDACs) inhibitors and DNA methyltransferase (DNMT) inhibitors, were studied. Recent breakthroughs in cancer immunotherapy treatment (CAR-T) cell therapy showcase the potential to enhance the immune response against various cancers; thus, related information was incorporated. Further, RNA-based therapies like RNA interference and mRNA-based vaccines and therapies, combination therapies, and novel therapies were discussed in the present article.

UNASSIGNED: Treatment of malignancies with chemotherapy and surgery is often associated with disease recurrence and metastasis. Immunotherapy improves cancer treatment by creating an active response against tumor antigens. Various cancer cells express a large amount of glucose-regulated protein 78 (GRP78) protein on their surface. Stimulating the immune system against this antigen can expose cancer cells to the immune system. Herein, we investigated the effectiveness of a cGRP78-based vaccine against different cancer cells.
UNASSIGNED: BALB/c mice were immunized with the cGRP78. The humoral immune response against different cancer cells was assessed by Cell-ELISA. The cellular immunity response was determined by splenocyte proliferation assay with different cancer antigens. The effect of vaccination on metastasis was investigated in vaccinated mice by injecting melanoma cancer cells into the tail of mice.
UNASSIGNED: These results indicated that the cGRP78 has acceptable antigenicity and stimulates the immune system to produce antibodies. After three injections, the amount of produced antibody was significantly different from the control group. Compared to the other three cell types, Hela and HepG2 showed the highest reaction to the serum of vaccinated mice. Cellular immunity against the B16F10 cell line had the best results compared to other cells. The metastasis results showed that after 30 days, the growth of B16F10 melanoma cancer cells was not noticeable in the lung tissue of vaccinated mice.
UNASSIGNED: Considering the resistance of vaccinated mice to metastasis, this vaccine offers a promising prospect for cancer treatment by inhibiting the spread of cancer cells.

Background: Hepatocellular carcinoma (HCC) is the main type of primary liver cancer, and its related death ranks third worldwide. The curative methods and progress prediction markers of HCC are not sufficient enough. Nevertheless, little progress has been made in the signature of m1A-, m5C-, m6A-, m7G-, and DNA methylation of HCC. Results: We calibrated a risk gene signature model that can be used to categorize HCC patients based on univariate, multivariate, and LASSO Cox regression analysis. This gene signature classified the patients into high- and low-risk subgroups. Patients in the high-risk group showed significantly reduced overall survival (OS) compared with patients in the low-risk group. The gene set variation analysis (GSVA), immune infiltration, and immunotherapy response were analyzed. The results demonstrated that an immunosuppressive environment was exited and the high-risk group had higher sensitivity to 5-fluorouracil, cisplatin, sorafenib, tamoxifen, and epirubicin. These results indicated personalized therapy should be taken into consideration. Conclusions: Our findings enriched our understanding of the molecular heterogeneity, tumor microenvironment (TME), and drug susceptibility of HCC. m1A-, m5C-, m6A-, m7G-, and DNA methylation-related regulators may be promising biomarkers for future research.

Theranostics, a method that combines targeted therapy and diagnostic imaging, has emerged as a viable route for enhancing cancer treatment, and hybrid nanoparticles (HNPs) are at the forefront of this field. Metallic, polymeric, lipid-based, and silica- based HNPs are studied for targeting and biocompatibility. Using HNPs, chemotherapeutic drugs, small interfering RNA, and therapeutic genes can be given precisely and controlled. This enhances therapeutic efficacy and reduces adverse effects. With fluorescence dyes, MRI contrast agents, and PET tracers, real-time therapy response monitoring is conceivable. A nano platform with therapeutic and diagnostic capabilities holds great promise for personalized medicine and precision oncology. The present study discusses HNPs\' biocompatibility, stability, immunogenicity, and long-term biosafety, which are crucial to the clinical translation of cancer theranostics. Further, in this in- -depth investigation, we investigated the design, synthesis, and multifunctional activities of HNPs for use in cancer theranostics.

BACKGROUND: Hepatocellular carcinoma (HCC) has high morbidity and mortality worldwide. Excision repair cross-complement 3 (ERCC3), a key functional gene in the nucleotide excision repair (NER) pathway, is commonly mutated or overexpressed in cancers and is thought to be a key gene contributing to the development of HCC. The characteristics of immune cell infiltration in the global tumor microenvironment (TME) mediated by ERCC3 and its related key genes in HCC are still unclear. The aim of this study was to integrate the role of ERCC3-related key genes in assessing the TME cell infiltration characteristics, immunotherapy efficacy, and prognosis of HCC patients. This study provides a theoretical basis for the study of immunological mechanisms and prognosis prediction in HCC.
METHODS: The HCC cohort from the TCGA database included 50 normal samples and 374 tumor samples to compare the differences in ERCC3-related gene expression and prognosis between liver tumor tissues and normal liver tissues and to analyze the extent to which different genes infiltrated TME cells by quantifying the relative abundance of 24 cells through single-sample genome enrichment analysis (ssGSEA). A risk score associated with the ERCC3 gene was constructed using the least absolute shrinkage and selection operator (LASSO) Cox regression model.
RESULTS: The expression of 11 ERCC3-related genes was significantly upregulated in HCC tumor tissues compared to normal liver tissues, and high expression of these genes was significantly associated with poor prognosis in HCC patients. The key genes (11 ERCC3-related genes) were closely associated with the nucleic acid reduction signaling pathway in nucleic acid metabolism and the viral oncogenic pathway, suggesting that these key genes may play a role in tumor cell proliferation, migration, and invasion, as well as in the pathogenesis of virus-associated HCC. In addition, the infiltration characteristics of TME immune cells in normal and tumor tissues were different. Immune and mesenchymal activity was significantly lower in tumor tissues than in healthy liver tissues. This study revealed that key genes were significantly positively correlated with CTLA4 and enriched in central memory CD4 T cells, effector memory CD4 T cells, activated CD4 T cells, and type 2 T helper cells. The prognostic model constructed by regression analysis could better distinguish patients into high-risk and low-risk groups, and the survival analysis showed that the survival time of patients with high-risk score subtypes was significantly lower than that of patients with low-risk scores and that the high-risk group contained higher levels of immune-suppressive cells, which may be a mediator of immune escape. Moreover, multivariate analyses showed that the risk score profile is a reliable and unbiased biomarker for assessing the prognosis of HCC patients, and its value in predicting the outcome of immunotherapy was also confirmed.
CONCLUSIONS: This study revealed a novel genetic signature that is significantly associated with TME cell infiltration and prognosis in HCC patients. It demonstrated that the combined action of multiple key genes associated with ERCC3 plays a crucial role in shaping the diversity and complexity of TME cell infiltrates. Evaluating the combined characteristics of multiple key genes associated with ERCC3 can help predict the outcome of immunotherapy in patients and provide new potential targets for immuno-individualized therapeutic studies on HCC.

Ataxia telangiectasia mutated (ATM), an apical DNA damage response gene, is a commonly mutated gene in tumors, and its mutation could strengthen tumor immunogenicity and alter the expression of PD-L1, which potentially contributes to immune checkpoint inhibitors (ICIs) therapy.
The characteristics of ATM mutation and its relationship with the ICIs-treated clinical prognosis have been analyzed comprehensively in this paper. The overall frequency of ATM mutations has been found to be 4% (554/10953) in the cancer genome atlas (TCGA) cohort.
Both the TMB and MSI levels in patients with ATM mutations were significantly higher than those in patients without mutations (P < 0.0001). The median TMB was positively correlated with the frequency of ATM mutations (r = 0.54, P = 0.003). In the TCGA cohort, patients with ATM mutations had better clinical benefits in terms of overall survival (OS, hazard ratio (HR) = 0.736, 95% CI = 0.623 - 0.869), progression-free survival (PFS, HR = 0.761, 95% CI = 0.652 - 0.889), and disease-free survival (DFS, HR = 0.686, 95% CI = 0.512 - 0.919)] than patients without ATM mutations. Subsequently, the verification results showed ATM mutations to be significantly correlated with longer OS in ICIs-treated patients (HR = 0.710, 95% CI = 0.544 - 0.928). Further exploration indicated ATM mutation to be significantly associated with regulated anti-tumor immunity (P < 0.05).
Our findings highlight the value of ATM mutation as a promising biomarker to predict ICIs therapy in multiple tumors.

BACKGROUND: Vasculogenic mimicry, a novel neovascularization pattern of aggressive tumors, is associated with poor clinical outcomes.
OBJECTIVE: The aim of this research was to establish a new model, termed VC score, to predict the prognosis, Tumor Microenvironment (TME) components, and immunotherapeutic response in Hepatocellular Carcinoma (HCC).
METHODS: The expression data of the public databases were used to develop the prognostic model. Consensus clustering was performed to confirm the molecular subtypes with ideal clustering efficacy. The high- and low-risk groups were stratified utilizing the VC score. Various methodologies, including survival analysis, single-sample Gene Set Enrichment Analysis (ssGSEA), Tumor Immune Dysfunction and Exclusion scores (TIDE), Immunophenoscore (IPS), and nomogram, were utilized for verification of the model performance and to characterize the immune status of HCC tissues. GSEA was performed to mine functional pathway information.
RESULTS: The survival and immune characteristics varied between the three molecular subtypes. A five-gene signature (TPX2, CDC20, CFHR4, SPP1, and NQO1) was verified to function as an independent predictive factor for the prognosis of patients with HCC. The high-risk group exhibited lower Overall Survival (OS) rates and higher mortality rates in comparison to the low-risk group. Patients in the low-risk group were predicted to benefit from immune checkpoint inhibitor therapy and exhibit increased sensitivity to immunotherapy. Enrichment analysis revealed that signaling pathways linked to the cell cycle and DNA replication processes exhibited enrichment in the high-risk group.
CONCLUSIONS: The VC score holds the potential to establish individualized treatment plans and clinical management strategies for patients with HCC.

Chemotherapy resistance is a common cause of tumor treatment failure. Various molecular responses, such as increased expression of efflux transporter proteins, including Pglycoprotein (P-gp), changes in the tumor microenvironment (TME), the role of platelets, and the effects of cancer stem cells (CSCs), can lead to drug resistance. Through extensive research on the mechanisms of drug resistance, more effective anti-resistance drugs and therapeutic approaches are being developed. This review explores drug resistance mechanisms and summarizes relevant anti-resistance drugs. In addition, due to the therapeutic limitations of the aforementioned treatments, new advances in nanocarrier-based combination immunotherapy to address the challenge of drug resistance have been described. Nanocarriers combined with immunotherapy can not only target tumor sites for targeted drug release but also modulate the autoimmune system and enhance immune efficacy, thereby overcoming tumor drug resistance. This review suggests new strategies for overcoming tumor drug resistance and is expected to inform tumor treatment and prognosis.

BACKGROUND: As a binding protein of Ki67, NIFK plays an important role in the mitosis of cells and is closely related to the progression of specific types of tumors. However, there is still a lack of systematic analysis of NIFK in pan-cancer and insufficient research to explore its role in human tumors.
METHODS: We systematically evaluated the pan-cancer expression and mutation of NIFK in human cancers using data from The Cancer Genome Atlas (TCGA) through large-scale bioinformatics analysis. In addition, we explored the pan-cancer immunological characteristics of NIFK, especially in colorectal adenocarcinoma (COAD). Furthermore, we used single-cell sequencing to analyze the expression of NIFK in different cells of COAD tissues and performed GO, KEGG, and gene set enrichment analysis of NIFK in COAD. Lastly, we evaluated the effects of NIFK knockdown on the colorectal cancer cell lines in in vitro experiment.
RESULTS: We found that NIFK was overexpressed in almost all types of tumors and showed significant prognostic efficacy. Additionally, correlations between NIFK and specific immune features, such as immune cell infiltration, immune checkpoint genes, TMB, and MSI, suggest that NIFK may be used to guide immunotherapy. Subsequently, it was found that the expression of NIFK was significantly upregulated in tumor cells through single-cell sequencing analysis, and the NIFK gene was closely associated with tumor progression and immune therapy response. Finally, we further elucidated the role of NIFK in colorectal cancer and found that downregulation of NIFK expression could inhibit the proliferation, migration, and invasion ability of colorectal cancer cells.
CONCLUSIONS: The results of this study demonstrated that NIFK, as a member of the pan-cancer genes, will serve as a biomarker and a potential therapeutic target for a range of cancer types, providing new insight into precision medicine.