Identification of a glycolysis-related gene signature associated with clinical outcome for patients with lung squamous cell carcinoma

HKDC1 promotes liver cancer stemness under hypoxia through stabilizing β-catenin

BACKGROUND AND AIMS

Hexokinases (HKs), a group of enzymes catalyzing the first step of glycolysis, have been shown to play important roles in liver metabolism and tumorigenesis. Our recent studies identified hexokinase domain containing 1 (HKDC1) as a top candidate associated with liver cancer metastasis. We aimed to compare its cell-type specificity with other HKs upregulated in liver cancer and investigate the molecular mechanisms underlying its involvement in liver cancer metastasis.

APPROACH AND RESULTS

We found that, compared to HK1 and HK2, the other 2 commonly upregulated HKs in liver cancer, HKDC1 was most strongly associated with the metastasis potential of tumors and organoids derived from 2 liver cancer mouse models we previously established. RNA in situ hybridization and single-cell RNA-seq analysis revealed that HKDC1 was specifically upregulated in malignant cells in HCC and cholangiocarcinoma patient tumors, whereas HK1 and HK2 were widespread across various tumor microenvironment lineages. An unbiased metabolomic profiling demonstrated that HKDC1 overexpression in HCC cells led to metabolic alterations distinct from those from HK1 and HK2 overexpression, with HKDC1 particularly impacting the tricarboxylic acid cycle. HKDC1 was prometastatic in HCC orthotopic and tail vein injection mouse models. Molecularly, HKDC1 was induced by hypoxia and bound to glycogen synthase kinase 3β to stabilize β-catenin, leading to enhanced stemness of HCC cells.

CONCLUSIONS

Overall, our findings underscore HKDC1 as a prometastatic HK specifically expressed in the malignant compartment of primary liver tumors, thereby providing a mechanistic basis for targeting this enzyme in advanced liver cancer.

Energy metabolism as the hub of advanced non-small cell lung cancer management: a comprehensive view in the framework of predictive, preventive, and personalized medicine

Energy metabolism is a hub of governing all processes at cellular and organismal levels such as, on one hand, reparable vs. irreparable cell damage, cell fate (proliferation, survival, apoptosis, malignant transformation etc.), and, on the other hand, carcinogenesis, tumor development, progression and metastazing versus anti-cancer protection and cure. The orchestrator is the mitochondria who produce, store and invest energy, conduct intracellular and systemically relevant signals decisive for internal and environmental stress adaptation, and coordinate corresponding processes at cellular and organismal levels. Consequently, the quality of mitochondrial health and homeostasis is a reliable target for health risk assessment at the stage of reversible damage to the health followed by cost-effective personalized protection against health-to-disease transition as well as for targeted protection against the disease progression (secondary care of cancer patients against growing primary tumors and metastatic disease). The energy reprogramming of non-small cell lung cancer (NSCLC) attracts particular attention as clinically relevant and instrumental for the paradigm change from reactive medical services to predictive, preventive and personalized medicine (3PM). This article provides a detailed overview towards mechanisms and biological pathways involving metabolic reprogramming (MR) with respect to inhibiting the synthesis of biomolecules and blocking common NSCLC metabolic pathways as anti-NSCLC therapeutic strategies. For instance, mitophagy recycles macromolecules to yield mitochondrial substrates for energy homeostasis and nucleotide synthesis. Histone modification and DNA methylation can predict the onset of diseases, and plasma C7 analysis is an efficient medical service potentially resulting in an optimized healthcare economy in corresponding areas. The MEMP scoring provides the guidance for immunotherapy, prognostic assessment, and anti-cancer drug development. Metabolite sensing mechanisms of nutrients and their derivatives are potential MR-related therapy in NSCLC. Moreover, miR-495-3p reprogramming of sphingolipid rheostat by targeting Sphk1, 22/FOXM1 axis regulation, and A2 receptor antagonist are highly promising therapy strategies. TFEB as a biomarker in predicting immune checkpoint blockade and redox-related lncRNA prognostic signature (redox-LPS) are considered reliable predictive approaches. Finally, exemplified in this article metabolic phenotyping is instrumental for innovative population screening, health risk assessment, predictive multi-level diagnostics, targeted prevention, and treatment algorithms tailored to personalized patient profiles-all are essential pillars in the paradigm change from reactive medical services to 3PM approach in overall management of lung cancers. This article highlights the 3PM relevant innovation focused on energy metabolism as the hub to advance NSCLC management benefiting vulnerable subpopulations, affected patients, and healthcare at large.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00357-5.

Effects of Camrelizumab Combined with First-Line Chemotherapy on Serum SCC, VEGF Levels, and Adverse Reactions in Patients with Advanced Squamous Cell Carcinoma of the Lung

Objective

To study the effects of camrelizumab accompanied by first-line chemotherapy on serum SCC, VEGF levels, and adverse reactions in people undergoing advanced lung squamous cell carcinoma.

Methods

Data sources of the study subjects were 60 people suffering from advanced squamous cell carcinoma of the lung hospitalized from January 2018 to October 2019. They were assigned to two groups, including the control group and the observation group in a random manner, and each consisted of 30 patients. Those in the observation group received camrelizumab (SHR-1210), and gemcitabine plus cisplatin (GP) chemotherapy were treated in the control group. Finally, according to the results, we compare the data of patients in both groups so as to find out the similarities and differences.

Results

Among them, the effective efficiency of clinical treatment in the control group reached 36.67%, and that in the observation group reached 56.67%. Intuitively, it can be concluded that the control group showed lower results than the observed group. The observed group turned out to have higher periodic survival and progression free survival (PFS) of patients than the other group. During and after the cycle treatment, the data of SCC and VEGF were reduced to some extent, but the control group appeared to have a more evident reduction rate than the other group.

Conclusion

SHR-1210 combined with chemotherapy has a considerable effect in practical application and has excellent clinical performance.

The hexokinase "HKDC1" interaction with the mitochondria is essential for liver cancer progression

Liver cancer (LC) is the fourth leading cause of death from cancer malignancies. Recently, a putative fifth hexokinase, hexokinase domain containing 1 (HKDC1), was shown to have significant overexpression in LC compared to healthy liver tissue. Using a combination of in vitro and in vivo tools, we examined the role of HKDC1 in LC development and progression. Importantly, HKDC1 ablation stops LC development and progression via its action at the mitochondria by promoting metabolic reprogramming and a shift of glucose flux away from the TCA cycle. HKDC1 ablation leads to mitochondrial dysfunction resulting in less cellular energy, which cannot be compensated by enhanced glucose uptake. Moreover, we show that the interaction of HKDC1 with the mitochondria is essential for its role in LC progression, and without this interaction, mitochondrial dysfunction occurs. As HKDC1 is highly expressed in LC cells, but only to a minimal degree in hepatocytes under normal conditions, targeting HKDC1, specifically its interaction with the mitochondria, may represent a highly selective approach to target cancer cells in LC.

Development and Validation of a 7-Gene Inflammatory Signature Forecasts Prognosis and Diverse Immune Landscape in Lung Adenocarcinoma

Background: Inflammatory responses are strongly linked with tumorigenesis and cancer development. This research aimed to construct and validate a novel inflammation response–related risk predictive signature for forecasting the prognosis of patients with LUAD.

Methods: Differential expression analysis, univariate Cox, LASSO, and multivariate Cox regression analyses of 200 inflammatory response–related genes (IRRG) were performed to establish a risk predictive model in the TCGA training cohort. The performance of the IRRG model was verified in eight GEO datasets. GSEA analysis, ESTIMATE algorithms, and ssGSEA analysis were applied to elucidate the possible mechanisms. Furthermore, the relationship analysis between risk score, model genes, and chemosensitivity was performed. Last, we verified the protein expression of seven model genes by immunohistochemical staining or Western blotting.

Results: We constructed a novel inflammatory response–related 7-gene signature (MMP14, BTG2, LAMP3, CCL20, TLR2, IL7R, and PCDH7). Patients in the high-risk group presented markedly decreased survival time in the TCGA cohort and eight GEO cohorts than the low-risk group. Interestingly, multiple pathways related to immune response were suppressed in high-risk groups. The low infiltration levels of B cell, dendritic cell, natural killer cell, and eosinophil can significantly affect the unsatisfactory prognosis of the high-risk group in LUAD. Moreover, the tumor cells’ sensitivity to anticancer drugs was markedly related to risk scores and model genes. The protein expression of seven model genes was consistent with the mRNA expression.

Conclusion: Our IRRG prognostic model can effectively forecast LUAD prognosis and is tightly related to immune infiltration.

Construction of a novel methylation-related prognostic model for colorectal cancer based on microsatellite status

The present study aimed to construct a novel methylation-related prognostic model based on microsatellite status that may enhance the prognosis of colorectal cancer (CRC) from methylation and microsatellite status perspective. DNA methylation and mRNA expression data with clinical information were downloaded from The Cancer Genome Atlas (TCGA) data set. The samples were divided into microsatellite stability and microsatellite instability group, and CIBERSORT was used to assess the immune cell infiltration characteristics. After identifying the differentially methylated genes and differentially expression genes using R packages, the methylation-driven genes were further identified. Prognostic genes that were used to establish the methylation-related risk score model were generated by the univariate and multivariate Cox regression model. Finally, we established and evaluated the methylation-related prognostic model for CRC patients. A total of 69 MDGs were obtained and three of these genes (MIOX, TH, DKFZP434K028) were selected to construct the prognostic model. Patients in the low-risk score group had a conspicuously better overall survival than those in the high-risk score group (p < .0001). The area under the receiver operating characteristic curve for this model was 0.689 at 3 years, 0.674 at 4 years, and 0.658 at 5 years. The Wilcoxon test showed that higher risk score was associated with higher T stage (p = .01), N stages (p = .0028), metastasis (p = .013), and advanced pathological stage (p = .0013). However, the more instability of microsatellite status, the lower risk score of CRC patients (p = .0048). Our constructed methylation-related prognostic model based on microsatellite status presents potential significance in assessing recurrence risk stratification, tumor staging, and immunotherapy for CRC patients.