Warburg effect in Gynecologic cancers

ESM1 enhances fatty acid synthesis and vascular mimicry in ovarian cancer by utilizing the PKM2-dependent warburg effect within the hypoxic tumor microenvironment

BACKGROUND

The hypoxic tumor microenvironment is a key factor that promotes metabolic reprogramming and vascular mimicry (VM) in ovarian cancer (OC) patients. ESM1, a secreted protein, plays an important role in promoting proliferation and angiogenesis in OC. However, the role of ESM1 in metabolic reprogramming and VM in the hypoxic microenvironment in OC patients has not been determined.

METHODS

Liquid chromatography coupled with tandem MS was used to analyze CAOV3 and OV90 cells. Interactions between ESM1, PKM2, UBA2, and SUMO1 were detected by GST pull-down, Co-IP, and molecular docking. The effects of the ESM1-PKM2 axis on cell glucose metabolism were analyzed based on an ECAR experiment. The biological effects of the signaling axis on OC cells were detected by tubule formation, transwell assay, RT‒PCR, Western blot, immunofluorescence, and in vivo xenograft tumor experiments.

RESULTS

Our findings demonstrated that hypoxia induces the upregulation of ESM1 expression through the transcription of HIF-1α. ESM1 serves as a crucial mediator of the interaction between PKM2 and UBA2, facilitating the SUMOylation of PKM2 and the subsequent formation of PKM2 dimers. This process promotes the Warburg effect and facilitates the nuclear translocation of PKM2, ultimately leading to the phosphorylation of STAT3. These molecular events contribute to the promotion of ovarian cancer glycolysis and vasculogenic mimicry. Furthermore, our study revealed that Shikonin effectively inhibits the molecular interaction between ESM1 and PKM2, consequently preventing the formation of PKM2 dimers and thereby inhibiting ovarian cancer glycolysis, fatty acid synthesis and vasculogenic mimicry.

CONCLUSION

Our findings demonstrated that hypoxia increases ESM1 expression through the transcriptional regulation of HIF-1α to induce dimerization via PKM2 SUMOylation, which promotes the OC Warburg effect and VM.

Construction and Validation of a Prognostic Risk Prediction Model for Lactate Metabolism-Related lncRNA in Endometrial Cancer

Endometrial cancer (EC) is a common group of malignant epithelial tumors that mainly occur in the female endometrium. Lactate is a key regulator of signal pathways in normal and malignant tissues. However, there is still no research on lactate metabolism-related lncRNA in EC. Here, we intended to establish a prognostic risk model for EC based on lactate metabolism-related lncRNA to forecast the prognosis of EC patients. First, we found that 38 lactate metabolism-associated lncRNAs were significantly overall survival through univariate Cox regression analysis. Using minimum absolute contraction and selection operator (LASSO) regression analysis and multivariate Cox regression analysis, six lactate metabolism-related lncRNAs were established as independent predictor in EC patients and were used to establish a prognostic risk signature. We next used multifactorial COX regression analysis and receiver operating characteristic (ROC) curve analysis to confirm that risk score was an independent prognostic factor of overall patient survival. The survival time of patients with EC in different high-risk populations was obviously related to clinicopathological factors. In addition, lactate metabolism-related lncRNA in high-risk population participated in multiple aspects of EC malignant progress through Gene Set Enrichment Analysis, Genomes pathway and Kyoto Encyclopedia of Genes and Gene Ontology. And risk scores were strongly associated with tumor mutation burden, immunotherapy response and microsatellite instability. Finally, we chose a lncRNA SRP14-AS1 to validate the model we have constructed. Interestingly, we observed that the expression degree of SRP14-AS1 was lower in tumor tissues of EC patients than in normal tissues, which was consistent with our findings in the TCGA database. In conclusion, our study constructed a prognostic risk model through lactate metabolism-related lncRNA and validated the model, confirming that the model can be used to predict the prognosis of EC patients and providing a molecular analysis of potential prognostic lncRNA for EC.

Targeting the Metabolic Paradigms in Cancer and Diabetes

Dysregulated metabolic dynamics are evident in both cancer and diabetes, with metabolic alterations representing a facet of the myriad changes observed in these conditions. This review delves into the commonalities in metabolism between cancer and type 2 diabetes (T2D), focusing specifically on the contrasting roles of oxidative phosphorylation (OXPHOS) and glycolysis as primary energy-generating pathways within cells. Building on earlier research, we explore how a shift towards one pathway over the other serves as a foundational aspect in the development of cancer and T2D. Unlike previous reviews, we posit that this shift may occur in seemingly opposing yet complementary directions, akin to the Yin and Yang concept. These metabolic fluctuations reveal an intricate network of underlying defective signaling pathways, orchestrating the pathogenesis and progression of each disease. The Warburg phenomenon, characterized by the prevalence of aerobic glycolysis over minimal to no OXPHOS, emerges as the predominant metabolic phenotype in cancer. Conversely, in T2D, the prevailing metabolic paradigm has traditionally been perceived in terms of discrete irregularities rather than an OXPHOS-to-glycolysis shift. Throughout T2D pathogenesis, OXPHOS remains consistently heightened due to chronic hyperglycemia or hyperinsulinemia. In advanced insulin resistance and T2D, the metabolic landscape becomes more complex, featuring differential tissue-specific alterations that affect OXPHOS. Recent findings suggest that addressing the metabolic imbalance in both cancer and diabetes could offer an effective treatment strategy. Numerous pharmaceutical and nutritional modalities exhibiting therapeutic effects in both conditions ultimately modulate the OXPHOS-glycolysis axis. Noteworthy nutritional adjuncts, such as alpha-lipoic acid, flavonoids, and glutamine, demonstrate the ability to reprogram metabolism, exerting anti-tumor and anti-diabetic effects. Similarly, pharmacological agents like metformin exhibit therapeutic efficacy in both T2D and cancer. This review discusses the molecular mechanisms underlying these metabolic shifts and explores promising therapeutic strategies aimed at reversing the metabolic imbalance in both disease scenarios.

FOXP2 suppresses the proliferation, invasion, and aerobic glycolysis of hepatocellular carcinoma cells by regulating the KDM5A/FBP1 axis

The Warburg effect is the preference of cancer cells to use glycolysis rather than oxidative phosphorylation to generate energy. Accumulating evidence suggests that aerobic glycolysis is widespread in hepatocellular carcinoma (HCC) and closely related to tumorigenesis. The purpose of this study was to investigate the role and mechanism of forkhead box P2 (FOXP2) in aerobic glycolysis and tumorigenesis in HCC. Here, we found that FOXP2 was lower expressed in HCC tissues and cells than in nontumor tissues and normal hepatocytes. Overexpression of FOXP2 suppressed cell proliferation and invasion of HCC cells and promoted cell apoptosis in vitro, and hindered the growth of mouse xenograft tumors in vivo. Further researches showed that FOXP2 inhibited the Warburg effect in HCC cells. Moreover, we demonstrated that FOXP2 up-regulated the expression of fructose-1, 6-diphosphatase (FBP1), and the inhibitory effect of FOXP2 on glycolysis was dependent on FBP1. Mechanistically, as a transcription factor, FOXP2 negatively regulated the transcription of lysine-specific demethylase 5A (KDM5A), and then blocked KDM5A-induced H3K4me3 demethylation in FBP1 promoter region, thereby promoting the expression of FBP1. Consistently, overexpressing KDM5A or silencing FBP1 effectively reversed the inhibitory effect of FOXP2 on HCC progression. Together, our findings revealed the mechanistic role of the FOXP2/KDM5A/FBP1 axis in glycolysis and malignant progression of HCC cells, providing a potential molecular target for the therapy of HCC.

Preparation of a Mesoporous Biosensor for Human Lactate Dehydrogenase for Potential Anticancer Inhibitor Screening

Cancer is the second leading cause of death worldwide, with a dramatic impact due to the acquired resistance of cancers to used chemotherapeutic drugs and treatments. The enzyme lactate dehydrogenase (LDH-A) is responsible for cancer cell proliferation. Recently the development of selective LDH-A inhibitors as drugs for cancer treatment has been reported to be an efficient strategy aiming to decrease cancer cell proliferation and increase the sensitivity to traditional chemotherapeutics. This study aims to obtain a stable and active biocatalyst that can be utilized for such drug screening purposes. It is conceived by adopting human LDH-A enzyme (hLDH-A) and investigating different immobilization techniques on porous supports to achieve a stable and reproducible biosensor for anticancer drugs. The hLDH-A enzyme is covalently immobilized on mesoporous silica (MCM-41) functionalized with amino and aldehyde groups following two different methods. The mesoporous support is characterized by complementary techniques to evaluate the surface chemistry and the porous structure. Fluorescence microscopy analysis confirms the presence of the enzyme on the support surface. The tested immobilizations achieve yields of ≥80%, and the best retained activity of the enzyme is as high as 24.2%. The optimal pH and temperature of the best immobilized hLDH-A are pH 5 and 45 °C for the reduction of pyruvate into lactate, while those for the free enzyme are pH 8 and 45 °C. The stability test carried out at 45 °C on the immobilized enzyme shows a residual activity close to 40% for an extended time. The inhibition caused by NHI-2 is similar for free and immobilized hLDH-A, 48% and 47%, respectively. These findings are significant for those interested in immobilizing enzymes through covalent attachment on inorganic porous supports and pave the way to develop stable and active biocatalyst-based sensors for drug screenings that are useful to propose drug-based cancer treatments.

Oncolytic Avian Reovirus σA-Modulated Upregulation of the HIF-1α/C-myc/glut1 Pathway to Produce More Energy in Different Cancer Cell Lines Benefiting Virus Replication

Our previous reports proved that the structural protein σA of avian reovirus (ARV) is an energy activator which can regulate cellular metabolism that is essential for virus replication. This study has further demonstrated that the ARV protein σA is able to upregulate the HIF-1α/myc/glut1 pathway in three cancer cell lines (A549, B16-F10, and HeLa) to alter the metabolic pathway of host cells. Quantitative real-time RT-PCR and Western blotting results have revealed that σA protein could enhance both mRNA and the protein levels of HIF-1α, c-myc, and glut1 in these cancer cell lines. In this work, ATeam immunofluorescence staining was used to reveal that knockdown of HIF-1α, c-myc, and glut1 by shRNAs decreased cellular ATP levels. Our data reveal that the ARV σA protein can downregulate lactate fermentation and upregulate glutaminolysis. The σA protein upregulates glutaminase, which converts glutamate into the TCA cycle intermediate α-ketoglutarate, activating the TCA cycle. In the lactate fermentation pathway, ARV σA protein suppresses lactate dehydrogenase A (LDHA), implying the Warburg effect does not occur in these cancer cell lines. This study provides a novel finding revealing that ARV σA protein upregulates glycolysis and glutaminolysis to produce energy using the HIF-1α/c-myc/glut1 pathway to benefit virus replication in these cancer cell lines.

Construction and validation of a metabolic-related genes prognostic model for oral squamous cell carcinoma based on bioinformatics

BACKGROUND

Oral squamous cell carcinoma (OSCC) accounts for a frequently-occurring head and neck cancer, which is characterized by high rates of morbidity and mortality. Metabolism-related genes (MRGs) show close association with OSCC development, metastasis and progression, so we constructed an MRGs-based OSCC prognosis model for evaluating OSCC prognostic outcome.

METHODS

This work obtained gene expression profile as well as the relevant clinical information from the The Cancer Genome Atlas (TCGA) database, determined the MRGs related to OSCC by difference analysis, screened the prognosis-related MRGs by performing univariate Cox analysis, and used such identified MRGs for constructing the OSCC prognosis prediction model through Lasso-Cox regression. Besides, we validated the model with the GSE41613 dataset based on Gene Expression Omnibus (GEO) database.

RESULTS

The present work screened 317 differentially expressed MRGs from the database, identified 12 OSCC prognostic MRGs through univariate Cox regression, and then established a clinical prognostic model composed of 11 MRGs by Lasso-Cox analysis. Based on the optimal risk score threshold, cases were classified as low- or high-risk group. As suggested by Kaplan-Meier (KM) analysis, survival rate was obviously different between the two groups in the TCGA training set (P < 0.001). According to subsequent univariate and multivariate Cox regression, risk score served as the factor to predict prognosis relative to additional clinical features (P < 0.001). Besides, area under ROC curve (AUC) values for patient survival at 1, 3 and 5 years were determined as 0.63, 0.70, and 0.76, separately, indicating that the prognostic model has good predictive accuracy. Then, we validated this clinical prognostic model using GSE41613. To enhance our model prediction accuracy, age, gender, risk score together with TNM stage were incorporated in a nomogram. As indicated by results of ROC curve and calibration curve analyses, the as-constructed nomogram had enhanced prediction accuracy compared with clinicopathological features alone, besides, combining clinicopathological characteristics with risk score contributed to predicting patient prognosis and guiding clinical decision-making.

CONCLUSION

In this study, 11 MRGs prognostic models based on TCGA database showed superior predictive performance and had a certain clinical application prospect in guiding individualized.

A novel small molecule glycolysis inhibitor WZ35 exerts anti-cancer effect via metabolic reprogramming

Background

Liver cancer is the fifth leading cause of cancer death worldwide, but early diagnosis and treatment of liver cancer remains a clinical challenge. How to screen and diagnose liver cancer early and prolong the survival rate is still the focus of researchers.

Methods

Cell experiments were used to detect the effect of WZ35 on the colony formation ability and proliferation activity of hepatoma cells, nude mouse experiment to observe the in vivo anticancer activity and toxic side effects of WZ35; metabolomics analysis, glucose metabolism experiment and Seahorse analysis of liver cancer cells treated with WZ35; cell experiments combined with bioinformatics analysis to explore the mechanism of WZ35-mediated metabolic reprogramming to exert anticancer activity; tissue microarray and case analysis to evaluate the clinical significance of biomarkers for early diagnosis, treatment and prognosis evaluation of liver cancer.

Results

WZ35 inhibited the proliferation activity of various cell lines of liver cancer, and showed good therapeutic effect in nude mice model of hepatocellular carcinoma without obvious toxic and side effects; WZ35 inhibited the absorption of glucose in hepatoma cells, and the drug effect glycolysis, phosphorylation and purine metabolism are relatively seriously damaged; WZ35 mainly inhibits YAP from entering the nucleus as a transcription factor activator by activating oxidative stress in liver cancer cells, reducing the transcription of GLUT1, and finally reducing its GLUT1. Tissue microarray and case analysis showed that GLUT1 and YAP were highly expressed and correlated in liver cancer patients, and were associated with poor patient prognosis. The GLUT1-YAP risk model had a high score in predicting prognosis.

Conclusion

The study confirms that WZ35 is a small molecule glycolysis inhibitor, and through its properties, it mediates metabolic reprogramming dominated by impaired glycolysis, oxidative phosphorylation and purine metabolism to inhibit the proliferation activity of liver cancer cells. Our findings present novel insights into the pathology of liver cancer and potential targets for new therapeutic strategies. GLUT1-YAP has important reference significance for predicting the stages of disease progression in liver cancer patients and have the potential to serve as novel biomarkers for the diagnosis and treatment of liver cancer.

Mutant TP53 driving the Warburg Effect in Mantle Cell lymphoma

The p53 mutation R273H in tumor cells leads to increased glucose uptake, lactic acidosis, and accelerated tumor growth, as was previously shown in mice. We here present a patient with mantle cell lymphoma harboring this p53_R273H mutation, whose clinical course is characterized by severe lactic acidosis, hypoglycemia, and aggressive disease.

Predictive Value of the Hemoglobin-Albumin-Lymphocyte-Platelet (HALP) Index on the Oncological Outcomes of Locally Advanced Cervical Cancer Patients

Purpose

The oncological outcomes of locally advanced cervical cancer (LACC) patients after treatment are poor and heterogeneous. This study aimed to determine the role of the hemoglobin-albumin-lymphocyte-platelet (HALP) inflammatory index in predicting oncological outcomes in LACC patients.

Patients and Methods

A total of 1588 LACC patients who received radiation therapy or concurrent chemoradiation were divided into training and test sets. Characteristics, survival, and a HALP cutoff determined by X-tile software were used to build predictive survival models on the training data. Validation of the model was performed on both sets.

Results

Patients with a HALP score ≤22.2 tended to have lower age (p < 0.001), lower comorbidity rate (p = 0.016), lower body mass index (p < 0.001), higher stage (p < 0.001), larger tumor size (p < 0.001), and higher likelihood to receive radiation alone than concurrent chemoradiation (p < 0.001). Survival analysis demonstrated that HALP >22.2 was independently associated with better progression-free survival (PFS; hazard ratio; HR 0.55) and overall survival (OS; HR 0.43). Validation of survival prediction by receiver-operating characteristics demonstrated a significantly improved area under the curve of survival prediction in both sets (p < 0.001) after the addition of the HALP index to the model.

Conclusion

A lower HALP score was an independent predictive factor for poorer oncological outcomes. The addition of the HALP index can improve the accuracy of predicting the oncological outcomes of LACC patients.

Warburg effect in keloids: A unique feature different from other types of scars

Keloid fibroblasts (KFs) undergo reprogramming of the metabolic phenotype from oxidative phosphorylation to the Warburg effect. However, more studies are needed to demonstrate whether there is a Warburg effect in KFs and to determine whether there is a similar phenomenon in other types of scars or in the proliferative stage of scars. In our study, the mRNA and protein expression of key glycolytic enzymes, glucose consumption and lactate production in KFs, normal skin fibroblasts (NFs), atrophic scar fibroblasts (ASFs), proliferative stage scar fibroblasts (PSSFs), and hypertrophic scar fibroblasts (HSFs) were detected. In addition, the effects of 2-deoxy-d-glucose (2-DG, a glycolysis inhibitor) on cell proliferation in KFs and NFs were studied. We found that the mRNA and protein expression of key glycolytic enzymes in KFs were significantly upregulated compared with those in NFs. Glucose consumption and lactate production in KFs were also higher than that in NFs. However, we found no similar phenomenon in ASFs, PSSFs, or HSFs. When treated with 2mmol/l 2-DG, the cell viability of KFs decreased more than that of NFs. What's more, treatment with increasing concentrations of 2-DG could inhibit cell viability and migration of KFs in a dose-dependent manner. In conclusion, the Warburg effect in KFs is a feature different from ASFs, PSSFs, or HSFs. Keloids are essentially different from other types of scars in terms of energy metabolism. This characteristic of KFs could provide new hope for the early diagnosis and treatment of keloids.

Response Predictive Markers and Synergistic Agents for Drug Repositioning of Statins in Ovarian Cancer

In the field of drug repurposing, the use of statins for treating dyslipidemia is considered promising in ovarian cancer treatment based on epidemiological studies and basic research findings. Biomarkers should be established to identify patients who will respond to statin treatment to achieve clinical application. In the present study, we demonstrated that statins have a multifaceted mode of action in ovarian cancer and involve pathways other than protein prenylation. To identify biomarkers that predict the response to statins, we subjected ovarian cancer cells to microarray analysis and calculated Pearson’s correlation coefficients between gene expression and cell survival after statin treatment. The results showed that VDAC1 and LDLRAP1 were positively and negatively correlated with the response to statins, respectively. Histoculture drug response assays revealed that statins were effective in clinical samples. We also confirmed the synergistic effects of statins with paclitaxel and panobinostat and determined that statins are hematologically safe to administer to statin-treated mice. Future clinical trials based on the expression of the biomarkers identified in this study for repurposing statins for ovarian cancer treatment are warranted.

Molecular insights and clinical impacts of extracellular vesicles in cancer

Cell-to-cell communication is a pivotal aspect of cancer biology. Recently, extracellular vesicles (EVs)have been shown to play essential roles in intercellular communications between cancer cells and the surrounding microenvironment owing to cancer development. EVs are small membrane-bound vesicles secreted by various cells containing proteins, lipids, mRNAs, and non-coding RNAs (microRNAs and long non-coding RNAs), which contribute to cancer cell development and progression. Here, we provide an overview of current research direction on EVs, especially biomolecules in EVs, and also point out the novel diagnostics, monitoring, predicting, and therapeutic aspects using EVs against cancer.

HOXC13 promotes cervical cancer proliferation, invasion and Warburg effect through β-catenin/c-Myc signaling pathway

Cervical cancer (CC) is one of the most common malignancy and is the second leading cause of death in gynecologic malignancies worldwide. The homeobox transcription factor homeobox C13 (HOXC13) has been demonstrated to play crucial roles in various cancers. However, its function in CC remains to be addressed. In the present study, upregulation of HOXC13 expression in human CC tissues was found in The Cancer Genome Atlas (TCGA) dataset and clinical samples and was associated with tumor size, FIGO stage and lymph node metastasis. Quantitative real-time polymerase chain reaction (qRT-PCR) and western blot assays suggested that the expression of HOXC13 was up-regulated in CC cells. Cell Counting Kit (CCK)-8, colony formation and cell cycle analysis assays indicated that HOXC13 promoted the proliferation and cycle progression of CC cells in vitro. Of note, knockdown of HOXC13 hinders tumor growth of xenograft tumor mice in vivo. Moreover, transwell and glycolysis measurement assays demonstrated that HOXC13 enhanced the migration, invasion and glycolysis of CC cells in vitro. Further mechanism analysis suggested that HOXC13 participated in CC progression through regulation of the β-catenin/c-Myc signaling pathway. Collectively, HOXC13 facilitated cell proliferation, migration, invasion and glycolysis through modulating β-catenin/c-Myc signaling pathway in CC, indicating that HOXC13 may provide a promising therapeutic target for the therapy of CC.

Glycolysis-Related Genes Serve as Potential Prognostic Biomarkers in Clear Cell Renal Cell Carcinoma

Metabolic rearrangement is a marker of cancer that has been widely studied in recent years. One of the major metabolic characteristics of tumor cells is the high levels of glycolysis, even under aerobic conditions, a phenomenon that is called the "Warburg effect." We investigated the expression and copy number variation (CNV) frequency of all glycolysis-related genes in multiple cancer types and found many differentially expressed genes, particularly in clear cell renal cell carcinoma (ccRCC). Single nucleotide variants (SNVs) showed that the overall average mutation frequency for all genes was low. The purpose of this study was to establish a predictive model by studying glycolysis-related genes in ccRCC. We compared the expression of glycolysis-related genes in 539 ccRCC tissues and 72 normal renal tissues from The Cancer Genome Atlas dataset and identified 17 upregulated and 26 downregulated genes. Pathway analysis revealed that PSAT1 and SDHB could activate the cell cycle, RPIA could activate the DNA damage response, and HK3 could activate apoptosis and EMT signaling, while PDK2 could inhibit apoptosis. The results of the drug sensitivity analysis suggested that some of these differentially expressed genes were positively correlated with drug sensitivity. Thirteen genes were selected from the gene coexpression network and the LASSO regression analysis. The Kaplan-Meier overall survival curves showed that the expression of upregulated genes in ccRCC patients was associated with lower overall survival. We established a predictive model consisting of 13 genes (RPIA, G6PD, PSAT1, ENO2, HK3, IDH1, PDK4, PGM2, PGK1, FBP1, OGDH, SUCLA2, and SUCLG2). This predictive model correlated well with the development and progression of ccRCC. Thus, it is of great value in the diagnosis and prognostic evaluation of ccRCC and may aid the identification of potential prognostic biomarkers and drug targets.

ROCK2 Promotes Osteosarcoma Growth and Glycolysis by Up-Regulating HKII via Phospho-PI3K/AKT Signalling

Background

Osteosarcoma (OS) is a malignant bone tumour that exhibits a high mortality. While tumours thrive in a state of malnutrition, the mechanism by which OS cells adapt to metabolic stress through metabolic reprogramming remains unclear.

Methods

We analysed the expression of ROCK2 in osteosarcoma tissues by RT-qPCR and Western blot. Cell proliferation were analysed using CCK8, EdU and colony formation assays. The level of cell glycolysis was detected by glucose-6 phosphate, glucose consumption, lactate production and ATP levels.

Results

Herein, our study showed that ROCK2 expression in OS tissues was higher than in adjacent tissues. Functional assays have demonstrated that ROCK2 contributes to the growth of OS cells by inducing aerobic glycolysis. The current study revealed that ROCK2 knockdown decreased the levels of mitochondrial hexokinase II (HKII). And also indicated that ROCK2 served as a key enzyme in glycolysis and that it served an important role in tumour growth. A significant positive correlation was identified between the mRNA and protein expressions of ROCK2 and HKII, further demonstrating that ROCK2-induced glycolysis and proliferation was dependent on HKII expression in OS cells. Mechanistically, ROCK2 promotes HKII expression by activating the phospho-PI3K/AKT signalling pathway.

Conclusion

Taken together, the results of the current study linked the two drivers of OS growth and aerobic glycolysis and identified a new mechanism of ROCK2 control in OS.

Macrophages in pancreatic cancer: An immunometabolic perspective

As one of the most fatal gastrointestinal cancers, pancreatic cancer (PC) has a long-term survival rate that has shown limited improvement during recent decades and remains dismal. The poor prognosis is attributed to challenges in early detection, low opportunity for radical resection and resistance to chemotherapy and radiation. Macrophages are one of the most abundant infiltrating immune cells in PC stroma, and they can crosstalk with cancer cells, adipocytes and other stromal cells to modulate metabolism, inflammation and immune status, create an immunosuppressive tumor microenvironment (TME), and ultimately facilitate tumor initiation and progression. In this review, we summarize recent advances in our understanding of macrophage origin, distribution and polarization, as well as provide a thorough review of the role macrophages in PC carcinogenesis and development, as well as the underlying molecular mechanism. Additionally, we investigated macrophage targets in preclinical and clinical trials to evaluate their potential therapeutic value in PC.

Correlation Between von Hippel-Lindau Gene Expression and Tumor SUVmax and Survival Prognosis in Hepatocellular Carcinoma

Background

We investigated the relationship between the 18F-FDG PET/CT metabolic parameter SUVmax in primary hepatocellular carcinoma (HCC) and expression of von Hippel-Lindau (VHL), as well as its effect on HCC survival prognosis.

Material/Methods

We retrospectively analyzed data for 62 HCC patients who received 18F-FDG PET/CT before surgery at the First Affiliated Hospital of Bengbu Medical College from June 2013 to June 2018 (42 males, 20 females; median age 62 years). No treatment was performed prior to the examination. The relationship between preoperative 18F-FDG PET/CT metabolic parameters, clinical pathology, and disease prognosis was analyzed.

Results

SUVmax was significantly different in varying HCC pathological grades, and with tumor length, lymph node metastasis, portal vein tumor thrombus, and distant metastasis (p<0.05). SUVmax was significantly higher in the shorter patient survival group (p<0.05). 18F-FDG uptake was correlated with expression of glucose transporter 1 and VHL in tumor tissues (correlation coefficients 0.476 and 0.565, respectively; both p<0.05). Negative expression of VHL suggested poor tumor differentiation and poor prognosis, but no correlation was observed with patient age, sex, tumor length, lymph node metastasis, or distant metastasis. The survival time of patients with low VHL expression was significantly shorter than that of patients with positive VHL expression (p=0.02).

Conclusions

VHL expression in primary HCC has a significant correlation with SUVmax, and negative VHL expression predicts a worse clinical prognosis.