Avenues of research in dietary interventions to target tumor metabolism in osteosarcoma

Mitochondrial enzyme FAHD1 reduces ROS in osteosarcoma

This study investigated the impact of overexpressing the mitochondrial enzyme Fumarylacetoacetate hydrolase domain-containing protein 1 (FAHD1) in human osteosarcoma epithelial cells (U2OS) in vitro. While the downregulation or knockdown of FAHD1 has been extensively researched in various cell types, this study aimed to pioneer the exploration of how increased catalytic activity of human FAHD1 isoform 1 (hFAHD1.1) affects human cell metabolism. Our hypothesis posited that elevation in FAHD1 activity would lead to depletion of mitochondrial oxaloacetate levels. This depletion could potentially result in a decrease in the flux of the tricarboxylic acid (TCA) cycle, thereby accompanied by reduced ROS production. In addition to hFAHD1.1 overexpression, stable U2OS cell lines were established overexpressing a catalytically enhanced variant (T192S) and a loss-of-function variant (K123A) of hFAHD1. It is noteworthy that homologs of the T192S variant are present in animals exhibiting increased resistance to oxidative stress and cancer. Our findings demonstrate that heightened activity of the mitochondrial enzyme FAHD1 decreases cellular ROS levels in U2OS cells. However, these results also prompt a series of intriguing questions regarding the potential role of FAHD1 in mitochondrial metabolism and cellular development.

Exploring the relationship between metabolism and immune microenvironment in osteosarcoma based on metabolic pathways

BACKGROUND

Metabolic remodeling and changes in tumor immune microenvironment (TIME) in osteosarcoma are important factors affecting prognosis and treatment. However, the relationship between metabolism and TIME needs to be further explored.

METHODS

RNA-Seq data and clinical information of 84 patients with osteosarcoma from the TARGET database and an independent cohort from the GEO database were included in this study. The activity of seven metabolic super-pathways and immune infiltration levels were inferred in osteosarcoma patients. Metabolism-related genes (MRGs) were identified and different metabolic clusters and MRG-related gene clusters were identified using unsupervised clustering. Then the TIME differences between the different clusters were compared. In addition, an MRGs-based risk model was constructed and the role of a key risk gene, ST3GAL4, in osteosarcoma cells was explored using molecular biological experiments.

RESULTS

This study revealed four key metabolic pathways in osteosarcoma, with vitamin and cofactor metabolism being the most relevant to prognosis and to TIME. Two metabolic pathway-related clusters (C1 and C2) were identified, with some differences in immune activating cell infiltration between the two clusters, and C2 was more likely to respond to two chemotherapeutic agents than C1. Three MRG-related gene clusters (GC1-3) were also identified, with significant differences in prognosis among the three clusters. GC2 and GC3 had higher immune cell infiltration than GC1. GC3 is most likely to respond to immune checkpoint blockade and to three commonly used clinical drugs. A metabolism-related risk model was developed and validated. The risk model has strong prognostic predictive power and the low-risk group has a higher level of immune infiltration than the high-risk group. Knockdown of ST3GAL4 significantly inhibited proliferation, migration, invasion and glycolysis of osteosarcoma cells and inhibited the M2 polarization of macrophages.

CONCLUSION

The metabolism of vitamins and cofactors is an important prognostic regulator of TIME in osteosarcoma, MRG-related gene clusters can well reflect changes in osteosarcoma TIME and predict chemotherapy and immunotherapy response. The metabolism-related risk model may serve as a useful prognostic predictor. ST3GAL4 plays a critical role in the progression, glycolysis, and TIME of osteosarcoma cells.

Phenylpropanoid-enriched broccoli seedling extract can reduce inflammatory markers and pain behavior

BACKGROUND

Pain is a worldwide problem requiring an effective, affordable, non-addictive therapy. Using the edible plant broccoli, a growth protocol was developed to induce a concentrated combinatorial of potential anti-inflammatories in seedlings.

METHODS

A growth method was utilized to produce a phenylpropanoid-rich broccoli sprout extract, referred to as Original Extract (OE). OE was concentrated and then resuspended for study of the effects on inflammation events. A rabbit disc model of inflammation and degeneration, and, a mouse model of pain behavior were used for in vivo and in vitro tests. To address aspects of mammalian metabolic processing, the OE was treated with the S9 liver microsome fraction derived from mouse, for use in a mouse in vivo study. Analytical chemistry was performed to identify major chemical species. Continuous variables were analyzed with a number of methods including ANOVA, and two-tailed t tests, as appropriate.

RESULTS

In a rabbit spine (disc) injury model, inflammatory markers were reduced, and levels of regenerative markers were increased as a result of OE treatment, both in vivo and in vitro. In a mouse pain behavioral model, after treatment with S9 liver microsome fraction, the resultant extract significantly reduced early and late pain behavior in response to a pain stimulus. The OE itself reduced pain behavior in the mouse pain model, but did not achieve the level of significance observed for S9-treated extract. Analytical chemistry undertaken on the extract constituents revealed identities of the chemical species in OE, and how S9 liver microsome fraction treatment altered species identities and proportions.

CONCLUSIONS

In vitro and in vivo results indicate that the OE, and S9-treated OE broccoli extracts are worthwhile materials to develop a non-opiate inflammation and pain-reducing treatment.

Fasting mimicking diet inhibits tumor-associated macrophage survival and pro-tumor function in hypoxia: implications for combination therapy with anti-angiogenic agent

BACKGROUND

Recent research shows that tumor-associated macrophages (TAMs) are the primary consumers of glucose in tumor tissue, surpassing that of tumor cells. Our previous studies revealed that inhibiting glucose uptake impairs the survival and tumor-promoting function of hypoxic TAMs, suggesting that glucose reduction by energy restriction (calorie restriction or short-term fasting) may has a significant impact on TAMs. The purpose of this study is to verify the effect of fasting-mimicking diet (FMD) on TAMs, and to determine whether FMD synergizes with anti-angiogenic drug apatinib via TAMs.

METHODS

The effect of FMD on TAMs and its synergistic effects with apatinib were observed using an orthotopic mouse breast cancer model. An in vitro cell model, utilizing M2 macrophages derived from THP-1 cell line, was intended to assess the effects of low glucose on TAMs under hypoxic and normoxic conditions. Bioinformatics was used to screen for potential mechanisms of action, which were then validated both in vivo and in vitro.

RESULTS

FMD significantly inhibit the pro-tumor function of TAMs in vivo and in vitro, with the inhibitory effect being more pronounced under hypoxic conditions. Additionally, the combination of FMD-mediated TAMs inhibition with apatinib results in synergistic anti-tumor activity. This effect is partially mediated by the downregulation of CCL8 expression and secretion by the mTOR-HIF-1α signaling pathway.

CONCLUSIONS

These results support further clinical combination studies of FMD and anti-angiogenic therapy as potential anti-tumor strategies.

FASN multi-omic characterization reveals metabolic heterogeneity in pancreatic and prostate adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) and prostate cancer (PCa) are among the most prevalent malignant tumors worldwide. There is now a comprehensive understanding of metabolic reprogramming as a hallmark of cancer. Fatty acid synthase (FASN) is a key regulator of the lipid metabolic network, providing energy to favor tumor proliferation and development. Whereas the biological role of FASN is known, its response and sensitivity to inhibition have not yet been fully established in these two cancer settings.

METHODS

To evaluate the association between FASN expression, methylation, prognosis, and mutational profile in PDAC and PCa, we interrogated public databases and surveyed online platforms using TCGA data. The STRING database was used to investigate FASN interactors, and the Gene Set Enrichment Analysis platform Reactome database was used to perform an enrichment analysis using data from RNA sequencing public databases of PDAC and PCa. In vitro models using PDAC and PCa cell lines were used to corroborate the expression of FASN, as shown by Western blot, and the effects of FASN inhibition on cell proliferation/cell cycle progression and mitochondrial respiration were investigated with MTT, colony formation assay, cell cycle analysis and MitoStress Test.

RESULTS

The expression of FASN was not modulated in PDAC compared to normal pancreatic tissues, while it was overexpressed in PCa, which also displayed a different level of promoter methylation. Based on tumor grade, FASN expression decreased in advanced stages of PDAC, but increased in PCa. A low incidence of FASN mutations was found for both tumors. FASN was overexpressed in PCa, despite not reaching statistical significance, and was associated with a worse prognosis than in PDAC. The biological role of FASN interactors correlated with lipid metabolism, and GSEA indicated that lipid-mediated mitochondrial respiration was enriched in PCa. Following validation of FASN overexpression in PCa compared to PDAC in vitro, we tested TVB-2640 as a FASN inhibitor. PCa proliferation arrest was modulated by FASN inhibition in a dose- and time-dependent manner, whereas PDAC proliferation was not altered. In line with this finding, mitochondrial respiration was found to be more affected in PCa than in PDAC. FASN inhibition interfered with metabolic signaling causing lipid accumulation and affecting cell viability with an impact on the replicative processes.

CONCLUSIONS

FASN exhibited differential expression patterns in PDAC and PCa, suggesting a different evolution during cancer progression. This was corroborated by the fact that both tumors responded differently to FASN inhibition in terms of proliferative potential and mitochondrial respiration, indicating that its use should reflect context specificity.

Combining bulk RNA-sequencing and single-cell RNA-sequencing data to reveal the immune microenvironment and metabolic pattern of osteosarcoma

Background: Osteosarcoma (OS) is a kind of solid tumor with high heterogeneity at tumor microenvironment (TME), genome and transcriptome level. In view of the regulatory effect of metabolism on TME, this study was based on four metabolic models to explore the intertumoral heterogeneity of OS at the RNA sequencing (RNA-seq) level and the intratumoral heterogeneity of OS at the bulk RNA-seq and single cell RNA-seq (scRNA-seq) level.

Methods: The GSVA package was used for single-sample gene set enrichment analysis (ssGSEA) analysis to obtain a glycolysis, pentose phosphate pathway (PPP), fatty acid oxidation (FAO) and glutaminolysis gene sets score. ConsensusClusterPlus was employed to cluster OS samples downloaded from the Target database. The scRNA-seq and bulk RNA-seq data of immune cells from GSE162454 dataset were analyzed to identify the subsets and types of immune cells in OS. Malignant cells and non-malignant cells were distinguished by large-scale chromosomal copy number variation. The correlations of metabolic molecular subtypes and immune cell types with four metabolic patterns, hypoxia and angiogenesis were determined by Pearson correlation analysis.

Results: Two metabolism-related molecular subtypes of OS, cluster 1 and cluster 2, were identified. Cluster 2 was associated with poor prognosis of OS, active glycolysis, FAO, glutaminolysis, and bad TME. The identified 28608 immune cells were divided into 15 separate clusters covering 6 types of immune cells. The enrichment scores of 5 kinds of immune cells in cluster-1 and cluster-2 were significantly different. And five kinds of immune cells were significantly correlated with four metabolic modes, hypoxia and angiogenesis. Of the 28,608 immune cells, 7617 were malignant cells. The four metabolic patterns of malignant cells were significantly positively correlated with hypoxia and negatively correlated with angiogenesis.

Conclusion: We used RNA-seq to reveal two molecular subtypes of OS with prognosis, metabolic pattern and TME, and determined the composition and metabolic heterogeneity of immune cells in OS tumor by bulk RNA-seq and single-cell RNA-seq.

Shilajit potentiates the effect of chemotherapeutic drugs and mitigates metastasis induced liver and kidney damages in osteosarcoma rats

Osteosarcoma is a primary malignant cancer of the bone identified by the direct formation of osteoid tissue or immature bone by cancer cells. The liver and kidneys represent two major secondary organs to which osteosarcoma metastasizes. In this study, we assessed Shilajit, a phytomineral diffusion traditionally used in Ayurvedic medicine, for its possible protective effects against metastasis induced liver and kidney damages in an osteosarcoma rat model. Osteosarcoma rats displayed typical dysregulation of serum levels of hepatic and renal functional markers (p < 0.05) including aspartate aminotransferase (AST)* and alanine aminotransferase (ALT), alkaline phosphatase (ALP), total proteins, albumin, bilirubin, creatinine, urea, and uric acid. Changes in functional markers were also positively correlated with marked histopathological alterations in liver and kidney tissues. Whereas Shilajit's treatment of osteosarcoma rates in combination with CMF (cyclophosphamide, methotrexate, and 5-fluorouracil) chemotherapy drug cocktail significantly (p < 0.05) reversed the studied functional markers to their near-normal levels. Co-treatment of shilajit and drug cocktails also markedly alleviated histopathological changes in liver and kidney tissues. Correlation co-efficient analysis of hepatic and renal functional markers revealed a significant inter-association among these markers. Collectively, present data indicate that shilajit may potentiate the effects of chemotherapy drugs and mitigate the metastasis-induced liver and kidney damage in osteosarcoma. Thus, the findings of this study substantiate the beneficial health effects of shilajit and promote its regular consumption.

Emerging Applications of Deep Learning in Bone Tumors: Current Advances and Challenges

Deep learning is a subfield of state-of-the-art artificial intelligence (AI) technology, and multiple deep learning-based AI models have been applied to musculoskeletal diseases. Deep learning has shown the capability to assist clinical diagnosis and prognosis prediction in a spectrum of musculoskeletal disorders, including fracture detection, cartilage and spinal lesions identification, and osteoarthritis severity assessment. Meanwhile, deep learning has also been extensively explored in diverse tumors such as prostate, breast, and lung cancers. Recently, the application of deep learning emerges in bone tumors. A growing number of deep learning models have demonstrated good performance in detection, segmentation, classification, volume calculation, grading, and assessment of tumor necrosis rate in primary and metastatic bone tumors based on both radiological (such as X-ray, CT, MRI, SPECT) and pathological images, implicating a potential for diagnosis assistance and prognosis prediction of deep learning in bone tumors. In this review, we first summarized the workflows of deep learning methods in medical images and the current applications of deep learning-based AI for diagnosis and prognosis prediction in bone tumors. Moreover, the current challenges in the implementation of the deep learning method and future perspectives in this field were extensively discussed.

Knowledge atlas and emerging trends on ncRNAs of osteosarcoma: A bibliometric analysis

BACKGROUND

Osteosarcoma is a common bone sarcoma that occurs in childhood and adolescence. Although research on non-coding RNAs (ncRNAs) of osteosarcoma has been developed rapidly in recent years, a specific bibliometric analysis on this topic has not yet been performed. The bibliometric analysis aims to summarize knowledge atlas, research hotspots, and emerging trends and to provide researchers with new perspectives in further studies.

METHODS

All publications regarding ncRNAs of osteosarcoma published from 2000 to 2021 were retrieved from the Web of Science Core Collection. Quantitative indicators including the number of publications and citations, H-index, and journal citation reports were analyzed by using Excel 2019 and R software. VOSviewer and CiteSpace were used to analyze the cooperation among countries/institutions/journals/authors and the co-occurrence of keywords, keywords bursts, and references.

RESULTS

A total of 3206 publications were extracted. A significant growth trend in the annual number of publications over the past 22 years is revealed (R ² = 0.999). The most prolific country and institution were China (2260) and Shanghai Jiao Tong University (134), respectively. Professors Wang W and Liu W contributed the most to this field. The keywords were stratified into six clusters: Cluster 1 (apoptosis and growth), Cluster 2 (cancer and progression), Cluster 3 (microRNAs and downregulation), Cluster 4 (genes and differentiation), Cluster 5 (expression and biological functions), and Cluster 6 (metastasis). The long non-coding RNAs and circular RNAs have been considered as an important research hotspot in the near future.

CONCLUSION

This study offers a scientific perspective on ncRNAs of osteosarcoma and provides researchers with valuable information to understand the knowledge structure and to identify emerging trends in this field.