Disruption of sugar nucleotide clearance is a therapeutic vulnerability of cancer cells

Predicting patient outcomes with gene-expression biomarkers from colorectal cancer organoids and cell lines

Introduction

Colorectal cancer (CRC) is characterized by an extremely high mortality rate, mainly caused by the high metastatic potential of this type of cancer. To date, chemotherapy remains the backbone of the treatment of metastatic colorectal cancer. Three main chemotherapeutic drugs used for the treatment of metastatic colorectal cancer are 5-fluorouracil, oxaliplatin and irinotecan which is metabolized to an active compound SN-38. The main goal of this study was to find the genes connected to the resistance to the aforementioned drugs and to construct a predictive gene expression-based classifier to separate responders and non-responders.

Methods

In this study, we analyzed gene expression profiles of seven patient-derived CRC organoids and performed correlation analyses between gene expression and IC50 values for the three standard-of-care chemotherapeutic drugs. We also included in the study publicly available datasets of colorectal cancer cell lines, thus combining two different in vitro models relevant to cancer research. Logistic regression was used to build gene expression-based classifiers for metastatic Stage IV and non-metastatic Stage II/III CRC patients. Prognostic performance was evaluated through Kaplan-Meier survival analysis and log-rank tests, while independent prognostic significance was assessed using multivariate Cox proportional hazards modeling.

Results

A small set of genes showed consistent correlation with resistance to chemotherapy across different datasets. While some genes were previously implicated in cancer prognosis and drug response, several were linked to drug resistance for the first time. The resulting gene expression signatures successfully stratified Stage II/III and Stage IV CRC patients, with potential clinical utility for improving treatment outcomes after further validation.

Discussion

This study highlights the advantages of integrating diverse experimental models, such as organoids and cell lines, to identify novel prognostic biomarkers and enhance the understanding of chemotherapy resistance in CRC.

Elucidating the role of pyrimidine metabolism in prostate cancer and its therapeutic implications

Our study aims to investigate the role of pyrimidine metabolism in prostate cancer and its associations with the immune microenvironment, drug sensitivity, and tumor mutation burden. Through transcriptomic and single-cell RNA sequencing analyses, we explored metabolic pathway enrichment, immune infiltration patterns, and differential gene expression in prostate cancer samples. The results showed that pyrimidine metabolism-related genes were significantly upregulated in the P2 subgroup compared to the P1 subgroup, with enhanced metabolic activity observed in basal and luminal epithelial cells. In addition, immune infiltration analysis revealed a strong correlation between pyrimidine metabolism and immune cell regulation, particularly involving T cell activity. Tumors in the P2 subgroup, characterized by higher pyrimidine metabolism, exhibited greater infiltration of activated CD4 + T cells and M2 macrophages, indicating a potential link between metabolic reprogramming and the immune response in prostate cancer. Drug sensitivity analysis further demonstrated that tumors with elevated pyrimidine metabolism displayed increased responsiveness to several chemotherapeutic agents, including BI-2536, JW-7-24-1, and PAC-1, suggesting that targeting pyrimidine metabolism may enhance treatment efficacy. Moreover, key genes involved in pyrimidine de novo synthesis, such as RRM2, were identified as potential drivers of tumor progression, providing new insights into the molecular mechanisms underlying aggressive prostate cancer phenotypes. In conclusion, pyrimidine metabolism plays a critical role in prostate cancer progression, influencing immune infiltration and drug sensitivity. Targeting this metabolic pathway offers a promising strategy for the development of new therapeutic approaches, particularly for overcoming drug resistance and improving outcomes in patients with advanced prostate cancer.

Integration of single-cell transcriptomics and bulk transcriptomics to explore prognostic and immunotherapeutic characteristics of nucleotide metabolism in lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is a highly aggressive tumor with one of the highest morbidity and mortality rates in the world. Nucleotide metabolic processes are critical for cancer development, progression, and alteration of the tumor microenvironment. However, the effect of nucleotide metabolism on LUAD remains to be thoroughly investigated.

Methods

Transcriptomic and clinical data of LUAD were downloaded and organized from TCGA and GEO databases. Genes related to nucleotide metabolism were downloaded from the Msigdb database. Genes associated with LUAD prognosis were identified using univariate COX analysis, and a prognostic risk model was constructed using the machine learning combination of Lasso + Stepcox. The model's predictive validity was evaluated using KM survival and timeROC curves. Based on the prognostic model, LUAD patients were classified into different nucleotide metabolism subtypes, and the differences between patients of different subtypes were explored in terms of genomic mutations, functional enrichment, tumor immune characteristics, and immunotherapy responses. Finally, the key gene SNRPA was screened, and a series of in vitro experiments were performed on LUAD cell lines to explore the role of SNRPA in LUAD.

Result

LUAD patients could be accurately categorized into subtypes based on the nucleotide metabolism-related prognostic risk score (NMBRS). There were significant differences in prognosis between patients of different subtypes, and the NMBRS showed high accuracy in predicting the prognosis of LUAD patients. In addition, patients of different subtypes showed significant differences in genomic mutation and functional enrichment and exhibited different anti-tumor immune profiles. Importantly, NMBRS can be used to predict the responsiveness of LUAD patients to immunotherapy. The results of in vitro cellular experiments indicate that SNRPA plays an important role in the development and progression of lung adenocarcinoma.

Conclusion

This study comprehensively reveals the prognostic value and clinical application of nucleotide metabolism in LUAD. A prognostic signature constructed based on genes related to nucleotide metabolism accurately predicted the prognosis of LUAD patients, and this signature can be used as a guide for LUAD immunotherapy.

Metabolic Atlas of Human Eyelid Infiltrative Basal Cell Carcinoma

Purpose

Eyelid infiltrative basal cell carcinoma (iBCC) is the most common malignant tumor affecting the ocular adnexa, but studies on metabolic changes within its microenvironment and heterogeneity at the tumor invasive area are limited. This study aims to analyze metabolic differences among iBCC cell types using single-cell and spatial metabolomics analysis and to examine metabolic environment at the tumor invasive area.

Methods

Single-cell transcriptomic data of human basal cell carcinoma (BCC) were clustered and visualized using Uniform Manifold Approximation and Projection. Metabolic reprogramming was analyzed with single-cell flux estimation analysis. Spatial metabolomics data were obtained with the Timstof Flex MALDI 2 system, and Bruker software was used for region selection.

Results

Eight cell types were identified within the iBCC microenvironment. Differences between inflammatory cancer-associated fibroblasts and myofibroblastic cancer-associated fibroblasts were analyzed. Metabolic flux analysis showed increased glycolysis, glutamine, heme, and glutathione fluxes in the iBCC microenvironment. Spatial metabolomics revealed high levels of taurine, deoxy-GMP, O-phosphoethanolamine, and pyrithione. Both tumor and invasive regions had significant upregulation of fatty acid pathways, with marked increases in oleic and arachidonic acids at the invasive area. Specific upregulation of UDP-glucuronic acid and high UDP-glucose 6-dehydrogenase (UGDH) expression in the tumor region suggest UXS1 as a potential therapeutic target for iBCC.

Conclusions

This study establishes a metabolic microenvironment atlas of iBCC, revealing significant metabolic differences and the dominance of lipid and lysosome metabolism. Potential metabolic markers and characteristic substances in the invasive area offer new insights for immunotherapy and the exploration of BCC's metabolic mechanisms.

Harnessing Gene Editing Technology for Tumor Microenvironment Modulation: An Emerging Anticancer Strategy

Cancer is a multifaceted disease influenced by both intrinsic cellular traits and extrinsic factors, with the tumor microenvironment (TME) being crucial for cancer progression. To satisfy their high proliferation and aggressiveness, cancer cells always plunder large amounts of nutrients and release various signals to their surroundings, forming a dynamic TME with special metabolic, immune, microbial and physical characteristics. Due to the neglect of interactions between tumor cells and the TME, traditional cancer therapies often struggle with challenges such as drug resistance, low efficacy, and recurrence. Importantly, the development of gene editing technologies, particularly the CRISPR-Cas system, offers promising new strategies for cancer treatment. Combined with nanomaterial strategies, CRISPR-Cas technology exhibits precision, affordability, and user-friendliness with reduced side effects, which holds great promise for profoundly altering the TME at the genetic level, potentially leading to lasting anticancer outcomes. This review will delve into how CRISPR-Cas can be leveraged to manipulate the TME, examining its potential as a transformative anticancer therapy.

Metabolomic Analysis of Histological Composition Variability of High-Grade Serous Ovarian Cancer Using 1H HR MAS NMR Spectroscopy

In this work, the HR MAS NMR (high-resolution magic-angle spinning nuclear magnetic resonance) spectroscopy technique was combined with standard histological examinations to investigate the metabolic features of high-grade serous ovarian cancer (HGSOC) with a special focus on the relation between a metabolic profile and a cancer cell fraction. The studied group consisted of 44 patients with HGSOC and 18 patients with benign ovarian tumors. Normal ovarian tissue was also excised from 13 control patients. The metabolic profiles of 138 tissue specimens were acquired on a Bruker Avance III 400 MHz spectrometer. The NMR spectra of the HGSOC samples could be discriminated from those acquired from the non-transformed tissue and were shown to depend on tumor purity. The most important features that differentiate the samples with a high fraction of cancer cells from the samples containing mainly fibrotic stroma are the increased intensities in the spectral regions corresponding to phosphocholine/glycerophosphocholine, phosphoethanolamine/serine, threonine, uridine nucleotides and/or uridine diphosphate (UDP) nucleotide sugars. Higher levels of glutamine, glutamate, acetate, lysine, alanine, leucine and isoleucine were detected in the desmoplastic stroma within the HGSOC lesions compared to the stroma of benign tumors. The HR MAS NMR analysis of the metabolic composition of the epithelial and stromal compartments within HGSOC contributes to a better understanding of the disease's biology.

Targeting hyaluronan metabolism-related molecules associated with resistant tumor-initiating cells potentiates chemotherapy efficacy in lung cancer

The success of chemotherapy regimens in patients with non-small cell lung cancer (NSCLC) could be restricted at least in part by cancer stem cells (CSC) niches within the tumor microenvironment (TME). CSC express CD133, CD44, CD47, and SOX2, among other markers and factors. Analysis of public data revealed that high expression of hyaluronan (HA), the main glycosaminoglycan of TME, correlated positively with CSC phenotype and decreased disease-free interval in NSCLC patients. We aimed to cross-validate these findings on human and murine lung cancer cells and observed that CD133 + CSC differentially expressed higher levels of HA, HAS3, ABCC5, SOX2, and CD47 (p < 0.01). We modulated HA expression with 4-methylumbelliferone (4Mu) and detected an increase in sensitivity to paclitaxel (Pa). We evaluated the effect of 4Mu + chemotherapy on survival, HA metabolism, and CSC profile. The combination of 4Mu with Pa reduced the clonogenic and tumor-forming ability of CSC. Pa-induced HAS3, ABCC5, SOX2, and CD47 expression was mitigated by 4Mu. Pa + 4Mu combination significantly reduced in vivo tumor growth, enhancing animal survival and restoring the CSC profile in the TME to basal levels. Our results suggest that HA is involved in lung CSC phenotype and chemosensitivity, and its modulation by 4Mu improves treatment efficacy to inhibit tumor progression.

HiChIP-Based Epigenomic Footprinting Identifies a Promoter Variant of UXS1 That Confers Genetic Susceptibility to Gastroesophageal Cancer

Genome-wide association studies (GWAS) have identified more than a hundred single nucleotide variants (SNV) associated with the risk of gastroesophageal cancer (GEC). The majority of the identified SNVs map to noncoding regions of the genome. Uncovering the causal SNVs and genes they modulate could help improve GEC prevention and treatment. Herein, we used HiChIP against histone 3 lysine 27 acetylation (H3K27ac) to simultaneously annotate active promoters and enhancers, identify the interactions between them, and detect nucleosome-free regions (NFR) harboring potential causal SNVs in a single assay. The application of H3K27ac HiChIP in GEC relevant models identified 61 potential functional SNVs that reside in NFRs and interact with 49 genes at 17 loci. The approach led to a 67% reduction in the number of SNVs in linkage disequilibrium at these 17 loci, and at 7 loci, a single putative causal SNV was identified. One SNV, rs147518036, located within the promoter of the UDP-glucuronate decarboxylase 1 (UXS1) gene, seemed to underlie the GEC risk association captured by the rs75460256 index SNV. The rs147518036 SNV creates a GABPA DNA recognition motif, resulting in increased promoter activity, and CRISPR-mediated inhibition of the UXS1 promoter reduced the viability of the GEC cells. These findings provide a framework that simplifies the identification of potentially functional regulatory SNVs and target genes underlying risk-associated loci. In addition, the study implicates increased expression of the enzyme UXS1 and activation of its metabolic pathway as a predisposition to gastric cancer, which highlights potential therapeutic avenues to treat this disease. Significance: Epigenomic footprinting using a histone posttranslational modification targeted 3D genomics methodology elucidates functional noncoding sequence variants and their target genes at cancer risk loci.

Generation of a biliary tract cancer cell line atlas reveals molecular subtypes and therapeutic targets

Biliary tract cancers (BTCs) are a group of deadly malignancies encompassing intrahepatic and extrahepatic cholangiocarcinoma, gallbladder carcinoma, and ampullary carcinoma. Here, we present the integrative analysis of 63 BTC cell lines via multi-omics clustering and genome- scale CRISPR screens, providing a platform to illuminate BTC biology and inform therapeutic development. We identify dependencies broadly enriched in BTC compared to other cancers as well as dependencies selective to the anatomic subtypes. Notably, cholangiocarcinoma cell lines are stratified into distinct lineage subtypes based on biliary or dual biliary/hepatocyte marker signatures, associated with dependency on specific lineage survival factors. Transcriptional analysis of patient specimens demonstrates the prognostic significance of these lineage subtypes. Additionally, we delineate strategies to enhance targeted therapies or to overcome resistance in cell lines with key driver gene mutations. Furthermore, clustering based on dependencies and proteomics data elucidates unexpected functional relationships, including a BTC subgroup with partial squamous differentiation. Thus, this cell line atlas reveals potential therapeutic targets in molecularly defined BTCs, unveils biologically distinct disease subtypes, and offers a vital resource for BTC research.

Metabolomic profiling of upper GI malignancies in blood and tissue: a systematic review and meta-analysis

OBJECTIVE

To conduct a systematic review and meta-analysis of case-control and cohort human studies evaluating metabolite markers identified using high-throughput metabolomics techniques on esophageal cancer (EC), cancer of the gastroesophageal junction (GEJ), and gastric cancer (GC) in blood and tissue.

BACKGROUND

Upper gastrointestinal cancers (UGC), predominantly EC, GEJ, and GC, are malignant tumour types with high morbidity and mortality rates. Numerous studies have focused on metabolomic profiling of UGC in recent years. In this systematic review and meta-analysis, we have provided a collective summary of previous findings on metabolites and metabolomic profiling associated with EC, GEJ and GC.

METHODS

Following the PRISMA procedure, a systematic search of four databases (Embase, PubMed, MEDLINE, and Web of Science) for molecular epidemiologic studies on the metabolomic profiles of EC, GEJ and GC was conducted and registered at PROSPERO (CRD42023486631). The Newcastle-Ottawa Scale (NOS) was used to benchmark the risk of bias for case-controlled and cohort studies. QUADOMICS, an adaptation of the QUADAS-2 (Quality Assessment of Diagnostic Accuracy) tool, was used to rate diagnostic accuracy studies. Original articles comparing metabolite patterns between patients with and without UGC were included. Two investigators independently completed title and abstract screening, data extraction, and quality evaluation. Meta-analysis was conducted whenever possible. We used a random effects model to investigate the association between metabolite levels and UGC.

RESULTS

A total of 66 original studies involving 7267 patients that met the required criteria were included for review. 169 metabolites were differentially distributed in patients with UGC compared to healthy patients among 44 GC, 9 GEJ, and 25 EC studies including metabolites involved in glycolysis, anaerobic respiration, tricarboxylic acid cycle, and lipid metabolism. Phosphatidylcholines, eicosanoids, and adenosine triphosphate were among the most frequently reported lipids and metabolites of cellular respiration, while BCAA, lysine, and asparagine were among the most commonly reported amino acids. Previously identified lipid metabolites included saturated and unsaturated free fatty acids and ketones. However, the key findings across studies have been inconsistent, possibly due to limited sample sizes and the majority being hospital-based case-control analyses lacking an independent replication group.

CONCLUSION

Thus far, metabolomic studies have provided new opportunities for screening, etiological factors, and biomarkers for UGC, supporting the potential of applying metabolomic profiling in early cancer diagnosis. According to the results of our meta-analysis especially BCAA and TMAO as well as certain phosphatidylcholines should be implicated into the diagnostic procedure of patients with UGC. We envision that metabolomics will significantly enhance our understanding of the carcinogenesis and progression process of UGC and may eventually facilitate precise oncological and patient-tailored management of UGC.

Metabolic Signaling in Cancer Metastasis

Metastases, which are the leading cause of death in patients with cancer, have metabolic vulnerabilities. Alterations in metabolism fuel the energy and biosynthetic needs of metastases but are also needed to activate cell state switches in cells leading to invasion, migration, colonization, and outgrowth in distant organs. Specifically, metabolites can activate protein kinases as well as receptors and they are crucial substrates for posttranslational modifications on histone and nonhistone proteins. Moreover, metabolic enzymes can have moonlighting functions by acting catalytically, mainly as protein kinases, or noncatalytically through protein-protein interactions. Here, we summarize the current knowledge on metabolic signaling in cancer metastasis.

SIGNIFICANCE

Effective drugs for the prevention and treatment of metastases will have an immediate impact on patient survival. To overcome the current lack of such drugs, a better understanding of the molecular processes that are an Achilles heel in metastasizing cancer cells is needed. One emerging opportunity is the metabolic changes cancer cells need to undergo to successfully metastasize and grow in distant organs. Mechanistically, these metabolic changes not only fulfill energy and biomass demands, which are often in common between cancer and normal but fast proliferating cells, but also metabolic signaling which enables the cell state changes that are particularly important for the metastasizing cancer cells.

SPTBN2 suppresses ferroptosis in NSCLC cells by facilitating SLC7A11 membrane trafficking and localization

The function of SLC7A11 in the process of ferroptosis is well-established, as it regulates the synthesis of glutathione (GSH), thereby influencing tumor development along with drug resistance in non-small cell lung cancer (NSCLC). However, the determinants governing SLC7A11's membrane trafficking and localization remain unknown. Our study identified SPTBN2 as a ferroptosis suppressor, enhancing NSCLC cells resistance to ferroptosis inducers. Mechanistically, SPTBN2, through its CH domain, interacted with SLC7A11 and connected it with the motor protein Arp1, thus facilitating the membrane localization of SLC7A11 - a prerequisite for its role as System Xc-, which mediates cystine uptake and GSH synthesis. Consequently, SPTBN2 suppressed ferroptosis through preserving the functional activity of System Xc- on the membrane. Moreover, Inhibiting SPTBN2 increased the sensitivity of NSCLC cells to cisplatin through ferroptosis induction, both in vitro and in vivo. Using Abrine as a potential SPTBN2 inhibitor, its efficacy in promoting ferroptosis and sensitizing NSCLC cells to cisplatin was validated. Collectively, SPTBN2 is a potential therapeutic target for addressing ferroptosis dysfunction and cisplatin resistance in NSCLC.

Recent advances in nanomedicine for metabolism-targeted cancer therapy

Metabolism denotes the sum of biochemical reactions that maintain cellular function. Different from most normal differentiated cells, cancer cells adopt altered metabolic pathways to support malignant properties. Typically, almost all cancer cells need a large number of proteins, lipids, nucleotides, and energy in the form of ATP to support rapid division. Therefore, targeting tumour metabolism has been suggested as a generic and effective therapy strategy. With the rapid development of nanotechnology, nanomedicine promises to have a revolutionary impact on clinical cancer therapy due to many merits such as targeting, improved bioavailability, controllable drug release, and potentially personalized treatment compared to conventional drugs. This review comprehensively elucidates recent advances of nanomedicine in targeting important metabolites such as glucose, glutamine, lactate, cholesterol, and nucleotide for effective cancer therapy. Furthermore, the challenges and future development in this area are also discussed.