Association Between Plasma Diacetylspermine and Tumor Spermine Synthase With Outcome in Triple-Negative Breast Cancer

Unveiling the hidden players: noncoding RNAs orchestrating polyamine metabolism in disease

Polyamines (PA) are polycations with pleiotropic functions in cellular physiology and pathology. In particular, PA have been involved in the regulation of cell homeostasis and proliferation participating in the control of fundamental processes like DNA transcription, RNA translation, protein hypusination, autophagy and modulation of ion channels. Indeed, their dysregulation has been associated to inflammation, oxidative stress, neurodegeneration and cancer progression. Accordingly, PA intracellular levels, derived from the balance between uptake, biosynthesis, and catabolism, need to be tightly regulated. Among the mechanisms that fine-tune PA metabolic enzymes, emerging findings highlight the importance of noncoding RNAs (ncRNAs). Among the ncRNAs, microRNA, long noncoding RNA and circRNA are the most studied as regulators of gene expression and mRNA metabolism and their alteration have been frequently reported in pathological conditions, such as cancer progression and brain diseases. In this review, we will discuss the role of ncRNAs in the regulation of PA genes, with a particular emphasis on the changes of this modulation observed in health disorders.

Characterization of polyamine metabolism predicts prognosis, immune profile, and therapeutic efficacy in lung adenocarcinoma patients

Background

Polyamine modification patterns in lung adenocarcinoma (LUAD) and their impact on prognosis, immune infiltration, and anti-tumor efficacy have not been systematically explored.

Methods

Patients from The Cancer Genome Atlas (TCGA) were classified into subtypes according to polyamine metabolism-related genes using the consensus clustering method, and the survival outcomes and immune profile were compared. Meanwhile, the geneCluster was constructed according to the differentially expressed genes (DEGs) of the subtypes. Subsequently, the polyamine metabolism-related score (PMRS) system was established using the least absolute shrinkage and selection operator (LASSO) multivariate regression analysis in the TCGA training cohort (n = 245), which can be applied to characterize the prognosis. To verify the predictive performance of the PMRS, the internal cohort (n = 245) and the external cohort (n = 244) were recruited. The relationship between the PMRS and immune infiltration and antitumor responses was investigated.

Results

Two distinct patterns (C1 and C2) were identified, in which the C1 subtype presented an adverse prognosis, high CD8+ T cell infiltration, tumor mutational burden (TMB), immune checkpoint, and low tumor immune dysfunction and exclusion (TIDE). Furthermore, two geneClusters were established, and similar findings were observed. The PMRS, including three genes (SMS, SMOX, and PSMC6), was then constructed to characterize the polyamine metabolic patterns, and the patients were divided into high- and low-PMRS groups. As confirmed by the validation cohort, the high-PMRS group possessed a poor prognosis. Moreover, external samples and immunohistochemistry confirmed that the three genes were highly expressed in tumor samples. Finally, immunotherapy and chemotherapy may be beneficial to the high-PMRS group based on the immunotherapy cohorts and low half-maximal inhibitory concentration (IC50) values.

Conclusion

We identified distinct polyamine modification patterns and established a PMRS to provide new insights into the mechanism of polyamine action and improve the current anti-tumor strategy of LUAD.

Cancer screening with multicancer detection tests: A translational science review

Multicancer detection (MCD) tests use a single, easily obtainable biospecimen, such as blood, to screen for more than one cancer concurrently. MCD tests can potentially be used to improve early cancer detection, including cancers that currently lack effective screening methods. However, these tests have unknown and unquantified benefits and harms. MCD tests differ from conventional cancer screening tests in that the organ responsible for a positive test is unknown, and a broad diagnostic workup may be necessary to confirm the location and type of underlying cancer. Among two prospective studies involving greater than 16,000 individuals, MCD tests identified those who had some cancers without currently recommended screening tests, including pancreas, ovary, liver, uterus, small intestine, oropharyngeal, bone, thyroid, and hematologic malignancies, at early stages. Reported MCD test sensitivities range from 27% to 95% but differ by organ and are lower for early stage cancers, for which treatment toxicity would be lowest and the potential for cure might be highest. False reassurance from a negative MCD result may reduce screening adherence, risking a loss in proven public health benefits from standard-of-care screening. Prospective clinical trials are needed to address uncertainties about MCD accuracy to detect different cancers in asymptomatic individuals, whether these tests can detect cancer sufficiently early for effective treatment and mortality reduction, the degree to which these tests may contribute to cancer overdiagnosis and overtreatment, whether MCD tests work equally well across all populations, and the appropriate diagnostic evaluation and follow-up for patients with a positive test.

Comprehensive investigation into the influence of glycosylation on head and neck squamous cell carcinoma and development of a prognostic model for risk assessment and anticipating immunotherapy

Background

It has been well established that glycosylation plays a pivotal role in initiation, progression, and therapy resistance of several cancers. However, the correlations between glycosylation and head and neck squamous cell carcinoma (HNSCC) have not been elucidated in detail.

Methods

The paramount genes governing glycosylation were discerned via the utilization of the Protein-Protein Interaction (PPI) network and correlation analysis, coupled with single-cell RNA sequencing (scRNA-seq) analysis. To construct risk models exhibiting heightened predictive efficacy, cox- and lasso-regression methodologies were employed, and the veracity of these models was substantiated across both internal and external datasets. Subsequently, an exploration into the distinctions within the tumor microenvironment (TME), immunotherapy responses, and enriched pathways among disparate risk cohorts ensued. Ultimately, cell experiments were conducted to validate the consequential impact of SMS in Head and Neck Squamous Cell Carcinoma (HNSCC).

Results

A total of 184 genes orchestrating glycosylation were delineated for subsequent scrutiny. Employing cox- and lasso-regression methodologies, we fashioned a 3-gene signature, proficient in prognosticating the outcomes for patients afflicted with HNSCC. Noteworthy observations encompassed distinctions in the Tumor Microenvironment (TME), levels of immune cell infiltration, and the presence of immune checkpoint markers among divergent risk cohorts, holding potentially consequential implications for the clinical management of HNSCC patients.

Conclusion

The prognosis of HNSCC can be proficiently anticipated through risk signatures based on Glycosylation-related genes (GRGs). A thorough delineation of the GRGs signature in HNSCC holds the potential to facilitate the interpretation of HNSCC's responsiveness to immunotherapy and provide innovative strategies for cancer treatment.

Metabolomics and triple-negative breast cancer: A systematic review

Triple-negative breast cancer stands out as the most aggressive subtype of breast malignancy and is characterized by an unfavourable prognosis. Objective: This systematic review summarizes the insights gleaned from metabolomic analyses of individuals afflicted with this cancer variant. The overarching goal was to delineate the molecular alterations associated with triple-negative breast cancer, pinpointing potential therapeutic targets and novel biomarkers. Methods: We systematically searched for evidence using the PubMed database and followed the PRISMA and STARLITE guidelines. The search parameters were delimited to articles published within the last 13 years. Results: From an initial pool of 148 scrutinized articles, 17 studies involving 1686 participants were deemed eligible for inclusion. The current body of research shows a paucity of studies, and the available evidence presents conflicting outcomes. Notwithstanding, Pathway Enrichment Analysis identified the urea and glucose-alanine cycles as the most affected metabolic pathways, followed by arginine, proline, and aspartate metabolism. Conclusion: Future investigations need to focus on elucidating which of those metabolites and/or pathways might be reliable candidates for novel therapeutic interventions or reliable biomarkers for diagnosis and prognosis of this subtype of breast cancer.

Polyamines: their significance for maintaining health and contributing to diseases

Polyamines are essential for the growth and proliferation of mammalian cells and are intimately involved in biological mechanisms such as DNA replication, RNA transcription, protein synthesis, and post-translational modification. These mechanisms regulate cellular proliferation, differentiation, programmed cell death, and the formation of tumors. Several studies have confirmed the positive effect of polyamines on the maintenance of health, while others have demonstrated that their activity may promote the occurrence and progression of diseases. This review examines a variety of topics, such as polyamine source and metabolism, including metabolism, transport, and the potential impact of polyamines on health and disease. In addition, a brief summary of the effects of oncogenes and signaling pathways on tumor polyamine metabolism is provided. Video Abstract.

Modulating a prebiotic food source influences inflammation and immune-regulating gut microbes and metabolites: insights from the BE GONE trial

BACKGROUND

Accessible prebiotic foods hold strong potential to jointly target gut health and metabolic health in high-risk patients. The BE GONE trial targeted the gut microbiota of obese surveillance patients with a history of colorectal neoplasia through a straightforward bean intervention.

METHODS

This low-risk, non-invasive dietary intervention trial was conducted at MD Anderson Cancer Center (Houston, TX, USA). Following a 4-week equilibration, patients were randomized to continue their usual diet without beans (control) or to add a daily cup of study beans to their usual diet (intervention) with immediate crossover at 8-weeks. Stool and fasting blood were collected every 4 weeks to assess the primary outcome of intra and inter-individual changes in the gut microbiome and in circulating markers and metabolites within 8 weeks. This study was registered on ClinicalTrials.gov as NCT02843425, recruitment is complete and long-term follow-up continues.

FINDINGS

Of the 55 patients randomized by intervention sequence, 87% completed the 16-week trial, demonstrating an increase on-intervention in diversity [n = 48; linear mixed effect and 95% CI for inverse Simpson index: 0.16 (0.02, 0.30); p = 0.02] and shifts in multiple bacteria indicative of prebiotic efficacy, including increased Faecalibacterium, Eubacterium and Bifidobacterium (all p < 0.05). The circulating metabolome showed parallel shifts in nutrient and microbiome-derived metabolites, including increased pipecolic acid and decreased indole (all p < 0.002) that regressed upon returning to the usual diet. No significant changes were observed in circulating lipoproteins within 8 weeks; however, proteomic biomarkers of intestinal and systemic inflammatory response, fibroblast-growth factor-19 increased, and interleukin-10 receptor-α decreased (p = 0.01).

INTERPRETATION

These findings underscore the prebiotic and potential therapeutic role of beans to enhance the gut microbiome and to regulate host markers associated with metabolic obesity and colorectal cancer, while further emphasizing the need for consistent and sustainable dietary adjustments in high-risk patients.

FUNDING

This study was funded by the American Cancer Society.

Blood-based Proteomic Signatures Associated With MEN1-related Duodenopancreatic Neuroendocrine Tumor Progression

PURPOSE

Patients with multiple endocrine neoplasia type 1 (MEN1) are predisposed to develop duodenopancreatic neuroendocrine tumors (dpNETs), and metastatic dpNET is the primary cause of disease-related mortality. Presently, there is a paucity of prognostic factors that can reliably identify patients with MEN1-related dpNETS who are at high risk of distant metastasis. In the current study, we aimed to establish novel circulating molecular protein signatures associated with disease progression.

EXPERIMENTAL DESIGN

Mass spectrometry-based proteomic profiling was conducted on plasmas procured through an international collaboration between MD Anderson Cancer Center, the National Institutes of Health, and the University Medical Center Utrecht from a cohort of 56 patients with MEN1 [14 with distant metastasis dpNETs (cases) and 42 with either indolent dpNETs or no dpNETs (controls)]. Findings were compared to proteomic profiles generated from serially collected plasmas from a mouse model of Men1-pancreatic neuroendocrine tumors (Men1fl/flPdx1-CreTg) and control mice (Men1fl/fl).

RESULTS

A total of 187 proteins were found to be elevated in MEN1 patients with distant metastasis compared to controls, including 9 proteins previously associated with pancreatic cancer and other neuronal proteins. Analyses of mouse plasmas revealed 196 proteins enriched for transcriptional targets of oncogenic MYCN, YAP1, POU5F1, and SMAD that were associated with disease progression in Men1fl/flPdx1-CreTg mice. Cross-species intersection revealed 19 proteins positively associated with disease progression in both human patients and in Men1fl/flPdx1-CreTg mice.

CONCLUSIONS

Our integrated analyses identified novel circulating protein markers associated with disease progression in MEN1-related dpNET.

Survival analysis of patient groups defined by unsupervised machine learning clustering methods based on patient metabolomic data

Purpose

Meta-analyses failed to accurately identify patients with non-metastatic breast cancer who are likely to benefit from chemotherapy, and metabolomics could provide new answers. In our previous published work, patients were clustered using five different unsupervised machine learning (ML) methods resulting in the identification of three clusters with distinct clinical and simulated survival data. The objective of this study was to evaluate the survival outcomes, with extended follow-up, using the same 5 different methods of unsupervised machine learning.

Experimental design

Forty-nine patients, diagnosed between 2013 and 2016, with non-metastatic BC were included retrospectively. Median follow-up was extended to 85.8 months. 449 metabolites were extracted from tumor resection samples by combined Liquid chromatography-mass spectrometry (LC-MS). Survival analyses were reported grouping together Cluster 1 and 2 versus cluster 3. Bootstrap optimization was applied.

Results

PCA k-means, K-sparse and Spectral clustering were the most effective methods to predict 2-year progression-free survival with bootstrap optimization (PFSb); as bootstrap example, with PCA k-means method, PFSb were 94% for cluster 1&2 versus 82% for cluster 3 (p = 0.01). PCA k-means method performed best, with higher reproducibility (mean HR=2 (95%CI [1.4-2.7]); probability of p ≤ 0.05 85%). Cancer-specific survival (CSS) and overall survival (OS) analyses highlighted a discrepancy between the 5 ML unsupervised methods.

Conclusion

Our study is a proof-of-principle that it is possible to use unsupervised ML methods on metabolomic data to predict PFS survival outcomes, with the best performance for PCA k-means. A larger population study is needed to draw conclusions from CSS and OS analyses.

A blood-based metabolomic signature predictive of risk for pancreatic cancer

Emerging evidence implicates microbiome involvement in the development of pancreatic cancer (PaCa). Here, we investigate whether increases in circulating microbial-related metabolites associate with PaCa risk by applying metabolomics profiling to 172 sera collected within 5 years prior to PaCa diagnosis and 863 matched non-subject sera from participants in the Prostate, Lung, Colorectal, and Ovarian (PLCO) cohort. We develop a three-marker microbial-related metabolite panel to assess 5-year risk of PaCa. The addition of five non-microbial metabolites further improves 5-year risk prediction of PaCa. The combined metabolite panel complements CA19-9, and individuals with a combined metabolite panel + CA19-9 score in the top 2.5th percentile have absolute 5-year risk estimates of >13%. The risk prediction model based on circulating microbial and non-microbial metabolites provides a potential tool to identify individuals at high risk of PaCa that would benefit from surveillance and/or from potential cancer interception strategies.

Integrated spatial transcriptomics and lipidomics of precursor lesions of pancreatic cancer identifies enrichment of long chain sulfatide biosynthesis as an early metabolic alteration

Background

The development of diverse spatial profiling technologies has provided an unprecedented insight into molecular mechanisms driving cancer pathogenesis. Here, we conducted the first integrated cross-species assessment of spatial transcriptomics and spatial metabolomics alterations associated with progression of intraductal papillary mucinous neoplasms (IPMN), bona fide cystic precursors of pancreatic ductal adenocarcinoma (PDAC).

Methods

Matrix Assisted Laster Desorption/Ionization (MALDI) mass spectrometry (MS)-based spatial imaging and Visium spatial transcriptomics (ST) (10X Genomics) was performed on human resected IPMN tissues (N= 23) as well as pancreata from a mutant Kras;Gnas mouse model of IPMN. Findings were further compared with lipidomic analyses of cystic fluid from 89 patients with histologically confirmed IPMNs, as well as single-cell and bulk transcriptomic data of PDAC and normal tissues.

Results

MALDI-MS analyses of IPMN tissues revealed long-chain hydroxylated sulfatides, particularly the C24:0(OH) and C24:1(OH) species, to be selectively enriched in the IPMN and PDAC neoplastic epithelium. Integrated ST analyses confirmed that the cognate transcripts engaged in sulfatide biosynthesis, including UGT8, Gal3St1 , and FA2H , were co-localized with areas of sulfatide enrichment. Lipidomic analyses of cystic fluid identified several sulfatide species, including the C24:0(OH) and C24:1(OH) species, to be significantly elevated in patients with IPMN/PDAC compared to those with low-grade IPMN. Targeting of sulfatide metabolism via the selective galactosylceramide synthase inhibitor, UGT8-IN-1, resulted in ceramide-induced lethal mitophagy and subsequent cancer cell death in vitro , and attenuated tumor growth of mutant Kras;Gnas allografts. Transcript levels of UGT8 and FA2H were also selectively enriched in PDAC transcriptomic datasets compared to non-cancerous areas, and elevated tumoral UGT8 was prognostic for poor overall survival.

Conclusion

Enhanced sulfatide metabolism is an early metabolic alteration in cystic pre-cancerous lesions of the pancreas that persists through invasive neoplasia. Targeting sulfatide biosynthesis might represent an actionable vulnerability for cancer interception.

17β-estradiol promotes extracellular vesicle release and selective miRNA loading in ERα-positive breast cancer

The causes and consequences of abnormal biogenesis of extracellular vesicles (EVs) are not yet well understood in malignancies, including in breast cancers (BCs). Given the hormonal signaling dependence of estrogen receptor-positive (ER+) BC, we hypothesized that 17β-estradiol (estrogen) might influence EV production and microRNA (miRNA) loading. We report that physiological doses of 17β-estradiol promote EV secretion specifically from ER+ BC cells via inhibition of miR-149-5p, hindering its regulatory activity on SP1, a transcription factor that regulates the EV biogenesis factor nSMase2. Additionally, miR-149-5p downregulation promotes hnRNPA1 expression, responsible for the loading of let-7's miRNAs into EVs. In multiple patient cohorts, we observed increased levels of let-7a-5p and let-7d-5p in EVs derived from the blood of premenopausal ER+ BC patients, and elevated EV levels in patients with high BMI, both conditions associated with higher levels of 17β-estradiol. In brief, we identified a unique estrogen-driven mechanism by which ER+ BC cells eliminate tumor suppressor miRNAs in EVs, with effects on modulating tumor-associated macrophages in the microenvironment.

ATP13A4 Upregulation Drives the Elevated Polyamine Transport System in the Breast Cancer Cell Line MCF7

Polyamine homeostasis is disturbed in several human diseases, including cancer, which is hallmarked by increased intracellular polyamine levels and an upregulated polyamine transport system (PTS). Thus far, the polyamine transporters contributing to the elevated levels of polyamines in cancer cells have not yet been described, despite the fact that polyamine transport inhibitors are considered for cancer therapy. Here, we tested whether the upregulation of candidate polyamine transporters of the P5B transport ATPase family is responsible for the increased PTS in the well-studied breast cancer cell line MCF7 compared to the non-tumorigenic epithelial breast cell line MCF10A. We found that MCF7 cells presented elevated expression of a previously uncharacterized P5B-ATPase, ATP13A4, which was responsible for the elevated polyamine uptake activity. Furthermore, MCF7 cells were more sensitive to polyamine cytotoxicity, as demonstrated by cell viability, cell death and clonogenic assays. Importantly, the overexpression of ATP13A4 WT in MCF10A cells induced a MCF7 polyamine phenotype, with significantly higher uptake of BODIPY-labeled polyamines and increased sensitivity to polyamine toxicity. In conclusion, we established ATP13A4 as a new polyamine transporter in the human PTS and showed that ATP13A4 may play a major role in the increased polyamine uptake of breast cancer cells. ATP13A4 therefore emerges as a candidate therapeutic target for anticancer drugs that block the PTS.

Analysis of the prognostic significance and potential mechanisms of lncRNAs related to m6A methylation in laryngeal cancer

Objective to investigate the prognostic significance and potential mechanism analysis of m6A methylation-associated lncRNAs in laryngeal cancer. Methods based on the expression of m6A-associated lncRNAs, the samples were divided into two clusters and least absolute value and selection operator (LASSO) regression analysis was performed to build and validate prognostic models. In addition, the relationships between risk scores, clusters, arginine synthase (SMS), tumor microenvironment, clinicopathological features, immune infiltration, immune checkpoints, and tumor mutation burden were analyzed. Finally, the relationship between SMS and m6A-associated IncRNAs was analyzed and SMS-associated pathways were enriched by gene set enrichment analysis (GSEA). Results a total of 95 lncRNAs were associated with the expression of 22 m6A methylation regulators in laryngeal cancer, 14 of which were prognostic lncRNAs. These lncRNAs were divided into two clusters and evaluated. Clinicopathological features did not show significant differences. However, the two clusters differed significantly in terms of naive B cells, memory B cells, naive CD4 T cells, T helper cells and immune score. lASSO regression analysis showed that risk score was a significant predictor of progression-free survival. Conclusion low expression of m6A-related lncRNAs involved in laryngeal cancer development in laryngeal cancer tissues can be used as an indicator to diagnose patients with laryngeal cancer, reduce patient prognosis, be an independent risk factor affecting patient prognosis and be able to assess patient prognosis.

Metabolomic Signatures of Scarff-Bloom-Richardson (SBR) Grade in Non-Metastatic Breast Cancer

PURPOSE

Identification of metabolomic biomarkers of high SBR grade in non-metastatic breast cancer.

METHODS

This retrospective bicentric metabolomic analysis included a training set (n = 51) and a validation set (n = 49) of breast cancer tumors, all classified as high-grade (grade III) or low-grade (grade I-II). Metabolomes of tissue samples were studied by liquid chromatography coupled with mass spectrometry.

RESULTS

A molecular signature of the top 12 metabolites was identified from a database of 602 frequently predicted metabolites. Partial least squares discriminant analyses showed that accuracies were 0.81 and 0.82, the R2 scores were 0.57 and 0.55, and the Q2 scores were 0.44431 and 0.40147 for the training set and validation set, respectively; areas under the curve for the Receiver Operating Characteristic Curve were 0.882 and 0.886. The most relevant metabolite was diacetylspermine. Metabolite set enrichment analyses and metabolic pathway analyses highlighted the tryptophan metabolism pathway, but the concentration of individual metabolites varied between tumor samples.

CONCLUSIONS

This study indicates that high-grade invasive tumors are related to diacetylspermine and tryptophan metabolism, both involved in the inhibition of the immune response. Targeting these pathways could restore anti-tumor immunity and have a synergistic effect with immunotherapy. Recent studies could not demonstrate the effectiveness of this strategy, but the use of theragnostic metabolomic signatures should allow better selection of patients.

Kynureninase Upregulation Is a Prominent Feature of NFR2-Activated Cancers and Is Associated with Tumor Immunosuppression and Poor Prognosis

The nuclear factor erythroid 2-related factor 2 (NRF2) pathway is frequently activated in various cancer types. Aberrant activation of NRF2 in cancer is attributed to gain-of-function mutations in the NRF2-encoding gene NFE2L2 or a loss of function of its suppressor, Kelch-like ECH-associated protein 1 (KEAP1). NRF2 activation exerts pro-tumoral effects in part by altering cancer cell metabolism. Previously, we reported a novel mechanism of NRF2 tumoral immune suppression through the selective upregulation of the tryptophan-metabolizing enzyme kynureninase (KYNU) in lung adenocarcinoma. In the current study, we explored the relevance of NRF2-mediated KYNU upregulation across multiple cancer types. Specifically, using a gene expression dataset for 9801 tumors representing 32 cancer types from The Cancer Genome Atlas (TCGA), we demonstrated that elevated KYNU parallels increased gene-based signatures of NRF2-activation and that elevated tumoral KYNU mRNA expression is strongly associated with an immunosuppressive tumor microenvironment, marked by high expression of gene-based signatures of Tregs as well as the immune checkpoint blockade-related genes CD274 (PDL-1), PDCD1 (PD-1), and CTLA4, regardless of the cancer type. Cox proportional hazard models further revealed that increased tumoral KYNU gene expression was prognostic for poor overall survival in several cancer types, including thymoma, acute myeloid leukemia, low-grade glioma, kidney renal papillary cell carcinoma, stomach adenocarcinoma, and pancreatic ductal adenocarcinoma (PDAC). Using PDAC as a model system, we confirmed that siRNA-mediated knockdown of NRF2 reduced KYNU mRNA expression, whereas activation of NFE2L2 (the coding gene for NRF2) through either small-molecule agonists or siRNA-mediated knockdown of KEAP1 upregulated KYNU in PDAC cells. Metabolomic analyses of the conditioned medium from PDAC cell lines revealed elevated levels of KYNU-derived anthranilate, confirming that KYNU was enzymatically functional. Collectively, our study highlights the activation of the NRF2-KYNU axis as a multi-cancer phenomenon and supports the relevance of tumoral KYNU as a marker of tumor immunosuppression and as a prognostic marker for poor overall survival.

c-MYC-Driven Polyamine Metabolism in Ovarian Cancer: From Pathogenesis to Early Detection and Therapy

c-MYC and its paralogues MYCN and MYCL are among the most frequently amplified and/or overexpressed oncoproteins in ovarian cancer. c-MYC plays a key role in promoting ovarian cancer initiation and progression. The polyamine pathway is a bona fide target of c-MYC signaling, and polyamine metabolism is strongly intertwined with ovarian malignancy. Targeting of the polyamine pathway via small molecule inhibitors has garnered considerable attention as a therapeutic strategy for ovarian cancer. Herein, we discuss the involvement of c-MYC signaling and that of its paralogues in promoting ovarian cancer tumorigenesis. We highlight the potential of targeting c-MYC-driven polyamine metabolism for the treatment of ovarian cancers and the utility of polyamine signatures in biofluids for early detection applications.

Overexpression of SMS in the tumor microenvironment is associated with immunosuppression in hepatocellular carcinoma

Disorders of polyamine metabolism may contribute to the development of hepatocellular carcinoma (HCC), but the precise mechanism remains unknown. This study reports that spermine synthase (SMS), an enzyme involved in polyamine biosynthesis, is overexpressed in HCC and not associated with hepatitis virus infection in HCC patients. The results of analyzing the clinical data of HCC patients showed that SMS level as a categorical dependent variable was related to clinicopathological features of poor prognosis. Furthermore, the Kaplan-Meier survival analysis and ROC curve indicated that increased SMS level is associated with poor survival rate in HCC and may be a potential biomarker to discriminate HCC tissues. However, SMS overexpression limited the therapeutic effect of immune checkpoint blockade (ICB), which seemed to be related to the immunosuppressive effect of the HCC immune microenvironment formed by higher mRNA transcript levels of immune checkpoints and higher infiltration levels of immunosuppressive cells. In samples with high and low SMS expression, functional enrichment analysis of the differentially expressed genes (DEGs) showed that SMS may be linked to the occurrence and development of HCC by affecting a variety of immune-related pathways, such as Intestinal immune network for IgA production, Fc gamma R-mediated phagocytosis, Antigen processing and presentation, Th1 and Th2 cell differentiation. Subsequently, analysis of the co-expression network of SMS in the liver hepatocellular carcinoma (LIHC) cohort revealed that SMS has a broad impact on multiple important immune- and metabolic-related processes in HCC. In summary, SMS is a promising biomarker to differentiate the prognosis, immune characteristics, and holds promise as a potential target for ICB therapy to improve HCC.

Two effective models based on comprehensive lipidomics and metabolomics can distinguish BC versus HCs, and TNBC versus non-TNBC

BACKGROUND

Lipidomics and metabolomics are closely related to tumor phenotypes, and serum lipoprotein subclasses and small-molecule metabolites are considered as promising biomarkers for breast cancer (BC) diagnosis. This study aimed to explore potential biomarker models based on lipidomic and metabolomic analysis that could distinguish BC from healthy controls (HCs) and triple-negative BC (TNBC) from non-TNBC.

METHODS

Blood samples were collected from 114 patients with BC and 75 HCs. A total of 112 types of lipoprotein subclasses and 30 types of small-molecule metabolites in the serum were detected by ¹ H-NMR. All lipoprotein subclasses and small-molecule metabolites were subjected to a three-step screening process in the order of significance (p < 0.05), univariate regression (p < 0.1), and lasso regression (nonzero coefficient). Discriminant models of BC versus HCs and TNBC versus non-TNBC were established using binary logistic regression.

RESULTS

We developed a valid discriminant model based on three-biomarker panel (formic acid, TPA2, and L6TG) that could distinguish patients with BC from HCs. The area under the receiver operating characteristic curve (AUC) was 0.999 (95% confidence interval [CI]: 0.995-1.000) and 0.990 (95% CI: 0.959-1.000) in the training and validation sets, respectively. Based on the panel (D-dimer, CA15-3, CEA, L5CH, glutamine, and ornithine), a discriminant model was established to differentiate between TNBC and non-TNBC, with AUC of 0.892 (95% CI: 0.778-0.967) and 0.905 (95% CI: 0.754-0.987) in the training and validation sets, respectively.

CONCLUSION

This study revealed lipidomic and metabolomic differences between BC versus HCs and TNBC versus non-TNBC. Two validated discriminatory models established against lipidomic and metabolomic differences can accurately distinguish BC from HCs and TNBC from non-TNBC.

IMPACT

Two validated discriminatory models can be used for early BC screening and help BC patients avoid time-consuming, expensive, and dangerous BC screening.

A polyamine-centric, blood-based metabolite panel predictive of poor response to CAR-T cell therapy in large B cell lymphoma

Anti-CD19 chimeric antigen receptor (CAR) T cell therapy for relapsed or refractory (r/r) large B cell lymphoma (LBCL) results in durable response in only a subset of patients. MYC overexpression in LBCL tumors is associated with poor response to treatment. We tested whether an MYC-driven polyamine signature, as a liquid biopsy, is predictive of response to anti-CD19 CAR-T therapy in patients with r/r LBCL. Elevated plasma acetylated polyamines were associated with non-durable response. Concordantly, increased expression of spermidine synthase, a key enzyme that regulates levels of acetylated spermidine, was prognostic for survival in r/r LBCL. A broad metabolite screen identified additional markers that resulted in a 6-marker panel (6MetP) consisting of acetylspermidine, diacetylspermidine, and lysophospholipids, which was validated in an independent set from another institution as predictive of non-durable response to CAR-T therapy. A polyamine centric metabolomics liquid biopsy panel has predictive value for response to CAR-T therapy in r/r LBCL.

Spermine synthase (SMS) serves as a prognostic biomarker in head and neck squamous cell carcinoma: a bioinformatics analysis

Background

Head and neck squamous cell carcinoma (HNSC) is an aggressive type of cancer that lacks early detection, and therefore, has a low 5-year survival rate. The spermine synthase (SMS) gene has been shown to be associated with Snyder-Robinson syndrome and poor prognosis of multiple cancers; however, its regulatory role in HNSC has never been investigated. Therefore, we explored the potential predictive value of SMS in HNSC.

Methods

We explored the association between SMS expression and clinicopathological parameters of HNSC patients by using data from The Cancer Genome Atlas datasets (TCGA). The prognostic value of SMS was evaluated using the Kaplan-Meier plotter, Gene Expression Profiling Interactive Analysis (GEPIA) 2 and univariate and multivariate Cox regression analyses. We further used gene set enrichment analysis (GESA) to investigate the potential roles of SMS in HNSC prognosis and Tumor Immunity Estimation Resource 2.0 (TIMER2.0) to analyze the correlation between immune cell infiltration and SMS expression. Finally, starBase was used to screen out prognosis-associated non-coding RNA genes to constructed the competing endogenous RNA (ceRNA) network. Co-expression and survival analyses were used to identify the ceRNA network's effect on HNSC prognosis.

Results

We found that SMS expression was increased in HNSC compared with normal tissues (P<0.05). In addition, SMS expression was associated with tumor grade (P=0.006), N stage (P=0.001), and prognosis. Survival analysis revealed that high expression of SMS showed worse overall survival (OS) (HR =1.4, P=0.01) and worse disease-free survival (DFS) (HR =1.5, P=0.014). Multivariate Cox analysis further supported the prognostic value of SMS in HNSC (HR =1.006636, P=0.0056). GESA showed that SMS was involved in metabolism- and immune-related pathways. The immune infiltration analyses results showed a decrease in the landscape of immune cell infiltration with high SMS expression and SMS deletion in HNSC. Finally, a ceRNA network (SMS/hsa-miR-23b-3p/KTN1-AS1 and VPS9D1-AS axis) was constructed based on the co-expression and survival analyses in HNSC.

Conclusions

Our findings first revealed that SMS functioned as a potential prognostic biomarker and provide insights into the molecular mechanisms of its function in HNSC. The use of SMS may be powerful for determining worse prognosis HNSC patients.

A Blood-Based Metabolite Panel for Distinguishing Ovarian Cancer from Benign Pelvic Masses

PURPOSE

To assess the contributions of circulating metabolites for improving upon the performance of the risk of ovarian malignancy algorithm (ROMA) for risk prediction of ovarian cancer among women with ovarian cysts.

EXPERIMENTAL DESIGN

Metabolomic profiling was performed on an initial set of sera from 101 serous and nonserous ovarian cancer cases and 134 individuals with benign pelvic masses (BPM). Using a deep learning model, a panel consisting of seven cancer-related metabolites [diacetylspermine, diacetylspermidine, N-(3-acetamidopropyl)pyrrolidin-2-one, N-acetylneuraminate, N-acetyl-mannosamine, N-acetyl-lactosamine, and hydroxyisobutyric acid] was developed for distinguishing early-stage ovarian cancer from BPM. The performance of the metabolite panel was evaluated in an independent set of sera from 118 ovarian cancer cases and 56 subjects with BPM. The contributions of the panel for improving upon the performance of ROMA were further assessed.

RESULTS

A 7-marker metabolite panel (7MetP) developed in the training set yielded an AUC of 0.86 [95% confidence interval (CI): 0.76-0.95] for early-stage ovarian cancer in the independent test set. The 7MetP+ROMA model had an AUC of 0.93 (95% CI: 0.84-0.98) for early-stage ovarian cancer in the test set, which was improved compared with ROMA alone [0.91 (95% CI: 0.84-0.98); likelihood ratio test P: 0.03]. In the entire specimen set, the combined 7MetP+ROMA model yielded a higher positive predictive value (0.68 vs. 0.52; one-sided P < 0.001) with improved specificity (0.89 vs. 0.78; one-sided P < 0.001) for early-stage ovarian cancer compared with ROMA alone.

CONCLUSIONS

A blood-based metabolite panel was developed that demonstrates independent predictive ability and complements ROMA for distinguishing early-stage ovarian cancer from benign disease to better inform clinical decision making.

Pharmacometabolomics reveals urinary diacetylspermine as a biomarker of doxorubicin effectiveness in triple negative breast cancer

Triple-negative breast cancer (TNBC) patients receive chemotherapy treatment, including doxorubicin, due to the lack of targeted therapies. Drug resistance is a major cause of treatment failure in TNBC and therefore, there is a need to identify biomarkers that determine effective drug response. A pharmacometabolomics study was performed using doxorubicin sensitive and resistant TNBC patient-derived xenograft (PDX) models to detect urinary metabolic biomarkers of treatment effectiveness. Evaluation of metabolite production was assessed by directly studying tumor levels in TNBC-PDX mice and human subjects. Metabolic flux leading to biomarker production was determined using stable isotope-labeled tracers in TNBC-PDX ex vivo tissue slices. Findings were validated in 12-h urine samples from control (n = 200), ER+/PR+ (n = 200), ER+/PR+/HER2+ (n = 36), HER2+ (n = 81) and TNBC (n = 200) subjects. Diacetylspermine was identified as a urine metabolite that robustly changed in response to effective doxorubicin treatment, which persisted after the final dose. Urine diacetylspermine was produced by the tumor and correlated with tumor volume. Ex vivo tumor slices revealed that doxorubicin directly increases diacetylspermine production by increasing tumor spermidine/spermine N¹-acetyltransferase 1 expression and activity, which was corroborated by elevated polyamine flux. In breast cancer patients, tumor diacetylspermine was elevated compared to matched non-cancerous tissue and increased in HER2+ and TNBC compared to ER+ subtypes. Urine diacetylspermine was associated with breast cancer tumor volume and poor tumor grade. This study describes a pharmacometabolomics strategy for identifying cancer metabolic biomarkers that indicate drug response. Our findings characterize urine diacetylspermine as a non-invasive biomarker of doxorubicin effectiveness in TNBC.

Application of Artificial Intelligence to Plasma Metabolomics Profiles to Predict Response to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer

There is a need to identify biomarkers predictive of response to neoadjuvant chemotherapy (NACT) in triple-negative breast cancer (TNBC). We previously obtained evidence that a polyamine signature in the blood is associated with TNBC development and progression. In this study, we evaluated whether plasma polyamines and other metabolites may identify TNBC patients who are less likely to respond to NACT. Pre-treatment plasma levels of acetylated polyamines were elevated in TNBC patients that had moderate to extensive tumor burden (RCB-II/III) following NACT compared to those that achieved a complete pathological response (pCR/RCB-0) or had minimal residual disease (RCB-I). We further applied artificial intelligence to comprehensive metabolic profiles to identify additional metabolites associated with treatment response. Using a deep learning model (DLM), a metabolite panel consisting of two polyamines as well as nine additional metabolites was developed for improved prediction of RCB-II/III. The DLM has potential clinical value for identifying TNBC patients who are unlikely to respond to NACT and who may benefit from other treatment modalities.

Polyamines in cancer: integrating organismal metabolism and antitumour immunity

The natural mammalian polyamines putrescine, spermidine and spermine are essential for both normal and neoplastic cell function and replication. Dysregulation of metabolism of polyamines and their requirements is common in many cancers. Both clinical and experimental depletion of polyamines have demonstrated their metabolism to be a rational target for therapy; however, the mechanisms through which polyamines can establish a tumour-permissive microenvironment are only now emerging. Recent data indicate that polyamines can play a major role in regulating the antitumour immune response, thus likely contributing to the existence of immunologically 'cold' tumours that do not respond to immune checkpoint blockade. Additionally, the interplay between the microbiota and associated tissues creates a tumour microenvironment in which polyamine metabolism, content and function can all be dramatically altered on the basis of microbiota composition, dietary polyamine availability and tissue response to its surrounding microenvironment. The goal of this Perspective is to introduce the reader to the many ways in which polyamines, polyamine metabolism, the microbiota and the diet interconnect to establish a tumour microenvironment that facilitates the initiation and progression of cancer. It also details ways in which polyamine metabolism and function can be successfully targeted for therapeutic benefit, including specifically enhancing the antitumour immune response.

Calorie restriction and breast cancer treatment: a mini-review

Calorie restriction (CR), referred to as a reduction in dietary calorie intake without malnutrition, has been demonstrated to be a safe way to extend longevity of yeast, worms, and laboratory animals, and to decrease the risk factors in age-related diseases including cancer in humans. Pre-clinical studies in animal models demonstrated that CR may enhance the efficacy of chemotherapy, radiation therapy, and immunotherapy during breast cancer treatment. Reduced calorie intake ameliorates risk factors and delays the onset of cancer by altering metabolism and fostering health-enhancing characteristics including increased autophagy and insulin sensitivity, and decreased blood glucose levels, inflammation, angiogenesis, and growth factor signaling. CR is not a common protocol implemented by medical practitioners to the general public due to the lack of substantial clinical studies. Future research and clinical trials are urgently needed to understand fully the biochemical basis of CR or CR mimetics to support its benefits. Here, we present a mini-review of research studies integrating CR as an adjuvant to chemotherapy, radiation therapy, or immunotherapy during breast cancer treatment.

A novel signature derived from metabolism-related genes GPT and SMS to predict prognosis of laryngeal squamous cell carcinoma

Background

A growing body of evidence has suggested the involvement of metabolism in the occurrence and development of tumors. But the link between metabolism and laryngeal squamous cell carcinoma (LSCC) has rarely been reported. This study seeks to understand and explain the role of metabolic biomarkers in predicting the prognosis of LSCC.

Methods

We identified the differentially expressed metabolism-related genes (MRGs) through RNA-seq data of The Cancer Genome Atlas (TCGA) and Gene set enrichment analysis (GSEA). After the screening of protein–protein interaction (PPI), hub MRGs were analyzed by least absolute shrinkage and selection operator (LASSO) and Cox regression analyses to construct a prognostic signature. Kaplan–Meier survival analysis and the receiver operating characteristic (ROC) was applied to verify the effectiveness of the prognostic signature in four cohorts (TCGA cohort, GSE27020 cohort, TCGA-sub1 cohort and TCGA-sub2 cohort). The expressions of the hub MRGs in LSCC cell lines and clinical samples were verified by quantitative reverse transcriptase PCR (qRT-PCR). The immunofluorescence staining of the tissue microarray (TMA) was carried out to further verify the reliability and validity of the prognostic signature. Cox regression analysis was then used to screen for independent prognostic factors of LSCC and a nomogram was constructed based on the results.

Results

Among the 180 differentially expressed MRGs, 14 prognostic MRGs were identified. A prognostic signature based on two MRGs (GPT and SMS) was then constructed and verified via internal and external validation cohorts. Compared to the adjacent normal tissues, SMS expression was higher while GPT expression was lower in LSCC tissues, indicating poorer outcomes. The prognostic signature was proven as an independent risk factor for LSCC in both internal and external validation cohorts. A nomogram based on these results was developed for clinical application.

Conclusions

Differentially expressed MRGs were found and proven to be related to the prognosis of LSCC. We constructed a novel prognostic signature based on MRGs in LSCC for the first time and verified it via different cohorts from both databases and clinical samples. A nomogram based on this prognostic signature was developed.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02647-2.

Cysteine conjugate beta-lyase 2 (CCBL2) expression as a prognostic marker of survival in breast cancer patients

Objective

Cysteine conjugate beta-lyase 2 (CCBL2), also known as kynurenine aminotransferase 3 (KAT3) or glutamine transaminase L (GTL), plays an essential role in transamination and cytochrome P450. Its correlation with some other cancers has been explored, but breast cancer (BC) not yet.

Methods

The mRNA and protein expression of CCBL2 in BC cell lines and patient samples were detected by RT-qPCR and immunohistochemistry (IHC). BC patients’ clinical information and RNA-Seq expression were acquired via The Cancer Genome Atlas (TCGA) database. Patients were categorized into high/low CCBL2 expression groups based on the optimal cutoff value (8.973) determined by receiver operating characteristic (ROC) curve. We investigated CCBL2 and clinicopathological characteristics’ relationship using Chi-square tests, estimated diagnostic capacity using ROC curves and drew survival curves using Kaplan–Meier estimate. We compared survival differences using Cox regression and externally validated using Gene Expression Omnibus (GEO) database. We evaluated enriched signaling pathways using gene set enrichment analysis (GSEA), explored CCBL2 and relevant genes’ relationship using tumor immunoassay resource (TIMER) databases and used the human protein atlas (HPA) for pan-cancer analysis and IHC.

Results

CCBL2 was overexpressed in normal human cell lines and tissues. CCBL2 expression was lower in BC tissues (n = 1104) than in normal tissues (n = 114), validated by GEO database. Several clinicopathologic features were related to CCBL2, especially estrogen receptor (ER), progesterone receptor (PR) and clinical stages. The low expression group exhibited poor survival. CCBL2’s area under curve (AUC) analysis showed finite diagnostic capacity. Multivariate cox-regression analysis indicated CCBL2 independently predicted BC survival. GSEA showed enriched pathways: early estrogen response, MYC and so on. CCBL2 positively correlated with estrogen, progesterone and androgen receptors. CCBL2 was downregulated in most cancers and was associated with their survival, including renal and ovarian cancers.

Conclusions

Low CCBL2 expression is a promising poor BC survival independent prognostic marker.

Mutational Activation of the NRF2 Pathway Upregulates Kynureninase Resulting in Tumor Immunosuppression and Poor Outcome in Lung Adenocarcinoma

Activation of the NRF2 pathway through gain-of-function mutations or loss-of-function of its suppressor KEAP1 is a frequent finding in lung cancer. NRF2 activation has been reported to alter the tumor microenvironment. Here, we demonstrated that NRF2 alters tryptophan metabolism through the kynurenine pathway that is associated with a tumor-promoting, immune suppressed microenvironment. Specifically, proteomic profiles of 47 lung adenocarcinoma (LUAD) cell lines (11 KEAP1 mutant and 36 KEAP1 wild-type) revealed the tryptophan-kynurenine enzyme kynureninase (KYNU) as a top overexpressed protein associated with activated NRF2. The siRNA-mediated knockdown of NFE2L2, the gene encoding for NRF2, or activation of the NRF2 pathway through siRNA-mediated knockdown of KEAP1 or via chemical induction with the NRF2-activator CDDO-Me confirmed that NRF2 is a regulator of KYNU expression in LUAD. Metabolomic analyses confirmed KYNU to be enzymatically functional. Analysis of multiple independent gene expression datasets of LUAD, as well as a LUAD tumor microarray demonstrated that elevated KYNU was associated with immunosuppression, including potent induction of T-regulatory cells, increased levels of PD1 and PD-L1, and resulted in poorer survival. Our findings indicate a novel mechanism of NRF2 tumoral immunosuppression through upregulation of KYNU.

The Potential Role of Spermine and Its Acetylated Derivative in Human Malignancies

Polyamines are essential biomolecules for normal cellular metabolism in humans. The roles of polyamines in cancer development have been widely discussed in recent years. Among all, spermine alongside with its acetylated derivative, N¹, N¹²-Diacetylspermine, demonstrate a relationship with the diagnosis and staging of various cancers, including lung, breast, liver, colorectal and urogenital. Numerous studies have reported the level of spermine in different body fluids and organ tissues in patients with different types of cancers. Currently, the role and the underlying mechanisms of spermine in cancer development and progression are still under investigation. This review summarized the roles of spermine in cancer development and as a diagnostic, prognostic and therapeutic tool in various cancers.

A Blood-based Polyamine Signature Associated With MEN1 Duodenopancreatic Neuroendocrine Tumor Progression

CONTEXT

Duodenopancreatic neuroendocrine tumors (dpNETs) frequently occur in patients with multiple endocrine neoplasia type 1 (MEN1), and metastatic dpNET is the primary cause of disease-related mortality. There is a need for biomarkers that can identify patients with MEN1-related dpNETs that are at high risk of developing distant metastasis. Polyamines have tumor-promoting roles in several cancer types.

OBJECTIVE

We hypothesized that MEN1-dpNET-related disease progression is associated with elevated levels of circulating polyamines.

METHODS

Through an international collaboration between The University of Texas MD Anderson Cancer Center, the National Institutes of Health, and the University Medical Center Utrecht, plasma polyamine levels were assessed using mass spectrometry in 84 patients with MEN1 (20 with distant metastatic dpNETs [patients] and 64 with either indolent dpNETs or no dpNETs [controls]). A mouse model of MEN1-pNET, Men1fl/flPdx1-CreTg, was used to test time-dependent changes in plasma polyamines associated with disease progression.

RESULTS

A 3-marker plasma polyamine signature (3MP: N-acetylputrescine, acetylspermidine, and diacetylspermidine) distinguished patients with metastatic dpNETs from controls in an initial set of plasmas from the 3 participating centers. The fixed 3MP yielded an area under the curve of 0.84 (95% CI, 0.62-1.00) with 66.7% sensitivity at 95% specificity for distinguishing patients from controls in an independent test set from MDACC. In Men1fl/flPdx1-CreTg mice, the 3MP was elevated early and remained high during disease progression.

CONCLUSION

Our findings provide a basis for prospective testing of blood-based polyamines as a potential means for monitoring patients with MEN1 for harboring or developing aggressive disease.

Impact of the Pd2Spm (Spermine) Complex on the Metabolism of Triple-Negative Breast Cancer Tumors of a Xenograft Mouse Model

The interest in palladium(II) compounds as potential new anticancer drugs has increased in recent years, due to their high toxicity and acquired resistance to platinum(II)-derived agents, namely cisplatin. In fact, palladium complexes with biogenic polyamines (e.g., spermine, Pd₂Spm) have been known to display favorable antineoplastic properties against distinct human breast cancer cell lines. This study describes the in vivo response of triple-negative breast cancer (TNBC) tumors to the Pd₂Spm complex or to cisplatin (reference drug), compared to tumors in vehicle-treated mice. Both polar and lipophilic extracts of tumors, excised from a MDA-MB-231 cell-derived xenograft mouse model, were characterized through nuclear magnetic resonance (NMR) metabolomics. Interestingly, the results show that polar and lipophilic metabolomes clearly exhibit distinct responses for each drug, with polar metabolites showing a stronger impact of the Pd(II)-complex compared to cisplatin, whereas neither drug was observed to significantly affect tumor lipophilic metabolism. Compared to cisplatin, exposure to Pd₂Spm triggered a higher number of, and more marked, variations in some amino acids, nucleotides and derivatives, membrane precursors (choline and phosphoethanolamine), dimethylamine, fumarate and guanidine acetate, a signature that may be relatable to the cytotoxicity and/or mechanism of action of the palladium complex. Putative explanatory biochemical hypotheses are advanced on the role of the new Pd₂Spm complex in TNBC metabolism.

Circulating acetylated polyamines correlate with Covid-19 severity in cancer patients

Cancer patients are particularly susceptible to the development of severe Covid-19, prompting us to investigate the serum metabolome of 204 cancer patients enrolled in the ONCOVID trial. We previously described that the immunosuppressive tryptophan/kynurenine metabolite anthranilic acid correlates with poor prognosis in non-cancer patients. In cancer patients, we observed an elevation of anthranilic acid at baseline (without Covid-19 diagnosis) and no further increase with mild or severe Covid-19. We found that, in cancer patients, Covid-19 severity was associated with the depletion of two bacterial metabolites, indole-3-proprionate and 3-phenylproprionate, that both positively correlated with the levels of several inflammatory cytokines. Most importantly, we observed that the levels of acetylated polyamines (in particular N1-acetylspermidine, N1,N8-diacetylspermidine and N1,N12-diacetylspermine), alone or in aggregate, were elevated in severe Covid-19 cancer patients requiring hospitalization as compared to uninfected cancer patients or cancer patients with mild Covid-19. N1-acetylspermidine and N1,N8-diacetylspermidine were also increased in patients exhibiting prolonged viral shedding (>40 days). An abundant literature indicates that such acetylated polyamines increase in the serum from patients with cancer, cardiovascular disease or neurodegeneration, associated with poor prognosis. Our present work supports the contention that acetylated polyamines are associated with severe Covid-19, both in the general population and in patients with malignant disease. Severe Covid-19 is characterized by a specific metabolomic signature suggestive of the overactivation of spermine/spermidine N1-acetyl transferase-1 (SAT1), which catalyzes the first step of polyamine catabolism.

Plasma Based Protein Signatures Associated with Small Cell Lung Cancer

Small-cell-lung cancer (SCLC) is associated with overexpression of oncogenes including Myc family genes and YAP1 and inactivation of tumor suppressor genes. We performed in-depth proteomic profiling of plasmas collected from 15 individuals with newly diagnosed early stage SCLC and from 15 individuals before the diagnosis of SCLC and compared findings with plasma proteomic profiles of 30 matched controls to determine the occurrence of signatures that reflect disease pathogenesis. A total of 272 proteins were elevated (area under the receiver operating characteristic curve (AUC) ≥ 0.60) among newly diagnosed cases compared to matched controls of which 31 proteins were also elevated (AUC ≥ 0.60) in case plasmas collected within one year prior to diagnosis. Ingenuity Pathway analyses of SCLC-associated proteins revealed enrichment of signatures of oncogenic MYC and YAP1. Intersection of proteins elevated in case plasmas with proteomic profiles of conditioned medium from 17 SCLC cell lines yielded 52 overlapping proteins characterized by YAP1-associated signatures of cytoskeletal re-arrangement and epithelial-to-mesenchymal transition. Among samples collected more than one year prior to diagnosis there was a predominance of inflammatory markers. Our integrated analyses identified novel circulating protein features in early stage SCLC associated with oncogenic drivers.

Protein citrullination as a source of cancer neoantigens

BACKGROUND

Citrulline post-translational modification of proteins is mediated by protein arginine deiminase (PADI) family members and has been associated with autoimmune diseases. The role of PADI-citrullinome in immune response in cancer has not been evaluated. We hypothesized that PADI-mediated citrullinome is a source of neoantigens in cancer that induces immune response.

METHODS

Protein expression of PADI family members was evaluated in 196 cancer cell lines by means of indepth proteomic profiling. Gene expression was assessed using messenger RNA data sets from The Cancer Genome Atlas. Immunohistochemical analysis of PADI2 and peptidyl-citrulline was performed using breast cancer tissue sections. Citrullinated 12-34-mer peptides in the putative Major Histocompatibility Complex-II (MHC-II) binding range were profiled in breast cancer cell lines to investigate the relationship between protein citrullination and antigen presentation. We further evaluated immunoglobulin-bound citrullinome by mass spectrometry using 156 patients with breast cancer and 113 cancer-free controls.

RESULTS

Proteomic and gene expression analyses revealed PADI2 to be highly expressed in several cancer types including breast cancer. Immunohistochemical analysis of 422 breast tumor tissues revealed increased expression of PADI2 in ER- tumors (p<0.0001); PADI2 protein expression was positively correlated (p<0.0001) with peptidyl-citrulline staining. PADI2 expression exhibited strong positive correlations with a B cell immune signature and with MHC-II-bound citrullinated peptides. Increased circulating citrullinated antigen-antibody complexes occurred among newly diagnosed breast cancer cases relative to controls (p=0.0012).

CONCLUSIONS

An immune response associated with citrullinome is a rich source of neoantigens in breast cancer with a potential for diagnostic and therapeutic applications.

A MYC-Driven Plasma Polyamine Signature for Early Detection of Ovarian Cancer

MYC is an oncogenic driver in the pathogenesis of ovarian cancer. We previously demonstrated that MYC regulates polyamine metabolism in triple-negative breast cancer (TNBC) and that a plasma polyamine signature is associated with TNBC development and progression. We hypothesized that a similar plasma polyamine signature may associate with ovarian cancer (OvCa) development. Using mass spectrometry, four polyamines were quantified in plasma from 116 OvCa cases and 143 controls (71 healthy controls + 72 subjects with benign pelvic masses) (Test Set). Findings were validated in an independent plasma set from 61 early-stage OvCa cases and 71 healthy controls (Validation Set). Complementarity of polyamines with CA125 was also evaluated. Receiver operating characteristic area under the curve (AUC) of individual polyamines for distinguishing cases from healthy controls ranged from 0.74-0.88. A polyamine signature consisting of diacetylspermine + N-(3-acetamidopropyl)pyrrolidin-2-one in combination with CA125 developed in the Test Set yielded improvement in sensitivity at >99% specificity relative to CA125 alone (73.7% vs 62.2%; McNemar exact test 2-sided P: 0.019) in the validation set and captured 30.4% of cases that were missed with CA125 alone. Our findings reveal a MYC-driven plasma polyamine signature associated with OvCa that complemented CA125 in detecting early-stage ovarian cancer.

MicroRNA-3613-3p functions as a tumor suppressor and represents a novel therapeutic target in breast cancer

BACKGROUND

MicroRNAs have been reported to participate in tumorigenesis, treatment resistance, and tumor metastasis. Novel microRNAs need to be identified and investigated to guide the clinical prognosis or therapy for breast cancer.

METHOD

The copy number variations (CNVs) of MIR3613 from Cancer Genome Atlas (TCGA) or Cancer Cell Line Encyclopedia (CCLE) were analyzed, and its correlation with breast cancer subtypes or prognosis was investigated. The expression level of miR-3613-3p in tumor tissues or serum of breast cancer patients was detected using in situ hybridization and qPCR. Gain-of-function studies were performed to determine the regulatory role of miR-3613-3p on proliferation, apoptosis, and tumor sphere formation of human breast cancer cells MDA-MB-231 or MCF-7. The effects of miR-3613-3p on tumor growth or metastasis in an immunocompromised mouse model of MDA-MB-231-luciferase were explored by intratumor injection of miR-3613-3p analogue. The target genes, interactive lncRNAs, and related signaling pathways of miR-3613-3p were identified by bioinformatic prediction and 3'-UTR assays.

RESULTS

We found that MIR3613 was frequently deleted in breast cancer genome and its deletion was correlated with the molecular typing, and an unfavorable prognosis in estrogen receptor-positive patients. MiR-3613-3p level was also dramatically lower in tumor tissues or serum of breast cancer patients. Gain-of-function studies revealed that miR-3613-3p could suppress proliferation and sphere formation and promote apoptosis in vitro and impeded tumor growth and metastasis in vivo. Additionally, miR-3613-3p might regulate cell cycle by targeting SMS, PAFAH1B2, or PDK3 to restrain tumor progression.

CONCLUSION

Our findings indicate a suppressive role of miR-3613-3p in breast cancer progression, which may provide an innovative marker or treatment for breast cancer patients.

Inhibition of the polyamine synthesis enzyme ornithine decarboxylase sensitizes triple-negative breast cancer cells to cytotoxic chemotherapy

Treatment of patients with triple-negative breast cancer (TNBC) is limited by a lack of effective molecular therapies targeting this disease. Recent studies have identified metabolic alterations in cancer cells that can be targeted to improve responses to standard-of-care chemotherapy regimens. Using MDA-MB-468 and SUM-159PT TNBC cells, along with LC-MS/MS and HPLC metabolomics profiling, we found here that exposure of TNBC cells to the cytotoxic chemotherapy drugs cisplatin and doxorubicin alter arginine and polyamine metabolites. This alteration was because of a reduction in the levels and activity of a rate-limiting polyamine biosynthetic enzyme, ornithine decarboxylase (ODC). Using gene silencing and inhibitor treatments, we determined that the reduction in ODC was mediated by its negative regulator antizyme, targeting ODC to the proteasome for degradation. Treatment with the ODC inhibitor difluoromethylornithine (DFMO) sensitized TNBC cells to chemotherapy, but this was not observed in receptor-positive breast cancer cells. Moreover, TNBC cell lines had greater sensitivity to single-agent DFMO, and ODC levels were elevated in TNBC patient samples. The alterations in polyamine metabolism in response to chemotherapy, as well as DFMO-induced preferential sensitization of TNBC cells to chemotherapy, reported here suggest that ODC may be a targetable metabolic vulnerability in TNBC.