Lysine in Combination With Estradiol Promote Dissemination of Estrogen Receptor Positive Breast Cancer via Upregulation of U2AF1 and RPN2 Proteins

Supervised discovery of interpretable gene programs from single-cell data

Factor analysis decomposes single-cell gene expression data into a minimal set of gene programs that correspond to processes executed by cells in a sample. However, matrix factorization methods are prone to technical artifacts and poor factor interpretability. We address these concerns with Spectra, an algorithm that combines user-provided gene programs with the detection of novel programs that together best explain expression covariation. Spectra incorporates existing gene sets and cell-type labels as prior biological information, explicitly models cell type and represents input gene sets as a gene-gene knowledge graph using a penalty function to guide factorization toward the input graph. We show that Spectra outperforms existing approaches in challenging tumor immune contexts, as it finds factors that change under immune checkpoint therapy, disentangles the highly correlated features of CD8+ T cell tumor reactivity and exhaustion, finds a program that explains continuous macrophage state changes under therapy and identifies cell-type-specific immune metabolic programs.

U2AF1 in various neoplastic diseases and relevant targeted therapies for malignant cancers with complex mutations (Review)

U2 small nuclear RNA auxiliary factor 1 (U2AF1) is a multifunctional protein that plays a crucial role in the regulation of RNA splicing during eukaryotic gene expression. U2AF1 belongs to the SR family of splicing factors and is involved in the removal of introns from mRNAs and exon-exon binding. Mutations in U2AF1 are frequently observed in myelodysplastic syndrome, primary myelofibrosis, chronic myelomonocytic leukaemia, hairy cell leukaemia and other solid tumours, particularly in lung, pancreatic, and ovarian carcinomas. Therefore, targeting U2AF1 for therapeutic interventions may be a viable strategy for treating malignant diseases. In the present review, the pathogenic mechanisms associated with U2AF1 in different malignant diseases were summarized, and the potential of related targeting agents was discussed. Additionally, the feasibility of natural product-based therapies directed against U2AF1 was explored.

Integrative physiology of lysine metabolites

Lysine is an essential amino acid that serves as a building block in protein synthesis. Beside this, the metabolic activity of lysine has only recently been unraveled. Lysine metabolism is tissue specific and is linked to several renal, cardiovascular, and endocrinological diseases through human metabolomics datasets. As a free molecule, lysine takes part in the antioxidant response and engages in protein modifications, and its chemistry shapes both proteome and metabolome. In the proteome, it is an acceptor for a plethora of posttranslational modifications. In the metabolome, it can be modified, conjugated, and degraded. Here, we provide an update on integrative physiology of mammalian lysine metabolites such as α-aminoadipic acid, saccharopine, pipecolic acid, and lysine conjugates such as acetyl-lysine, and sugar-lysine conjugates such as advanced glycation end products. We also comment on their emerging associative and mechanistic links to renal disease, hypertension, diabetes, and cancer.

Comparison of serum metabolomics in women with breast Cancer Prior to Chemotherapy and at 1 year: cardiometabolic implications

OBJECTIVE

Early-stage breast cancer (BC) is the second most common malignancy in women, worldwide. Early-detection and treatment advances have led to 5-year survival rates of 90% for early-stage breast cancer. However, the long-term morbidity of breast cancer remains high, with a majority of survivors facing increased risk of cardiometabolic conditions as well as secondary cancers. In particular, African American women with breast cancer experience higher morbidity and mortality than other women. Metabolomics is the comprehensive study of metabolites in biological samples to elucidate the role of monosaccharides, amino acids, and their respective metabolic pathways. Although some studies have found differential metabolites in women with breast cancer compared to normal controls, there has been little study of women with breast cancer across time and the active treatment trajectory. This study examines and compares the serum metabolomic profile of women with BC, prior to initial chemotherapy and at 1 year after inception of chemotherapy.

METHODS

This study examined serum metabolites through a secondary analysis of a longitudinal parent study (EPIGEN) of women diagnosed with early-stage BC. Participants were evaluated across 5 time points: prior to their receipt of chemotherapy (T1), at the time of their 4th chemotherapy treatment (T2), 6 months after the initiation of chemotherapy (T3), one year after the initiation of chemotherapy (T4) and two years after the initiation of chemotherapy (T5). This analysis focused on the metabolomic data from 70 participants from T1 to T4. Using ultra high-pressure liquid chromatography high resolution mass spectrometry (UHPLC-HRMS), we performed Friedman Rank Sum Test followed by Nemenyi post-hoc pairwise tests to identify which metabolite levels differed between time points, focusing on metabolites with a Benjamini-Hochberg false discovery rate (FDR) from the overall Friedman test < 0.05 and then specifically examined the p-values from the T1 vs. T4 pairwise comparison.

RESULTS

The untargeted serum metabolomics yielded a total of 2,395 metabolites identified on the basis of the accurate mass and MS/MS fragmentation, 1,264 of which were significant after Friedman's test (FDR < 0.05). The analysis then focused on the levels of 124 metabolites from the T1 vs. T4 post-hoc comparison that had a combined FDR < 0.05 and fold change (FC) > 2.0. Metabolite set enrichment analysis (MSEA) as part of Metaboanalyst 3.0 was performed to identify pathways that were significantly altered. The known metabolites identified from the functional analysis were used to evaluate the up and down regulated pathways. The 40metabolites from the Functional Analysis were mainly attributed to amino acids (specifically lysine regulation), fatty acids (particularly unsaturated) and steroid hormone synthesis (lysophosphatidic acid).

CONCLUSION

There were multiple significant changes in the serum metabolomic profile of women with breast cancer at one-year post inception of chemotherapy compared to pre-chemotherapy, most notably associated with lysine degradation, branched-chain amino acid synthesis, linoleic acid metabolism, tyrosine metabolism and biosynthesis of unsaturated fatty acids as the top 5 metabolic pathways. Some of these changes could be associated with metabolic perturbations that are consistent with heightened risk of cardiometabolic morbidity. Our results provide new insights into the mechanisms underlying potential heightened cardiovascular health risks in this population.

RPN2 in cancer: An overview

Oncogenes together with tumor suppresser genes are confirmed to regulate tumor phenotype in human cancers. RPN2, widely verified as an oncogene, encodes a protein that is part of an N-oligosaccharyl transferase, and is observed to be aberrantly expressed in human malignancies. Accumulating evidence unveils the vital functions of RPN2, contributing to tumorigenicity, metastasis, progression, and multi-drug resistance. Furthermore, previous studies partly indicated that RPN2 was involved in tumor progression via contributing to N-glycosylation and regulating multiple signaling pathways. In addition, RPN2 was also confirmed as a downstream target involved in tumor progression. Moreover, with demonstrated prognosis value and therapeutic target, RPN2 was also determined as a promising biomarker for forecasting patients' prognostic and therapy efficacy. In the present review, we aimed to summarize the present studies of RPN2 in cancer, and enhance the understanding of RPN2's extensive functions and clinical significances.

Establishment of a lncRNA-Based Prognostic Gene Signature Associated With Altered Immune Responses in HCC

Hepatocellular carcinoma (HCC) is a common malignancy with higher mortality, and means are urgently needed to improve the prognosis. T cell exclusion (TCE) plays a pivotal role in immune evasion, and lncRNAs represent a large group of tumor development and progression modulators. Using the TCGA HCC dataset (n=374), we identified 2752 differentially expressed and 702 TCE-associated lncRNAs, of which 336 were in both groups. As identified using the univariate Cox regression analysis, those associated with overall survival (OS) were subjected to the LASSO-COX regression analysis to develop a prognosis signature. The model, which consisted of 11 lncRNAs and was named 11LNCPS for 11-lncRNA prognosis signature, was validated and performed better than two previous models. In addition to OS and TCE, higher 11LNCPS scores had a significant correlation with reduced infiltrations of CD8+ T cells and dendritic cells (DCs) and decreased infiltrations of Th1, Th2, and pro B cells. As expected, these infiltration alterations were significantly associated with worse OS in HCC. Analysis of published data indicates that HCCs with higher 11LNCPS scores were transcriptomically similar to those that responded better to PDL1 inhibitor. Of the 11LNCPS lncRNAs, LINC01134 and AC116025.2 seem more crucial, as their upregulations affected more immune cell types' infiltrations and were significantly associated with TCE, worse OS, and compromised immune responses in HCC. LncRNAs in the 11LNCPS impacted many cancer-associated biological processes and signaling pathways, particularly those involved in immune function and metabolism. The 11LNCPS should be useful for predicting prognosis and immune responses in HCC.

Nuclear Receptor-Mediated Metabolic Reprogramming and the Impact on HR+ Breast Cancer

Simple Summary

Breast cancer is the most commonly diagnosed and second leading cause of cancer-related deaths in women in the United States, with hormone receptor positive (HR+) tumors representing more than two-thirds of new cases. Recent evidence has indicated that dysregulation of multiple metabolic programs, which can be driven through nuclear receptor activity, is essential for tumor genesis, progression, therapeutic resistance and metastasis. This study will review the current advances in our understanding of the impact and implication of altered metabolic processes driven by nuclear receptors, including hormone-dependent signaling, on HR+ breast cancer.

Abstract

Metabolic reprogramming enables cancer cells to adapt to the changing microenvironment in order to maintain metabolic energy and to provide the necessary biological macromolecules required for cell growth and tumor progression. While changes in tumor metabolism have been long recognized as a hallmark of cancer, recent advances have begun to delineate the mechanisms that modulate metabolic pathways and the consequence of altered signaling on tumorigenesis. This is particularly evident in hormone receptor positive (HR+) breast cancers which account for approximately 70% of breast cancer cases. Emerging evidence indicates that HR+ breast tumors are dependent on multiple metabolic processes for tumor progression, metastasis, and therapeutic resistance and that changes in metabolic programs are driven, in part, by a number of key nuclear receptors including hormone-dependent signaling. In this review, we discuss the mechanisms and impact of hormone receptor mediated metabolic reprogramming on HR+ breast cancer genesis and progression as well as the therapeutic implications of these metabolic processes in this disease.