Impact of Exogenous Treatment with Histidine on Hepatocellular Carcinoma Cells

Serum metabolic fingerprints encode functional biomarkers for ovarian cancer diagnosis: a large-scale cohort study

BACKGROUND

Ovarian cancer (OC) ranks as the most lethal gynaecological malignancy worldwide, with early diagnosis being crucial yet challenging. Current diagnostic methods like transvaginal ultrasound and blood biomarkers show limited sensitivity/specificity. This study aimed to identify and validate serum metabolic biomarkers for OC diagnosis using the largest cohort reported to date.

METHODS

We constructed a large-scale OC-associated cohort of 1432 subjects, including 662 OC, 563 benign ovarian disease, and 207 healthy control subjects, across retrospective (n = 1073) and set-aside validation (n = 359) cohorts. Serum metabolic fingerprints (SMFs) were recorded using nanoparticle-enhanced laser desorption/ionization mass spectrometry (NELDI-MS). A diagnostic panel was developed through machine learning of SMFs in the discovery cohort and validated in independent verification and set-aside validation cohorts. The identified metabolic biomarkers were further validated using liquid chromatography MS and their biological functions were assessed in OC cell lines.

FINDINGS

We identified a metabolic biomarker panel including glucose, histidine, pyrrole-2-carboxylic acid, and dihydrothymine. This panel achieved consistent areas under the curve (AUCs) of 0.87-0.89 for distinguishing between malignant and benign ovarian masses across all cohorts, and improved to AUCs of 0.95-0.99 when combined with risk of ovarian malignancy algorithm (ROMA). In vitro validation provided initial biological context for the metabolic alterations observed in our diagnostic panel.

INTERPRETATION

Our study established a reliable serum metabolic biomarker panel for OC diagnosis with potential clinical translations. The NELDI-MS based approach offers advantages of fast analytical speed (∼30 s/sample) and low cost (∼2-3 dollars/sample), making it suitable for large-scale clinical applications.

FUNDING

MOST (2021YFA0910100), NSFC (82421001, 823B2050, 824B2059, and 82173077), Medical-Engineering Joint Funds of Shanghai Jiao Tong University (YG2021GD02, YG2024ZD07, and YG2023ZD08), Shanghai Science and Technology Committee Project (23JC1403000), Shanghai Institutions of Higher Learning (2021-01-07-00-02-E00083), Shanghai Jiao Tong University Inner Mongolia Research Institute (2022XYJG0001-01-16), Sichuan Provincial Department of Science and Technology (2024YFHZ0176), Innovation Research Plan by the Shanghai Municipal Education Commission (ZXWF082101), Innovative Research Team of High-Level Local Universities in Shanghai (SHSMU-ZDCX20210700), Basic-Clinical Collaborative Innovation Project from Shanghai Immune Therapy Institute, Guangdong Basic and Applied Basic Research Foundation (2024A1515013255).

Molecular dynamics-based computational investigations on the influence of tumor suppressor p53 binding protein against other proteins/peptides

The tumor-suppressing p-53 binding protein is a crucial protein that is involved in the prevention of cancer via its regulatory effect on a number of cellular processes. Recent evidence indicates that it interacts with a number of other proteins involved in cancer in ways that are not fully understood. An understanding of such interactions could provide insights into novel ways p53 further exerts its tumour prevention role via its interactions with diverse proteins. Thus, this study aimed to examine the interactions of the p53 protein with other proteins (peptides and histones) using molecular simulation dynamics. We opted for a total of seven proteins, namely 2LVM, 2MWO, 2MWP, 4CRI, 4 × 34, 5Z78, and 6MYO (control), and had their PBD files retrieved from the protein database. These proteins were then docked against the p-53 protein and the resulting interactions were examined using molecular docking simulations run at 500 ns. The result of the interactions revealed the utilisation of various amino acids in the process. The peptide that interacted with the highest number of amino acids was 5Z78 and these were Lys10, Gly21, Trp24, Pro105, His106, and Arg107, indicating a stronger interaction. The RMSD and RMSF values indicate that the complexes formed were stable, with 4CRI, 6MYO, and 2G3R giving the most stable values (less than 2.5 Å). Other parameters, including the SASA, Rg, and number of hydrogen bonds, all indicated the formation of fairly stable complexes. Our study indicates that overall, the interactions of 53BP1 with p53K370me2, p53K382me2, methylated K810 Rb, p53K381acK382me2, and tudor-interacting repair regulator protein indicated interactions that were not as strong as those with the histone protein. Thus, it could be that P53 may mediate its tumour suppressing effect via interactions with amino acids and histone.

Comprehensive metabolomic analysis identifies key biomarkers and modulators of immunotherapy response in NSCLC patients

Although immune checkpoint inhibitors (ICIs) have revolutionized immuno-oncology with effective clinical responses, only 30 to 40 % of patients respond to ICIs, highlighting the need for reliable biomarkers to predict and enhance therapeutic outcomes. This study investigated how amino acid, glycolysis, and bile acid metabolism affect ICI efficacy in non-small cell lung cancer (NSCLC) patients. Through targeted metabolomic profiling and machine learning analysis, we identified amino acid metabolism as a key factor, with histidine (His) linked to favorable outcomes and homocysteine (HCys), phenylalanine (Phe), and sarcosine (Sar) linked to poor outcomes. Importantly, the His/HCys+Phe+Sar ratio emerges as a robust biomarker. Furthermore, we emphasize the role of glycolysis-related metabolites, particularly lactate. Elevated lactate levels post-immunotherapy treatment correlate with poorer outcomes, underscoring lactate as a potential indicator of treatment efficacy. Moreover, specific bile acids, glycochenodeoxycholic acid (GCDCA) and taurolithocholic acid (TLCA), are associated with better survival and therapeutic response. Particularly, TLCA enhances T cell activation and anti-tumor immunity, suggesting its utility as a predictive biomarker and therapeutic agent. We also suggest a connection between gut microbiota and TLCA levels, with the Eubacterium genus modulating this relationship. Therefore, modulating specific metabolic pathways-particularly amino acid, glycolysis, and bile acid metabolism-could predict and enhance the efficacy of ICI therapy in NSCLC patients, with potential implications for personalized treatment strategies in immuno-oncology. ONE SENTENCE SUMMARY: Our study identifies metabolic biomarkers and pathways that could predict and enhance the outcomes of immune checkpoint inhibitor therapy in NSCLC patients.

Enhancing the anticancer effect of androgen deprivation therapy by monocarboxylate transporter 1 inhibitor in prostate cancer cells

BACKGROUND

Tumor initiation and progression necessitate a metabolic shift in cancer cells. Consequently, the progression of prostate cancer (PCa), a leading cause of cancer-related deaths in males globally, involves a shift from lipogenic to glycolytic metabolism. Androgen deprivation therapy (ADT) serves as the standard treatment for advanced-stage PCa. However, despite initial patient responses, castrate resistance emerges ultimately, necessitating novel therapeutic approaches. Therefore, in this study, we aimed to investigate the role of monocarboxylate transporters (MCTs) in PCa post-ADT and evaluate their potential as therapeutic targets.

METHODS

PCa cells (LNCaP and C4-2 cell line), which has high prostate-specific membrane antigen (PSMA) and androgen receptor (AR) expression among PCa cell lines, was used in this study. We assessed the expression of MCT1 in PCa cells subjected to ADT using charcoal-stripped bovine serum (CSS)-containing medium or enzalutamide (ENZ). Furthermore, we evaluated the synergistic anticancer effects of combined treatment with ENZ and SR13800, an MCT1 inhibitor.

RESULTS

Short-term ADT led to a significant upregulation in folate hydrolase 1 (FOLH1) and solute carrier family 16 member 1 (SLC16A1) gene levels, with elevated PSMA and MCT1 protein levels. Long-term ADT induced notable changes in cell morphology with further upregulation of FOLH1/PSMA and SLC16A1/MCT1 levels. Treatment with ENZ, a nonsteroidal anti-androgen, also increased PSMA and MCT1 expression. However, combined therapy with ENZ and SR13800 led to reduced PSMA level, decreased cell viability, and suppressed expression of cancer stem cell markers and migration indicators. Additionally, analysis of human PCa tissues revealed a positive correlation between PSMA and MCT1 expression in tumor regions.

CONCLUSIONS

Our results demonstrate that ADT led to a significant upregulation in MCT1 levels. However, the combination of ENZ and SR13800 demonstrated a promising synergistic anticancer effect, highlighting a potential therapeutic significance for patients with PCa undergoing ADT.

The Role of Amino Acids in Non-Enzymatic Antioxidant Mechanisms in Cancer: A Review

Currently, the antioxidant properties of amino acids and their role in the physicochemical processes accompanying oxidative stress in cancer remain unclear. Cancer cells are known to extensively uptake amino acids, which are used as an energy source, antioxidant precursors that reduce oxidative stress in cancer, and as regulators of inhibiting or inducing tumor cell-associated gene expression. This review examines nine amino acids (Cys, His, Phe, Met, Trp, Tyr, Pro, Arg, Lys), which play a key role in the non-enzymatic oxidative process in various cancers. Conventionally, these amino acids can be divided into two groups, in one of which the activity increases (Cys, Phe, Met, Pro, Arg, Lys) in cancer, and in the other, it decreases (His, Trp, Tyr). The review examines changes in the metabolism of nine amino acids in eleven types of oncology. We have identified the main nonspecific mechanisms of changes in the metabolic activity of amino acids, and described direct and indirect effects on the redox homeostasis of cells. In the future, this will help to understand better the nature of life of a cancer cell and identify therapeutic targets more effectively.

Characterization of Salivary and Plasma Metabolites as Biomarkers for HCC: A Pilot Study

(1) Background: The incidence of hepatocellular carcinoma (HCC) is rising, and current screening methods lack sensitivity. This study aimed to identify distinct and overlapping metabolites in saliva and plasma that are significantly associated with HCC. (2) Methods: Saliva samples were collected from 42 individuals (HCC = 16, cirrhosis = 12, healthy = 14), with plasma samples from 22 (HCC = 14, cirrhosis = 2, healthy = 6). We performed untargeted mass spectrometry on blood and plasma, tested metabolites for associations with HCC or cirrhosis using a logistic regression, and identified enriched pathways with Metaboanalyst. Pearson's correlation was employed to test for correlations between salivary and plasma metabolites. (3) Results: Six salivary metabolites (1-hexadecanol, isooctanol, malonic acid, N-acetyl-valine, octadecanol, and succinic acid) and ten plasma metabolites (glycine, 3-(4-hydroxyphenyl)propionic acid, aconitic acid, isocitric acid, tagatose, cellobiose, fucose, glyceric acid, isocitric acid, isothreonic acid, and phenylacetic acid) were associated with HCC. Malonic acid was correlated between the paired saliva and plasma samples. Pathway analysis highlighted deregulation of the 'The Citric Acid Cycle' in both biospecimens. (4) Conclusions: Our study suggests that salivary and plasma metabolites may serve as independent sources for HCC detection. Despite the lack of correlation between individual metabolites, they converge on 'The Citric Acid Cycle' pathway, implicated in HCC pathogenesis.

Pretreatment Glasgow Prognostic Score Correlated with Serum Histidine Level and Three-Year Mortality of Patients with Locally Advanced Head and Neck Squamous Cell Carcinoma and Optimal Performance Status

Few prospective cohort trials have investigted the effect of pretreatment nutritional and inflammatory status on the clinical outcome of patients with cancer and optimal performance status and assessed the interplay between nutrition, inflammation, body composition, and circulating metabolites before treatment. Here, 50 patients with locally advanced head and neck squamous cell carcinoma (LAHNSCC) and Eastern Cooperative Oncology Group performance status (ECOG PS) ≤ 2 were prospectively recruited along with 43 healthy participants. Before concurrent chemoradiotherapy, compared with healthy controls, the cancer group showed lower levels of histidine, leucine, and phenylalanine and had low values in anthropometric and body composition measurements; however, the group displayed higher ornithine levels, more malnutrition, and severe inflammation. Pretreatment advanced Glasgow prognostic score (1 and 2) status was the sole prognostic factor for 3-year mortality rate and was associated with age and serum histidine levels in patients with cancer. Thus, even at the same tumor stage and ECOG PS, patients with LAHNSCC, poor nutrition, and high inflammation severity at baseline may have inferior survival outcomes than those with adequate nutrition and low inflammation severity. Assessment of pretreatment nutritional and inflammatory status should be included in the enrollment criteria in future studies.

Treatment-Interval Changes in Serum Levels of Albumin and Histidine Correlated with Treatment Interruption in Patients with Locally Advanced Head and Neck Squamous Cell Carcinoma Completing Chemoradiotherapy under Recommended Calorie and Protein Provision

We investigated risk factors for treatment interruption (TI) in patients with locally advanced head and neck squamous-cell carcinoma (LAHNSCC) following concurrent chemoradiotherapy (CCRT), under the provision of recommended calorie and protein intake; we also evaluated the associations between clinicopathological variables, calorie and protein supply, nutrition–inflammation biomarkers (NIBs), total body composition change (TBC), and a four-serum-amino-acid metabolite panel (histidine, leucine, ornithine, and phenylalanine) among these patients. Patients with LAHNSCC who completed the entire planned CCRT course and received at least 25 kcal/kg/day and 1 g of protein/kg/day during CCRT were prospectively recruited. Clinicopathological variables, anthropometric data, blood NIBs, CCRT-related factors, TBC data, and metabolite panels before and after treatment were collected; 44 patients with LAHNSCC were enrolled. Nine patients (20.4%) experienced TIs. Patients with TIs experienced greater reductions in hemoglobin, serum levels of albumin, uric acid, histidine, and appendicular skeletal mass, and suffered from more grade 3/4 toxicities than those with no TI. Neither increased daily calorie supply (≥30 kcal/kg/day) nor feeding tube placement was correlated with TI. Multivariate analysis showed that treatment-interval changes in serum albumin and histidine levels, but not treatment toxicity, were independently associated with TI. Thus, changes in serum levels of albumin and histidine over the treatment course could cause TI in patients with LAHNSCC following CCRT.