Impact of Pelvic Radiation Therapy for Prostate Cancer on Global Metabolic Profiles and Microbiota-Driven Gastrointestinal Late Side Effects: A Longitudinal Observational Study

Microbiome and metabolome dynamics during radiotherapy for prostate cancer

BACKGROUND

Prostate cancer patients treated with radiotherapy are susceptible to acute gastrointestinal (GI) toxicity due to substantial overlap of the intestines with the radiation volume. Due to their intimate relationship with GI toxicity, faecal microbiome and metabolome dynamics during radiotherapy were investigated.

MATERIAL & METHODS

This prospective study included 50 prostate cancer patients treated with prostate (bed) only radiotherapy (PBRT) (n = 28) or whole pelvis radiotherapy (WPRT) (n = 22) (NCT04638049). Longitudinal sampling was performed prior to radiotherapy, after 10 fractions, near the end of radiotherapy and at follow-up. Patient symptoms were dichotomized into a single toxicity score. Microbiome and metabolome fingerprints were analyzed by 16S rRNA gene sequencing and ultra-high-performance liquid chromatography hybrid high-resolution mass spectrometry, respectively.

RESULTS

The individual α-diversity did not significantly change over time. Microbiota composition (β-diversity) changed significantly over treatment (PERMANOVA p-value = 0.03), but there was no significant difference in stability when comparing PBRT versus WPRT. Levels of various metabolites were significantly altered during radiotherapy. Baseline α-diversity was not associated with any toxicity outcome. Based on the metabolic fingerprint, no natural clustering according to toxicity profile could be achieved.

CONCLUSIONS

Radiation dose and treatment volume demonstrated limited effects on microbiome and metabolome fingerprints. In addition, no distinctive signature for toxicity status could be established. There is an ongoing need for toxicity risk stratification tools for diagnostic and therapeutic purposes, but the current evidence implies that the translation of metabolic and microbial biomarkers into routine clinical practice remains challenging.

Microbiota as the unifying factor behind the hallmarks of cancer

The human microbiota is a complex ecosystem that colonizes body surfaces and interacts with host organ systems, especially the immune system. Since the composition of this ecosystem depends on a variety of internal and external factors, each individual harbors a unique set of microbes. These differences in microbiota composition make individuals either more or less susceptible to various diseases, including cancer. Specific microbes are associated with cancer etiology and pathogenesis and several mechanisms of how they drive the typical hallmarks of cancer were recently identified. Although most microbes reside in the distal gut, they can influence cancer initiation and progression in distant tissues, as well as modulate the outcomes of established cancer therapies. Here, we describe the mechanisms by which microbes influence carcinogenesis and discuss their current and potential future applications in cancer diagnostics and management.

The gut microbiota as a booster for radiotherapy: novel insights into radio-protection and radiation injury

Approximately 60-80% of cancer patients treated with abdominopelvic radiotherapy suffer post-radiotherapy toxicities including radiation enteropathy and myelosuppression. Effective preventive and therapeutic strategies are lacking for such radiation injury. The gut microbiota holds high investigational value for deepening our understanding of the pathogenesis of radiation injury, especially radiation enteropathy which resembles inflammatory bowel disease pathophysiology and for facilitating personalized medicine by providing safer therapies tailored for cancer patients. Preclinical and clinical data consistently support that gut microbiota components including lactate-producers, SCFA-producers, indole compound-producers and Akkermansia impose intestinal and hematopoietic radio-protection. These features serve as potential predictive biomarkers for radiation injury, together with the microbial diversity which robustly predicts milder post-radiotherapy toxicities in multiple types of cancer. The accordingly developed manipulation strategies including selective microbiota transplantation, probiotics, purified functional metabolites and ligands to microbe-host interactive pathways are promising radio-protectors and radio-mitigators that merit extensive validation in clinical trials. With massive mechanistic investigations and pilot clinical trials reinforcing its translational value the gut microbiota may boost the prediction, prevention and mitigation of radiation injury. In this review, we summarize the state-of-the-art landmark researches related with radio-protection to provide illuminating insights for oncologists, gastroenterologists and laboratory scientists interested in this overlooked complexed disorder.

Prospective, longitudinal analysis of the gut microbiome in patients with locally advanced rectal cancer predicts response to neoadjuvant concurrent chemoradiotherapy

BACKGROUND

Neoadjuvant concurrent chemoradiotherapy (nCCRT) is a standard treatment for locally advanced rectal cancer (LARC). The gut microbiome may be reshaped by radiotherapy through its effects on microbial composition, mucosal immunity, and the systemic immune system. We sought to clarify dynamic, longitudinal changes in the gut microbiome and blood immunomodulators throughout nCCRT and to explore the relationship of such changes with outcomes after nCCRT.

METHODS

A total of 39 patients with LARC were recruited for this study. Fecal samples and peripheral blood samples were collected from all 39 patients before nCCRT, during nCCRT (at week 3), and after nCCRT (at week 5). The gut microbiota and the microbial community structure were analyzed by 16S rRNA sequencing of the V3-V4 region. Levels of blood immunomodulatory proteins were measured with a Millipore HCKPMAG-11 K kit and Luminex 200 platform (Luminex, USA).

RESULTS

Cross-sectional and longitudinal analyses revealed that the gut microbiome profile and enterotype exhibited characteristic variations that could distinguish patients with good response (AJCC TRG classification 0-1) vs poor response (TRG 2-3) to nCCRT. Sparse partial least squares regression and canonical correspondence analyses showed multivariate associations between specific microbial taxa, host immunomodulatory proteins, immune cells, and outcomes after nCCRT. An integrated model consisting of baseline Clostridium sensu stricto 1 levels, fold changes in Intestinimonas, blood levels of the herpesvirus entry mediator (HVEM/CD270), and lymphocyte counts could predict good vs poor outcome after nCCRT [area under the receiver-operating characteristics curve (AUC)= 0.821; area under the precision-recall curve [AUPR] = 0.911].

CONCLUSIONS

Our results showed that longitudinal variations in specific gut taxa, associated host immune cells, and immunomodulatory proteins before and during nCCRT could be useful for early predictions of the efficacy of nCCRT, which could guide the choice of individualized treatment for patients with LARC.

Carbon Ion Radiotherapy Induce Metabolic Inhibition After Functional Imaging-Guided Simultaneous Integrated Boost for Prostate Cancer

Purpose

As local recurrence remains a challenge and the advantages of the simultaneous integrated boost (SIB) technique have been validated in photon radiotherapy, we applied the SIB technique to CIRT. The aim was to investigate the metabolomic changes of the CIRT with concurrent androgen deprivation therapy (ADT) in localized prostate cancer (PCa) and the unique metabolic effect of the SIB technique.

Material and Methods

This study enrolled 24 pathologically confirmed PCa patients. All patients went through CIRT with concurrent ADT. The gross target volume (GTV) boost was defined as positive lesions on both 68Ga-PSMA PET/CT and mpMRI images. Urine samples collected before and after CIRT were analyzed by the Q-TOF UPLC-MS/MS system. R platform and MetDNA were used for peak detection and identification. Statistical analysis and metabolic pathway analysis were performed on Metaboanalyst.

Results

The metabolite profiles were significantly altered after CIRT. The most significantly altered metabolic pathway is PSMA participated alanine, aspartate and glutamate metabolism. Metabolites in this pathway showed a trend to be better suppressed in the SIB group. A total of 11 identified metabolites were significantly discriminative between two groups and all of them were better down-regulated in the SIB group. Meanwhile, among these metabolites, three metabolites in DNA damage and repair related purine metabolism were down-regulated to a greater extent in the SIB group.

Conclusion

Metabolic dysfunction was one of the typical characteristics of PCa. CIRT with ADT showed a powerful inhibition of PCa metabolism, especially in PSMA participated metabolic pathway. The SIB CIRT showed even better performance on down-regulation of most metabolism than uniform-dose-distribution CIRT. Meanwhile, the SIB CIRT also showed its unique superiority to inhibit purine metabolism. PSMA PET/CT guided SIB CIRT showed its potentials to further benefit PCa patients.

Biofluid Metabolomics and Lipidomics of Mice Exposed to External Very High-Dose Rate Radiation

High-throughput biodosimetry methods to determine exposure to ionizing radiation (IR) that can also be easily scaled to multiple testing sites in emergency situations are needed in the event of malicious attacks or nuclear accidents that may involve a substantial number of civilians. In the event of an improvised nuclear device (IND), a complex IR exposure will have a very high-dose rate (VHDR) component from an initial blast. We have previously addressed low-dose rate (LDR, ≤1 Gy/day) exposures from internal emitters on biofluid small molecule signatures, but further research on the VHDR component of the initial blast is required. Here, we exposed 8- to 10-week-old male C57BL/6 mice to an acute dose of 3 Gy using a reference dose rate of 0.7 Gy/min or a VHDR of 7 Gy/s, collected urine and serum at 1 and 7 d, then compared the metabolite signatures using either untargeted (urine) or targeted (serum) approaches with liquid chromatography mass spectrometry platforms. A Random Forest classification approach showed strikingly similar changes in urinary signatures at 1 d post-irradiation with VHDR samples grouping closer to control samples at 7 d. Identical metabolite panels (carnitine, trigonelline, xanthurenic acid, N6,N6,N6-trimethyllysine, spermine, and hexosamine-valine-isoleucine-OH) could differentiate IR exposed individuals with high sensitivity and specificity (area under the receiver operating characteristic (AUROC) curves 0.89–1.00) irrespective of dose rate at both days. For serum, the top 25 significant lipids affected by IR exposure showed slightly higher perturbations at 0.7 Gy/min vs. 7 Gy/s; however, identical panels showed excellent sensitivity and specificity at 1 d (three hexosylceramides (16:0), (18:0), (24:0), sphingomyelin [26:1], lysophosphatidylethanolamine [22:1]). Mice could not be differentiated from control samples at 7 d for a 3 Gy exposure based on serum lipid signatures. As with LDR exposures, we found that identical biofluid small molecule signatures can identify IR exposed individuals irrespective of dose rate, which shows promise for more universal applications of metabolomics for biodosimetry.

Metabolic response to radiation therapy in cancer

Tumor metabolism has emerged as a hallmark of cancer and is involved in carcinogenesis and tumor growth. Reprogramming of tumor metabolism is necessary for cancer cells to sustain high proliferation rates and enhanced demands for nutrients. Recent studies suggest that metabolic plasticity in cancer cells can decrease the efficacy of anticancer therapies by enhancing antioxidant defenses and DNA repair mechanisms. Studying radiation-induced metabolic changes will lead to a better understanding of radiation response mechanisms as well as the identification of new therapeutic targets, but there are few robust studies characterizing the metabolic changes induced by radiation therapy in cancer. In this review, we will highlight studies that provide information on the metabolic changes induced by radiation and oxidative stress in cancer cells and the associated underlying mechanisms.

Carbon Ion Radiotherapy Evokes a Metabolic Reprogramming and Individualized Response in Prostate Cancer

Introduction: Carbon ion radiotherapy (CIRT) is a novel treatment for prostate cancer (PCa). However, the underlying mechanism for the individualized response to CIRT is still not clear. Metabolic reprogramming is essential for tumor growth and proliferation. Although changes in metabolite profiles have been detected in patients with cancer treated with photon radiotherapy, there is limited data regarding CIRT-induced metabolic changes in PCa. Therefore, the study aimed to investigate the impact of metabolic reprogramming on individualized response to CIRT in patients with PCa.

Materials and Methods: Urine samples were collected from pathologically confirmed patients with PCa before and after CIRT. A UPLC-MS/MS system was used for metabolite detection. XCMS online, MetDNA, and MS-DIAL were used for peak detection and identification of metabolites. Statistical analysis and metabolic pathway analysis were performed on MetaboAnalyst.

Results: A total of 1,701 metabolites were monitored in this research. Principal component analysis (PCA) revealed a change in the patient's urine metabolite profiles following CIRT. Thirty-five metabolites were significantly altered, with the majority of them being amino acids. The arginine biosynthesis and histidine metabolism pathways were the most significantly altered pathways. Hierarchical cluster analysis (HCA) showed that after CIRT, the patients could be clustered into two groups according to their metabolite profiles. The arginine biosynthesis and phenylalanine, tyrosine, and tryptophan biosynthesis pathways are the most significantly discriminated pathways.

Conclusion: Our preliminary findings indicate that metabolic reprogramming and inhibition are important mechanisms involved in response to CIRT in patients with PCa. Therefore, changes in urine metabolites could be used to timely assess the individualized response to CIRT.