Impact of mechanical bowel preparation on the gut microbiome of patients undergoing left-sided colorectal cancer surgery: randomized clinical trial.

BACKGROUND: Postoperative complications after colorectal cancer surgery have been linked to the gut microbiome. However, the impact of mechanical bowel preparation using oral preparation agents or rectal enema on postoperative infections remains poorly understood. This study aimed to compare the impact of oral preparation and rectal enema on the gut microbiome and postoperative complications. METHODS: This open-label pilot RCT was conducted at the National Cancer Institute, Vilnius, Lithuania. Patients with left-side colorectal cancer scheduled for elective resection with primary anastomosis were randomized 1 : 1 to preoperative mechanical bowel preparation with either oral preparation or rectal enema. Stool samples were collected before surgery, and on postoperative day 6 and 30 for 16S rRNA gene sequencing analysis. The primary outcome was difference in ß-diversity between groups on postoperative day 6. RESULTS: Forty participants were randomized to oral preparation (20) or rectal enema (20). The two groups had similar changes in microbiome composition, and there was no difference in ß-diversity on postoperative day 6. Postoperative infections occurred in 12 patients (32%), without differences between the study groups. Patients with infections had an increased abundance of bacteria from the Actinomycetaceae family, Actinomyces genus, Sutterella uncultured species, and Enterococcus faecalis species. CONCLUSION: Mechanical bowel preparation with oral preparation or rectal enema resulted in similar dysbiosis. Patients who experienced postoperative infections exhibited distinct gut microbiome compositions on postoperative day 6, characterized by an increased abundance of bacteria from the Actinomycetaceae family, Actinomyces genus, Sutterella uncultured species, and Enterococcus faecalis species. REGISTRATION NUMBER: NCT04013841 (http://www.clinicaltrials.gov).

Cellular and Microbial In Vitro Modelling of Gastrointestinal Cancer.

Human diseases are multifaceted, starting with alterations at the cellular level, damaging organs and their functions, and disturbing interactions and immune responses. In vitro systems offer clarity and standardisation, which are crucial for effectively modelling disease. These models aim not to replicate every disease aspect but to dissect specific ones with precision. Controlled environments allow researchers to isolate key variables, eliminate confounding factors and elucidate disease mechanisms more clearly. Technological progress has rapidly advanced model systems. Initially, 2D cell culture models explored fundamental cell interactions. The transition to 3D cell cultures and organoids enabled more life-like tissue architecture and enhanced intercellular interactions. Advanced bioreactor-based devices now recreate the physicochemical environments of specific organs, simulating features like perfusion and the gastrointestinal tract's mucus layer, enhancing physiological relevance. These systems have been simplified and adapted for high-throughput research, marking significant progress. This review focuses on in vitro systems for modelling gastrointestinal tract cancer and the side effects of cancer treatment. While cell cultures and in vivo models are invaluable, our main emphasis is on bioreactor-based in vitro modelling systems that include the gut microbiome.

Human gut microbiome: Therapeutic opportunities for metabolic syndrome-Hype or hope?

Shifts in gut microbiome composition and metabolic disorders are associated with one another. Clinical studies and experimental data suggest a causal relationship, making the gut microbiome an attractive therapeutic goal. Diet, intake of probiotics or prebiotics and faecal microbiome transplantation (FMT) are methods to alter a person's microbiome composition. Although FMT may allow establishing a proof of concept to use microbiome modulation to treat metabolic disorders, studies show mixed results regarding the effects on metabolic parameters as well as on the composition of the microbiome. This review summarizes the current knowledge on diet, probiotics, prebiotics and FMT to treat metabolic diseases, focusing on studies that also report alterations in microbiome composition. Furthermore, clinical trial results on the effects of common drugs used to treat metabolic diseases are synopsized to highlight the bidirectional relationship between the microbiome and metabolic diseases. In conclusion, there is clear evidence that microbiome modulation has the potential to influence metabolic diseases; however, it is not possible to distinguish which intervention is the most successful. In addition, a clear commitment from all stakeholders is necessary to move forward in the direction of developing targeted interventions for microbiome modulation.

Combination of DNA methylation biomarkers with multiparametric magnetic resonance and ultrasound imaging fusion biopsy to detect the local spread of prostate cancer.

BACKGROUND: This study aimed to investigate the extent of field cancerization adjacent to index lesions in prostate cancer (PCa) by measuring DNA methylation of selected tumor suppressor genes in the perifocal tissue of PCa not visible on multiparametric magnetic resonanse imaging (mpMRI) for the safe zone of focal therapy identification. METHODS: A total of 272 patients were enrolled in this study, 44 patients' tissue biosamples were included in the field cancerization research, and 272 urine samples were included in the urine-based test development. Targeted biopsies were performed using the mpMRI/ultrasoundimage fusion system. RESULTS: Quantitative analysis revealed significantly higher DNA methylation levels of RARB, RASSF1, GSTP1 & APC genes in the index lesion compared with perifocal tissue samples 10 mm away from it (p < 0.0001). Notably, the RARB, GSTP1 & APC and RARB, RASSF1, GSTP1 & APC biomarker combinations exhibited the highest sensitivity and specificity comparing the extent of DNA methylation in index lesions and noncancerous prostate tissues 20 mm away (both area under the curve [AUC] = 0.98; p < 0.0001). The analysis of the potential urinary biomarkers showed that the combination of all four DNA methylation biomarkers with prostate-specific antigen (PSA) or PSA density (PSAD) in the blood significantly improves the detection of clinically significant PCa (csPCa). The combination of the four-biomarker test with PSAD allowed the identification of csPCa with ≥90% sensitivity and specificity. CONCLUSION: Thus, this study suggests that for focal therapy by region target hemi-ablation, the safe distance from the index lesion is no less than 10 mm. Noninvasive urine DNA methylation tests in combination with PSAD could be used for further follow-up of the patients, but larger prospective studies with external validation are needed.

SARS-CoV-2 RT-qPCR Ct values in saliva and nasopharyngeal swab samples for disease severity prediction.

Background: Comparison of clinical value of RT-qPCR-based SARS-CoV-2 tests performed on saliva samples (SSs) and nasopharyngeal swab samples (NPSs) for prediction of the COVID-19 disease severity. Methods: Three paired SSs and NPSs collected every 3 days from 100 hospitalised COVID-19 patients during 2020 Jul-2021 Jan were tested by RT-qPCR for the original SARS-CoV-2 virus and compared to 150 healthy controls. Cases were divided into mild+moderate (Cohort I, N = 47) and severe disease (Cohort II, N = 53) cohorts and compared. Results: SARS-CoV-2 was detected in 65% (91/140) vs. 53% (82/156) of NPSs and 49% (68/139) vs. 48% (75/157) of SSs collected from Cohort I and II, respectively, resulting in the total respective detection rates of 58% (173/296) vs. 48% (143/296) (P = 0.017). Ct values of SSs were lower than those of NPSs (mean Ct = 28.01 vs. 30.07, P = 0.002). Although Ct values of the first SSs were significantly lower in Cohort I than in Cohort II (P = 0.04), it became negative earlier (mean 11.7 vs. 14.8 days, P = 0.005). Multivariate Cox proportional hazards regression analysis showed that Ct value ≤30 from SSs was the independent predictor for severe COVID-19 (HR = 10.06, 95% CI: 1.84-55.14, P = 0.008). Conclusion: Salivary RT-qPCR testing is suitable for SARS-CoV-2 infection control, while simple measurement of Ct values can assist in prediction of COVID-19 severity.

Urine Molecular Biomarkers for Detection and Follow-Up of Small Renal Masses.

Active surveillance (AS) is the best strategy for small renal masses (SRMs) management; however, reliable methods for early detection and disease aggressiveness prediction are urgently needed. The aim of the present study was to validate DNA methylation biomarkers for non-invasive SRM detection and prognosis. The levels of methylated genes TFAP2B, TAC1, PCDH8, ZNF677, FLRT2, and FBN2 were evaluated in 165 serial urine samples prospectively collected from 39 patients diagnosed with SRM, specifically renal cell carcinoma (RCC), before and during the AS via quantitative methylation-specific polymerase chain reaction. Voided urine samples from 92 asymptomatic volunteers were used as the control. Significantly higher methylated TFAP2B, TAC1, PCDH8, ZNF677, and FLRT2 levels and/or frequencies were detected in SRM patients' urine samples as compared to the control. The highest diagnostic power (AUC = 0.74) was observed for the four biomarkers panel with 92% sensitivity and 52% specificity. Methylated PCDH8 level positively correlated with SRM size at diagnosis, while TFAP2B had the opposite effect and was related to SRM progression. To sum up, SRMs contribute significantly to the amount of methylated DNA detectable in urine, which might be used for very early RCC detection. Moreover, PCDH8 and TFAP2B methylation have the potential to be prognostic biomarkers for SRMs.

The Role of TSHR, PTEN and RASSF1A Promoters' Methylation Status for Non-Invasive Detection of Papillary Thyroid Carcinoma.

Aim: We investigated whether a difference exists between TSHR, PTEN and RASSF1A methylation status in plasma of subjects with papillary thyroid cancer (PTC). Methods: Peripheral blood samples were collected from 68 patients with PTC and 86 healthy controls (HC). Thyroid cancer tissue and corresponding adjacent normal tissue methylation levels were analyzed. DNA methylation level changes in TSHR, PTEN and RASSF1A genes were analyzed by quantitative methylation-sensitive polymerase chain reaction. Results: We observed that the methylation level of TSHR was significantly higher in the thyroid cancer tissue compared to adjacent normal tissue (p = 0.040). TSHR methylation levels in the PTC group plasma samples were significantly higher compared to HC (p = 0.022). After surgery, PTC plasma samples showed lower TSHR and PTEN methylation levels compared to the levels before surgery (p = 0.003, p = 0.031, respectively). The TSHR methylation level was significantly higher in PTC with larger tumor size (>2 cm) (p < 0.001), and lymph node metastases (p = 0.01), lymphovascular invasion (p = 0.02) and multifocality (p = 0.013) 0ROC analysis revealed that the TSHR methylation level provides high accuracy in distinguishing PTC from HC (p = 0.022, AUC of 0.616). Conclusion: TSHR methylation in peripheral blood samples is expected to be a sensitive and specific minimally invasive tool for the diagnosis of PTC, especially in combination with other diagnostic means.

Clinical significance of novel DNA methylation biomarkers for renal clear cell carcinoma.

OBJECTIVE: Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney tumor characterized by the highest mortality rate of the genitourinary cancers, and, therefore, new diagnostic and/or prognostic biomarkers are urgently needed. METHODS: Based on genome-wide DNA methylation profiling in 11 pairs of ccRCC and non-cancerous renal tissues (NRT), the methylation at regulatory regions of ZNF677, FBN2, PCDH8, TFAP2B, TAC1, and FLRT2 was analyzed in 168 renal tissues and 307 urine samples using qualitative and quantitative methylation-specific PCR (MSP). RESULTS: Significantly higher methylation frequencies for all genes were found in ccRCC tissues compared to NRT (33-60% vs. 0-11%). The best diagnostic performance demonstrated a panel of ZNF677, FBN2, PCDH8, TFAP2B & TAC1 with 82% sensitivity and 96% specificity. Hypermethylation of ZNF677 and PCDH8 in the tissue samples was significantly related to numerous adverse clinicopathologic parameters. For the urine-based ccRCC detection, the highest diagnostic power (AUC = 0.78) was observed for a panel of ZNF677 & PCDH8 (with or without FBN2 or FLRT2) with 69-78% sensitivity and 69-80% specificity, albeit with lower values in the validation cohort. Besides, methylation of PCDH8 was significantly related to higher tumor stage and fat invasion in the study and validation cohorts. Moreover, PCDH8 was strongly predictive for OS (HR, 5.7; 95% CI 1.16-28.12), and its prognostic power considerably increased in combination with ZNF677 (HR, 12.5; 95% CI 1.47-105.58). CONCLUSION: In summary, our study revealed novel, potentially promising DNA methylation biomarkers of ccRCC with the possibility to be applied for non-invasive urine-based ccRCC detection and follow-up.

Promoter Methylation of PRKCB, ADAMTS12, and NAALAD2 Is Specific to Prostate Cancer and Predicts Biochemical Disease Recurrence.

The molecular diversity of prostate cancer (PCa) has been demonstrated by recent genome-wide studies, proposing a significant number of different molecular markers. However, only a few of them have been transferred into clinical practice so far. The present study aimed to identify and validate novel DNA methylation biomarkers for PCa diagnosis and prognosis. Microarray-based methylome data of well-characterized cancerous and noncancerous prostate tissue (NPT) pairs was used for the initial screening. Ten protein-coding genes were selected for validation in a set of 151 PCa, 51 NPT, as well as 17 benign prostatic hyperplasia samples. The Prostate Cancer Dataset (PRAD) of The Cancer Genome Atlas (TCGA) was utilized for independent validation of our findings. Methylation frequencies of ADAMTS12, CCDC181, FILIP1L, NAALAD2, PRKCB, and ZMIZ1 were up to 91% in our study. PCa specific methylation of ADAMTS12, CCDC181, NAALAD2, and PRKCB was demonstrated by qualitative and quantitative means (all p < 0.05). In agreement with PRAD, promoter methylation of these four genes was associated with the transcript down-regulation in the Lithuanian cohort (all p < 0.05). Methylation of ADAMTS12, NAALAD2, and PRKCB was independently predictive for biochemical disease recurrence, while NAALAD2 and PRKCB increased the prognostic power of multivariate models (all p < 0.01). The present study identified methylation of ADAMTS12, NAALAD2, and PRKCB as novel diagnostic and prognostic PCa biomarkers that might guide treatment decisions in clinical practice.

Urinary DNA methylation biomarkers for prediction of prostate cancer upgrading and upstaging.

BACKGROUND: Significant numbers of prostate cancer (PCa) patients experience tumour upstaging and upgrading in surgical specimens that cause serious problems in timely and proper selection of the treatment strategy. This study was aimed at the evaluation of a set of established epigenetic biomarkers as a noninvasive tool for more accurate PCa categorization before radical prostatectomy (RP). METHODS: Quantitative methylation-specific PCR was applied for the methylation analysis of RARB, RASSF1, and GSTP1 in 514 preoperatively collected voided or catheterized urine samples from the single-centre cohort of 1056 treatment-naïve PCa patients who underwent RP. The rates of biopsy upgrading and upstaging were analysed in the whole cohort. RESULTS: Pathological examination of RP specimens revealed Gleason score upgrading in 27.2% and upstaging in 20.3% of the patients with a total misclassification rate of 39.0%. DNA methylation changes in at least one gene were detected in more than 80% of urine samples. Combination of the PSA test with the three-gene methylation analysis in urine was a significant predictor of pathological upstaging and upgrading (P < 0.050), however, with limited increase in overall accuracy. The PSA test or each gene alone was not informative enough. CONCLUSIONS: The urinary DNA methylation assay in combination with serum PSA may predict tumour stage or grade migration post-RP aiding in improved individual risk assessment and appropriate treatment selection. Clinical utility of these biomarkers should be proven in larger multi-centre studies.