Non-small cell lung cancer patients treated with Anti-PD1 immunotherapy show distinct microbial signatures and metabolic pathways according to progression-free survival and PD-L1 status

Due to the high variance in response rates concerning anti-PD1 immunotherapy (IT), there is an unmet need to discover innovative biomarkers to predict immune checkpoint inhibitor (ICI)-efficacy. Our study included 62 Caucasian advanced-stage non-small cell lung cancer (NSCLC) patients treated with anti-PD1 ICI. Gut bacterial signatures were evaluated by metagenomic sequencing and correlated with progression-free survival (PFS), PD-L1 expression and other clinicopathological parameters. We confirmed the predictive role of PFS-related key bacteria with multivariate statistical models (Lasso- and Cox-regression) and validated on an additional patient cohort (n = 60). We find that alpha-diversity showed no significant difference in any comparison. However, there was a significant difference in beta-diversity between patients with long- (>6 months) vs. short (≤6 months) PFS and between chemotherapy (CHT)-treated vs. CHT-naive cases. Short PFS was associated with increased abundance of Firmicutes (F) and Actinobacteria phyla, whereas elevated abundance of Euryarchaeota was specific for low PD-L1 expression. F/Bacteroides (F/B) ratio was significantly increased in patients with short PFS. Multivariate analysis revealed an association between Alistipes shahii, Alistipes finegoldii, Barnesiella visceriola, and long PFS. In contrast, Streptococcus salivarius, Streptococcus vestibularis, and Bifidobacterium breve were associated with short PFS. Using Random Forest machine learning approach, we find that taxonomic profiles performed superiorly in predicting PFS (AUC = 0.74), while metabolic pathways including Amino Acid Synthesis and Fermentation were better predictors of PD-L1 expression (AUC = 0.87). We conclude that specific metagenomic features of the gut microbiome, including bacterial taxonomy and metabolic pathways might be suggestive of ICI efficacy and PD-L1 expression in NSCLC patients.

Quantification of Training Load Relative to Match Load of Youth National Team Soccer Players

BACKGROUND

Previous studies have examined the training load relative to match load in club settings. The aims of this study were to (1) quantify the external training load relative to match load in days before a subsequent international game and (2) examine the cumulative training load in relation to match load of U-17 national team field soccer players.

HYPOTHESIS

Volume and intensity load parameters will vary between trainings; the farthermost trainings have the highest load gradually decreasing toward the match.

STUDY DESIGN

Prospective cohort study.

LEVEL OF EVIDENCE

Level 4.

METHODS

External training load data were collected from 84 youth national team players using global positioning technology between 2016 and 2020. In the national team setting, training load data were obtained from 3 days before the actual match day (MD-3, MD-2, MD-1 days) and analyzed with regard to the number of days up to the game. Volume and intensity parameters were calculated as a percentage of the subsequent match load.

RESULTS

Significant differences were found between MD-1 and MD-2, as well as between MD-1 and MD-3 for most volume parameters (P < 0.01; effect sizes [ESs] 0.68-0.99) and high-intensity distance (P < 0.002; ES 0.67 and 0.73) and maximum velocity (P < 0.002; ES 0.82) as intensity parameters. Most cumulative values were significantly different from total duration (P < 0.001, common language ES 0.80-0.96).

CONCLUSION

The training volume gradually decreased as match day approached, with the highest volume occurring on MD-3. Intensity variables, such as maximum velocity, high-intensity accelerations, and meterage per minute were larger in MD-1 training relative to match load. Training volume was lowest in MD-1 trainings and highest in MD-3 trainings; intensity however varies between training days.

CLINICAL RELEVANCE

The findings of this study may help to understand the special preparational demands of international matches, highlighting the role of decreased training volume and increased intensity.

Factors Influencing Creatine Kinase Response in Youth National Team Soccer Players

BACKGROUND

Previous studies have examined the relationship between external training load and creatine kinase (CK) response after soccer matches in adults. This study aimed to build training- and match-specific CK prediction models for elite youth national team soccer players.

HYPOTHESIS

Training and match load will have different effects on the CK response of elite youth soccer players, and there will be position-specific differences in the most influential external and internal load parameters on the CK response.

STUDY DESIGN

Prospective cohort study.

LEVEL OF EVIDENCE

Level 4.

METHODS

Forty-one U16-U17 youth national team soccer players were measured over an 18-month period. Training and match load were monitored with global positioning system devices. Individual CK values were measured from whole blood every morning in training camps. The dataset consisted of 1563 data points. Clustered prediction models were used to examine the relationship between external/internal load and consecutive CK changes. Clusters were built based on the playing position and activity type. The performance of the linear regression models was described by the R² and the root-mean-square error (RMSE, U/L for CK values).

RESULTS

The prediction models fitted similarly during games and training sessions (R² = 0.38-0.88 vs 0.6-0.77), but there were large differences based on playing positions. In contrast, the accuracy of the models was better during training sessions (RMSE = 81-135 vs 79-209 U/L). Position-specific differences were also found in the external and internal load parameters, which best explained the CK changes.

CONCLUSION

The relationship between external/internal load parameters and CK changes are position specific and might depend on the type of session (training or match). Morning CK values also contributed to the next day's CK values.

CLINICAL RELEVANCE

The relationship between position-specific external/internal load and CK changes can be used to individualize postmatch recovery strategies and weekly training periodization with a view to optimize match performance.