Research into flywheel (FW) resistance training and force–velocity–power (F–v–P) profiling has recently gained attention. Ground reaction force (GRF) and velocity (v) during FW squats can be predicted from shaft rotational data. Our study aimed to compare the inter-set reliability of GRF, v, and F–v–P relationship output variables calculated from force plates and linear encoder (presumed gold-standard) and rotary encoder data. Fifty participants performed two sets of FW squats at four inertias. Peak and mean concentric and eccentric GRF, v, and F–v–P outcomes from mean variables during the concentric phase of the squat were calculated. Good to excellent reliability was found for GRF and v (ICC > 0.85), regardless of the measure and the variable type. The F–v–P outcomes showed moderate to good reliability (ICC > 0.74). Inter-measure bias (p < 0.05) was found in the majority of GRF and v variables, as well as for all the calculated F–v–P outcomes (trivial to large TEs) with very large to perfect correlations for v (r 0.797–0.948), GRF (r 0.712–0.959), and, finally, F–v–P outcomes (ICC 0.737–0.943). Rotary encoder overestimated the force plates and linear encoder variables, and the differences were dependent on the level of inertia. Despite high reliability, FW device users should be aware of the discrepancy between the measures.

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IntroductionMost predictive biomarkers approved for clinical use measure single analytes such as genetic alteration or protein overexpression. We developed and validated a novel biomarker with the aim of achieving broad clinical utility. The Xerna™ TME Panel is a pan-tumor, RNA expression-based classifier, designed to predict response to multiple tumor microenvironment (TME)-targeted therapies, including immunotherapies and anti-angiogenic agents.MethodsThe Panel algorithm is an artificial neural network (ANN) trained with an input signature of 124 genes that was optimized across various solid tumors. From the 298-patient training data, the model learned to discriminate four TME subtypes: Angiogenic (A), Immune Active (IA), Immune Desert (ID), and Immune Suppressed (IS). The final classifier was evaluated in four independent clinical cohorts to test whether TME subtype could predict response to anti-angiogenic agents and immunotherapies across gastric, ovarian, and melanoma datasets.ResultsThe TME subtypes represent stromal phenotypes defined by angiogenesis and immune biological axes. The model yields clear boundaries between biomarker-positive and -negative and showed 1.6-to-7-fold enrichment of clinical benefit for multiple therapeutic hypotheses. The Panel performed better across all criteria compared to a null model for gastric and ovarian anti-angiogenic datasets. It also outperformed PD-L1 combined positive score (&gt;1) in accuracy, specificity, and positive predictive value (PPV), and microsatellite-instability high (MSI-H) in sensitivity and negative predictive value (NPV) for the gastric immunotherapy cohort.DiscussionThe TME Panel’s strong performance on diverse datasets suggests it may be amenable for use as a clinical diagnostic for varied cancer types and therapeutic modalities.

The most utilized targeted therapies in colorectal cancer (CRC) are focused on EGFR inhibition and anti-angiogenesis. In the ~5% of patients with microsatellite instability (MSI-H) or high tumor mutational burden (TMB), checkpoint inhibitors (CPIs) have been approved. Oncxerna has developed an RNA expression-based approach to characterize the ‘dominant' biology of a patient's tumor microenvironment with the diagnostic hypothesis to prospectively pair those patients with therapies and known mechanism of action that directly target these biologies. We developed an RNA-based gene expression panel (TME Panel-1) and machine learning (ML) algorithms to prospectively predict a patient's response to anti-angiogenesis or immune modulators, such as CPIs. In this study, we explore the potential of the TME Panel-1 to identify dominant biologies present in colorectal cancer specimens procured from the Wood-Hudson Cancer Research Lab. Total RNA expression counts from FFPE slides were analyzed with the ML algorithms and used to assign each sample into one of four subgroups. The respective prevalence of the subgroups are similar to those observed in gastric cancer and ovarian cancer samples, suggesting that the TME-Panel 1 has potential to be used to develop pan-tumor diagnostics. We will present these results, correlations with clinical outcomes and other relevant biomarkers for CRC. In summary, we conclude that RNA-based descriptors of biology may be a useful approach to enrich for better response to targeted therapies whose mechanism of action is to modify the TME biology. Citation Format: Kristen Strand-Tibbitts, Kerry Culm-Merdek, Valerie Chamberlain Santps, Laura Benjamin, Julia Carter, Larry Douglass, Roman Luštrik, Robert Cvitkovič, Luka Ausec, Rafael Rosengarten. Development of an RNA based diagnostic panel to the tumor microenvironment to match cancer therapies for colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 348.

The purpose of our study was to examine the practical application of the progressive resistance exercise protocol among older adult women using a custom-made low-row flywheel (FW) device. The objective was to compare the effects of the FW device exercise protocol to the traditional gravitybased (GB) one, with regards to older adult women's physical abilities, i.e. shoulder mobility, upper body low-row strength, velocity, power and, lastly, trunk extensor endurance. Fourty healthy older adult women (old: 66 ± 5 years; height: 1,62 m; weight: 73,7 kg; body mass index: 28 ± 6 kg/m2 ) were randomly assigned to the FW low-row or Pulley lowrow group. They underwent eight weeks of resistance exercise. We used a two-way ANOVA for repeated measures and standardized effect sizes (ES) comparison to assess exercise-related differences within and between groups. The results showed significant improvement of resistance exercise parameters during the eight-week resistance exercise protocol, regardless of the group. Moreover, we found no statistically important inter-group differences in improvement of shoulder mobility, upper body strength, velocity, power and trunk extensor endurance. Nevertheless, the highest ES in favour of FW low-row group was found when comparing the eccentric peak power changes. We have demonstrated that FW load could be as effective and useful as GB pulley row-row resistance exercise modality. Further research is required, where the concept of the eccentric overload and muscle power enhancement with the use of FW devices for older adult population should be utilized.