👤 Claudia Langlais

The PRO-CTCAE provides patient-reported data on symptomatic AEs. A summary metric-the ACS-reflecting total AE burden can be calculated by averaging AE-level composite scores at a given timepoint for each participant. This study investigated the psychometric properties and interpretability of this PRO-CTCAE ACS in patients with breast, lung, or head/neck cancers. We conducted a secondary analysis of a PRO-CTCAE validation dataset comprising 940 adults undergoing chemotherapy or radiation therapy (clinicaltrials.gov: NCT02158637). We focused on empirically recommended symptom terms for three cancer sites. Analyses included Spearman's correlations, coefficient alpha, and eigenvalues from the correlation matrices, confirmatory factor analysis (CFA), and principal component analysis (PCA). Latent profile analysis (LPA) was used to assess ACS interpretability in the lung cohort. Mean composite score inter-correlations were moderate (0.30-0.35), and coefficient alphas were high (0.81-0.91). Eigenvalue ratios and CFA supported retention of a single factor/component, with suitable model fit indices. ACS correlated highly with factor scores and the first principal component from the PCA. Reduced sets of terms produced reliable scores that closely approximated the full set scores and aligned with external criteria. LPA in the lung subgroup identified four latent classes; ACS differentiated high vs. low symptom burden groups but did not distinguish the two groups expressing distinct symptom profiles. The ACS demonstrated structural validity through adequately fitting linear factor models and effectively summarized symptomatic AE burden. However, similar ACS values may mask clinically distinct symptomatic AE profiles, underscoring the value of both summary metrics and profile-based approaches. Show less

The CCR4-NOT complex plays an important role in the translational repression and deadenylation of mRNAs. However, little is known about the specific roles of interacting factors. We demonstrate that the DEAD-box helicases eIF4A2 and DDX6 interact directly with the MA3 and MIF domains of CNOT1 and compete for binding. Furthermore, we now show that incorporation of eIF4A2 into the CCR4-NOT complex inhibits CNOT7 deadenylation activity in contrast to DDX6 which enhances CNOT7 activity. Polyadenylation tests (PAT) on endogenous mRNAs determined that eIF4A2 bound mRNAs have longer poly(A) tails than DDX6 bound mRNAs. Immunoprecipitation experiments show that eIF4A2 does not inhibit CNOT7 association with the CCR4-NOT complex but instead inhibits CNOT7 activity. We identified a CCR4-NOT interacting factor, TAB182, that modulates helicase recruitment into the CCR4-NOT complex, potentially affecting the outcome for the targeted mRNA. Together, these data show that the fate of an mRNA is dependent on the specific recruitment of either eIF4A2 or DDX6 to the CCR4-NOT complex which results in different pathways for translational repression and mRNA deadenylation. Show less