Combined Inhibition of SHP2 and CXCR1/2 Promotes Antitumor T-cell Response in NSCLC.

SHP2 inhibitors (SHP2i) alone and in various combinations are being tested in multiple tumors with overactivation of the RAS/ERK pathway. SHP2 plays critical roles in normal cell signaling; hence, SHP2is could influence the tumor microenvironment. We found that SHP2i treatment depleted alveolar and M2-like macrophages, induced tumor-intrinsic CCL5/CXCL10 secretion, and promoted B and T lymphocyte infiltration in Kras- and Egfr-mutant non-small cell lung cancer (NSCLC). However, treatment also increased intratumor granulocytic myeloid-derived suppressor cells (gMDSC) via tumor-intrinsic, NFκB-dependent production of CXCR2 ligands. Other RAS/ERK pathway inhibitors also induced CXCR2 ligands and gMDSC influx in mice, and CXCR2 ligands were induced in tumors from patients on KRASG12C inhibitor trials. Combined SHP2 (SHP099)/CXCR1/2 (SX682) inhibition depleted a specific cluster of S100a8/9 hi gMDSCs, generated Klrg1 + CD8+ effector T cells with a strong cytotoxic phenotype but expressing the checkpoint receptor NKG2A, and enhanced survival in Kras- and Egfr-mutant models. Our results argue for testing RAS/ERK pathway/CXCR1/2/NKG2A inhibitor combinations in patients with NSCLC. SIGNIFICANCE: Our study shows that inhibiting the SHP2/RAS/ERK pathway triggers NFκB-dependent upregulation of CXCR2 ligands and recruitment of S100A8hi gMDSCs, which suppress T cells. Combining SHP2/CXCR2 inhibitors blocks gMDSC immigration, resulting in enhanced Th1 polarization, induced CD8+KLRG1+ effector T cells with high cytotoxic activity, and improved survival in multiple NSCLC models.This article is highlighted in the In This Issue feature, p. 1.

Correction: Association Between Improvement in Baseline Mood and Long-Term Use of a Mindfulness and Meditation App: Observational Study.

[This corrects the article DOI: 10.2196/12617.].

Characterizing Emotional State Transitions During Prolonged Use of a Mindfulness and Meditation App: Observational Study.

BACKGROUND: The increasing demand for mental health care, a lack of mental health care providers, and unequal access to mental health care services have created a need for innovative approaches to mental health care. Digital device apps, including digital therapeutics, that provide recommendations and feedback for dealing with stress, depression, and other mental health issues can be used to adjust mood and ultimately show promise to help meet this demand. In addition, the recommendations delivered through such apps can also be tailored to an individual's needs (ie, personalized) and thereby potentially provide greater benefits than traditional "one-size-fits-all" recommendations. OBJECTIVE: This study aims to characterize individual transitions from one emotional state to another during the prolonged use of a digital app designed to provide a user with guided meditations based on their initial, potentially negative, emotional state. Understanding the factors that mediate such transitions can lead to improved recommendations for specific mindfulness and meditation interventions or activities (MMAs) provided in mental health apps. METHODS: We analyzed data collected during the use of the Stop, Breathe & Think (SBT) mindfulness app. The SBT app prompts users to input their emotional state before and immediately after engaging with MMAs recommended by the app. Data were collected from more than 650,000 SBT users engaging in nearly 5 million MMAs. We limited the scope of our analysis to users with 10 or more MMA sessions that included at least 6 basal emotional state evaluations. Using clustering techniques, we grouped emotions recorded by individual users and then applied longitudinal mixed effect models to assess the associations between individual recommended MMAs and transitions from one group of emotions to another. RESULTS: We found that basal emotional states have a strong influence on transitions from one emotional state to another after MMA engagement. We also found that different MMAs impact these transitions, and many were effective in eliciting a healthy transition but only under certain conditions. In addition, we observed gender and age effects on these transitions. CONCLUSIONS: We found that the initial emotional state of an SBT app user determines the type of SBT MMAs that will have a favorable effect on their transition from one emotional state to another. Our results have implications for the design and use of guided mental health recommendations for digital device apps.

Investigation of associations between Piezo1 mechanoreceptor gain-of-function variants and glaucoma-related phenotypes in humans and mice.

Glaucoma disproportionately affects individuals of African descent. Prior studies of the PIEZO1 mechanoreceptor have suggested a possible role in glaucoma pathophysiology. Here, we investigated associations between a Piezo1 gain-of-function variant common in individuals of African descent with glaucoma-related phenotypes. We analyzed whole genome sequences to identify Piezo1 variants and their frequencies among 1565 human participants. For the most common variant (e756del), we compared phenotypes between heterozygotes, homozygotes, and wildtypes. Longitudinal mixed effects models of visual field mean deviation (MD) and retinal nerve fiber layer (RNFL) thickness were used to evaluate progression. Based on trends in the models, further investigation was conducted using Piezo1 gain-of-function mice. About 30% of African descent individuals had at least one e756del allele. There were trends suggesting e756del was associated with higher IOPs, thinner RNFLs, lower optic nerve head capillary densities, and greater decreases in MD and RNFL thickness over time, but these did not reach statistical significance. Among mice, increased Piezo1 activity was not significantly associated with IOP or retinal ganglion cell density. Our study confirms that the Piezo1 e756del gain-of-function variant is a frequent polymorphism present in African descent individuals but is unrelated to examined differences in glaucoma phenotypes. Ongoing work is needed to elucidate the role of Piezo1-mediated mechanotransduction in glaucoma.

Association Between Improvement in Baseline Mood and Long-Term Use of a Mindfulness and Meditation App: Observational Study.

BACKGROUND: The use of smartphone apps to monitor and deliver health care guidance and interventions has received considerable attention recently, particularly with regard to behavioral disorders, stress relief, negative emotional state, and poor mood in general. Unfortunately, there is little research investigating the long-term and repeated effects of apps meant to impact mood and emotional state. OBJECTIVE: We aimed to investigate the effects of both immediate point-of-intervention and long-term use (ie, at least 10 engagements) of a guided meditation and mindfulness smartphone app on users' emotional states. Data were collected from users of a mobile phone app developed by the company Stop, Breathe & Think (SBT) for achieving emotional wellness. To explore the long-term effects, we assessed changes in the users' basal emotional state before they completed an activity (eg, a guided meditation). We also assessed the immediate effects of the app on users' emotional states from preactivity to postactivity. METHODS: The SBT app collects information on the emotional state of the user before and after engagement in one or several mediation and mindfulness activities. These activities are recommended and provided by the app based on user input. We considered data on over 120,000 users of the app who collectively engaged in over 5.5 million sessions with the app during an approximate 2-year period. We focused our analysis on users who had at least 10 engagements with the app over an average of 6 months. We explored the changes in the emotional well-being of individuals with different emotional states at the time of their initial engagement with the app using mixed-effects models. In the process, we compared 2 different methods of classifying emotional states: (1) an expert-defined a priori mood classification and (2) an empirically driven cluster-based classification. RESULTS: We found that among long-term users of the app, there was an association between the length of use and a positive change in basal emotional state (4% positive mood increase on a 2-point scale every 10 sessions). We also found that individuals who were anxious or depressed tended to have a favorable long-term emotional transition (eg, from a sad emotional state to a happier emotional state) after using the app for an extended period (the odds ratio for achieving a positive emotional state was 3.2 and 6.2 for anxious and depressed individuals, respectively, compared with users with fewer sessions). CONCLUSIONS: Our analyses provide evidence for an association between both immediate and long-term use of an app providing guided meditations and improvements in the emotional state.