BackgroundTo explore the relationship between future self-continuity and problematic mobile video gaming among Chinese college students and to examine the serial mediation of consideration of future consequences and state self-control capacity on the association between future self-continuity and problematic mobile video gaming, based on Identity-Based Motivation Theory.MethodsThe Problematic Mobile Video Gaming Scale, Future Self-continuity Scale, Consideration of Future Consequences Scale, and Short Version of State Self-control Capacity Scale were administered to a sample comprising 800 college students (338 males accounting for 42.3%). Multivariate analysis and latent variables analysis were utilized to explore the separate mediating role consideration of future consequences and state self-control capacity played in the association between future self-continuity and problematic mobile video gaming, and their serial mediation also was investigated. The Bootstrap method was employed to test the significance of these mediation effects.ResultsThe negative association between future self-continuity and problematic mobile video gaming was moderately found. Students with increased consideration of future consequences from higher levels of future self-continuity have decreased their problematic mobile video gaming. Future self-continuity significantly positively predicted state self-control capacity, which in turn significantly negatively predicted problematic mobile video gaming. The serial mediation was also found.ConclusionThe findings revealed why differences in identification with the current and future selves become influencing factors in problematic mobile video gaming. This study observed the mediating role that consideration of future consequences and state self-control capacity play in the association between future self-continuity and problematic mobile video gaming.

In the US, the majority of cancer samples analyzed are from white people, leading to biases in racial and ethnic treatment outcomes. Colorectal cancer (CRC) incidence and mortality rates are high in Alabama African Americans (AAs) and Oklahoma American Indians (AIs). We hypothesized that differences between racial groups may partially explain these disparities. Thus, we compared transcriptomic profiles of CRCs of Alabama AAs, Oklahoma AIs, and white people from both states. Compared to CRCs of white people, CRCs of AAs showed (a) higher expression of cytokines and vesicle trafficking toward modulated antitumor-immune activity, and (b) lower expression of the ID1/BMP/SMAD axis, IL22RA1, APOBEC3, and Mucins; and AIs had (c) higher expression of PTGS2/COX2 (an NSAID target/pro-oncogenic inflammation) and splicing regulators, and (d) lower tumor suppressor activities (e.g., TOB2, PCGF2, BAP1). Therefore, targeting strategies designed for white CRC patients may be less effective for AAs/AIs. These findings illustrate needs to develop optimized interventions to overcome racial CRC disparities.

Immune checkpoint inhibitors (ICI) are highly effective in specific cancers where canonical markers of antitumor immunity are used for patient selection. Improved predictors of T cell-inflammation are needed to identify ICI-responsive tumor subsets in additional cancer types. We investigated associations of a 4-chemokine expression signature (c-Score: CCL4, CCL5, CXCL9, CXCL10) with metrics of antitumor immunity across tumor types. Across cancer entities from The Cancer Genome Atlas, subgroups of tumors displayed high expression of the c-Score (c-Scorehi) with increased expression of immune checkpoint (IC) genes and transcriptional hallmarks of the cancer-immunity cycle. There was an incomplete association of the c-Score with high tumor mutation burden (TMB), with only 15% of c-Scorehi tumors displaying ≥10 mutations per megabase. In a heterogeneous pan-cancer cohort of 82 patients, with advanced and previously treated solid cancers, c-Scorehi tumors had a longer median time to progression (103 versus 72 days, P = 0.012) and overall survival (382 versus 196 days, P = 0.038) following ICI therapy initiation, compared to patients with low c-Score expression. We also found c-Score stratification to outperform TMB assignment for overall survival prediction (HR = 0.42 [0.22–0.79], P = 0.008 versus HR = 0.60 [0.29-1.27], P = 0.18, respectively). Assessment of the c-Score using the TIDE and PredictIO databases, which include ICI treatment outcomes from 10 tumor types, provided further support for the c-Score as a predictive ICI therapeutic biomarker. In summary, the c-Score identifies patients with hallmarks of T cell-inflammation and potential response to ICI treatment across cancer types, which is missed by TMB assignment.