MHC Hammer reveals genetic and non-genetic HLA disruption in cancer evolution

Disruption of the class I human leukocyte antigen (HLA) molecules has important implications for immune evasion and tumor evolution. We developed major histocompatibility complex loss of heterozygosity (LOH), allele-specific mutation and measurement of expression and repression (MHC Hammer). We identified extensive variability in HLA allelic expression and pervasive HLA alternative splicing in normal lung and breast tissue. In lung TRACERx and lung and breast TCGA cohorts, 61% of lung adenocarcinoma (LUAD), 76% of lung squamous cell carcinoma (LUSC) and 35% of estrogen receptor-positive (ER+) cancers harbored class I HLA transcriptional repression, while HLA tumor-enriched alternative splicing occurred in 31%, 11% and 15% of LUAD, LUSC and ER+ cancers. Consistent with the importance of HLA dysfunction in tumor evolution, in LUADs, HLA LOH was associated with metastasis and LUAD primary tumor regions seeding a metastasis had a lower effective neoantigen burden than non-seeding regions. These data highlight the extent and importance of HLA transcriptomic disruption, including repression and alternative splicing in cancer evolution

Short-term uncertainty in the dispatch of energy resources for VPP: A novel rolling horizon model based on stochastic programming

The intermittent nature of distributed energy resources introduces new degrees of uncertainty in the operation of energy systems; hence, short-term decisions can no longer be considered fully deterministic. In this article, an energy management system (EMS) was proposed to optimize the market participation and the real-time operation of a virtual power plant (VPP) composed of photovoltaic generators, non-flexible loads, and storage systems (e-vehicle, stationary battery, and thermal storage). The market bidding process was optimized through a two-stage stochastic formulation, which considered the day-ahead forecast uncertainty to minimize the energy cost and make available reserve margins in the ancillary service market. The real-time management of regulating resources was obtained through an innovative rolling horizon stochastic programming model, taking into account the effects of short-term uncertainties. Numerical simulations were carried out to demonstrate the effectiveness of the proposed EMS. The architecture proved to be effective in managing several distributed resources, enabling the provision of ancillary services to the power system. In particular, the model developed allowed an increase in the VPP's profits of up to 11% and a reduction in the energy imbalance of 25.1% compared to a deterministic optimization