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Simple Summary: Cancer arises through the accumulation of somatic mutations in key biological pathways. This paper aims to develop a probabilistic approach to delineate the temporal order of mutations during cancer development based on mutation profile data from a cohort of patients. A unique feature of our method is that it incorporates intra-tumor heterogeneity (ITH) information, which refers to the heterogeneous cell populations within a tumor and characterizes the evolutionary history of the tumor. We showed that by integrating ITH, pathways, and functional annotation information, our method yielded high accuracy in inferring the temporal order of pathway mutations during carcinogenesis. The development of cancer involves the accumulation of somatic mutations in several essential biological pathways. Delineating the temporal order of pathway mutations during tumorigenesis is crucial for comprehending the biological mechanisms underlying cancer development and identifying potential targets for therapeutic intervention. Several computational and statistical methods have been introduced for estimating the order of somatic mutations based on mutation profile data from a cohort of patients. However, one major issue of current methods is that they do not take into account intra-tumor heterogeneity (ITH), which limits their ability to accurately discern the order of pathway mutations. To address this problem, we propose PATOPAI, a probabilistic approach to estimate the temporal order of mutations at the pathway level by incorporating ITH information as well as pathway and functional annotation information of mutations. PATOPAI uses a maximum likelihood approach to estimate the probability of pathway mutational events occurring in a specific sequence, wherein it focuses on the orders that are consistent with the phylogenetic structure of the tumors. Applications to whole exome sequencing data from The Cancer Genome Atlas (TCGA) illustrate our method's ability to recover the temporal order of pathway mutations in several cancer types. [ABSTRACT FROM AUTHOR]

Immune checkpoint inhibition targeting the PD-1/PD-L1 pathway has become a powerful clinical strategy for treating cancer, but its efficacy is complicated by various resistance mechanisms. One of the reasons for the resistance is the internalization and recycling of PD-L1 itself upon antibody binding. The inhibition of lysosome-mediated degradation of PD-L1 is critical for preserving the amount of PD-L1 recycling back to the cell membrane. In this study, we find that Hsc70 promotes PD-L1 degradation through the endosome-lysosome pathway and reduces PD-L1 recycling to the cell membrane. This effect is dependent on Hsc70-PD-L1 binding which inhibits the CMTM6-PD-L1 interaction. We further identify an Hsp90α/β inhibitor, AUY-922, which induces Hsc70 expression and PD-L1 lysosomal degradation. Either Hsc70 overexpression or AUY-922 treatment can reduce PD-L1 expression, inhibit tumor growth and promote anti-tumor immunity in female mice; AUY-922 can further enhance the anti-tumor efficacy of anti-PD-L1 and anti-CTLA4 treatment. Our study elucidates a molecular mechanism of Hsc70-mediated PD-L1 lysosomal degradation and provides a target and therapeutic strategies for tumor immunotherapy. Hsc70 (heat shock protein family A member 8) is a cytoplasmic chaperone protein involved in endosomal micro-autophagy and chaperone-mediated autophagy. Here the authors report that Hsc70 promotes lysosomal degradation of PD-L1 and that its overexpression promotes anti-tumor immune responses in preclinical cancer models. [ABSTRACT FROM AUTHOR]