Protocol to analyze immune cells in the tumor microenvironment by transcriptome using machine learning.

Immunotherapy is a promising strategy to treat cancer. Here, we present a protocol for analyzing the transcriptome-based phenotypic alterations and immune cell infiltration in the tumor microenvironment. We describe steps for integrating single-cell RNA sequencing (scRNA-seq) data, comparing phenotypes and origins of mononuclear phagocytes, inferring the differentiation trajectory and infiltration process, and identifying infiltration-associated genes using machine learning. We then detail procedures for exploring the impact of these genes in prognosis through the integrated microarray and bulk RNA-seq data to obtain potential drug targets. For complete details on the use and execution of this protocol, please refer to Liao et al.1.

Early Emerging SARS-CoV-2 Spike Mutants Are Diversified in Virologic Properties but Elicit Compromised Antibody Responses.

Despite the effective antivirals and vaccines, COVID-19 remains a public health concern. The mutations that occurred during the early stage of the pandemic can be valuable in assessing the viral fitness and evolutionary trajectory. In this study, we analyzed a panel of 2969 spike sequences deposited in GISAID before April 2020 and characterized nine representative spike single-point mutants in detail. Compared with the WA01/2020, most (8 out of 9) mutants demonstrated an equivalent or diminished protein expression or processing, pseudovirus infectivity, and cell-cell fusion. Interestingly, most of the mutants in native form elicited minimum antibody responses in mice despite unaltered CD4+ and CD8+ T cell responses. The mutants remained sensitive to the antisera and the type I interferon. Taken together, these data suggest that the early emerging mutants are virologically divergent, and some of which showed transmission fitness. Our findings have important implications for the retrospective tracing of the early SARS-CoV-2 transmission and future pandemic preparedness.

MIF is a critical regulator of mononuclear phagocytic infiltration in hepatocellular carcinoma.

Immunotherapy targeting tumor-associated macrophages (TAMs) is a promising approach to treating cancer. However, the limited drug targets and ambiguous mechanisms impede the development of clinical immunotherapy strategies. To elucidate the underlying processes involved in mononuclear phagocyte (MNP) infiltration and phenotypic changes in hepatocellular carcinoma (HCC), we integrated single-cell RNA-sequencing data from 100,030 cells derived from patients with HCC and healthy individuals and compared the phenotypes and origins of the MNPs in the tumor core, tumor periphery, adjacent normal tissue, and healthy liver samples. Using machine learning and multi-omics analyses, we identified 445 infiltration-associated genes and potential drug targets affecting this process. Through in vitro experiments, we found that the expression of macrophage migration inhibitory factor (MIF) is the upstream regulator of secreted phosphoprotein 1 (SPP1) and promote migration in TAMs. Our findings also indicate that MIF promotes tumor metastasis and invasion and is a promising potential target for treating HCC.