Development of a CD8+ T cell-based molecular classification for predicting prognosis and heterogeneity in triple-negative breast cancer by integrated analysis of single-cell and bulk RNA-sequencing

Cell-type-specific subtyping of epigenomes improves prognostic stratification of cancer

BACKGROUND

Most molecular classifications of cancer are based on bulk-tissue profiles that measure an average over many distinct cell types. As such, cancer subtypes inferred from transcriptomic or epigenetic data are strongly influenced by cell-type composition and do not necessarily reflect subtypes defined by cell-type-specific cancer-associated alterations, which could lead to suboptimal cancer classifications.

METHODS

To address this problem, we here propose the novel concept of cell-type-specific combinatorial clustering (CELTYC), which aims to group cancer samples by the molecular alterations they display in specific cell types. We illustrate this concept in the context of DNA methylation data of liver and kidney cancer, deriving in each case novel cancer subtypes and assessing their prognostic relevance against current state-of-the-art prognostic models.

RESULTS

In both liver and kidney cancer, we reveal improved cell-type-specific prognostic models, not discoverable using standard methods. In the case of kidney cancer, we show how combinatorial indexing of epithelial and immune-cell clusters define improved prognostic models driven by synergy of high mitotic age and altered cytokine signaling. We validate the improved prognostic models in independent datasets and identify underlying cytokine-immune-cell signatures driving poor outcome.

CONCLUSIONS

In summary, cell-type-specific combinatorial clustering is a valuable strategy to help dissect and improve current prognostic classifications of cancer in terms of the underlying cell-type-specific epigenetic and transcriptomic alterations.

GrB-Fc-KS49, an anti-EMP2 granzyme B fusion protein therapeutic alters immune cell infiltration and suppresses breast cancer growth

BACKGROUND

Granzyme B (GrB) is a key effector molecule, delivered by cytotoxic T lymphocytes and natural killer cells during immune surveillance to induce cell death. Fusion proteins and immunoconjugates represent an innovative therapeutic approach to specifically deliver a deadly payload to target cells. Epithelial membrane protein-2 (EMP2) is highly expressed in invasive breast cancer (BC), including triple-negative BC (TNBC), and represents an attractive therapeutic target.

METHODS

We designed a novel fusion protein (GrB-Fc-KS49) composed of an active GrB fused to an anti-EMP2 single-chain antibody tethered through the immunoglobulin G heavy chain (Fc) domain. We assessed the construct's GrB enzymatic activity, anti-EMP2 binding affinity, and cytotoxicity against a panel of BC cells. The construct's pharmacokinetics (PK), toxicity profile, and in vivo efficacy were also evaluated.

RESULTS

GrB-Fc-KS49 exhibited comparable GrB enzymatic activity to commercial GrB, as well as high affinity to an EMP2 peptide, with the dissociation constant in the picomolar range. The fusion protein rapidly internalized into EMP2+cancer cells and showed in vitro cytotoxicity to cell lines expressing surface EMP2, with half-maximal cytotoxicity (IC50) values below 100 nM for most positive lines. Ex vivo stability at 37°C indicated a half-life exceeding 96 hours while in vivo PK indicated a biexponential plasma clearance, with a moderate initial clearance (t1/2α=18.4 hours) and a much slower terminal clearance rate (t1/2β=73.1 hours). No toxicity was measured in a Chem16 panel between the control and the GrB-Fc-KS49. In vivo, the GrB-Fc-KS49 showed efficacy against a TNBC syngeneic (4T1/FLuc) mouse model, reducing tumor volume and cell proliferation and increasing cell death compared with controls. Treatment using an EMT6 mouse model confirmed these results. In addition to a significant impact on cell proliferation, GrB-Fc-KS49 treatment also resulted in a dramatic increase of tumor-infiltrating CD45+ cells and redistribution of tumor-associated macrophages. Transcriptomic analysis of tumors post-treatment confirmed the remodeling of the immune tumor microenvironment by the GrB-Fc-KS49 immunotoxin.

CONCLUSIONS

GrB-Fc-KS49 showed high specificity and cytotoxicity towards EMP2-positive cells. In vivo, it reduced tumor burden and increased the recruitment of immune cells into the tumor, suggesting that GrB-Fc-KS49 is a promising therapeutic candidate against BC.

Identifying MS4A6A+ macrophages as potential contributors to the pathogenesis of nonalcoholic fatty liver disease, periodontitis, and type 2 diabetes mellitus

Purpose

Concrete epidemiological evidence has suggested the mutually-contributing effect respectively between nonalcoholic fatty liver disease (NAFLD), type 2 diabetes mellitus (T2DM), and periodontitis (PD); however, their shared crosstalk mechanism remains an open issue.

Method

The NAFLD, PD, and T2DM-related datasets were obtained from the NCBI GEO repository. Their common differentially expressed genes (DEGs) were identified and the functional enrichment analysis performed by the DAVID platform determined relevant biological processes and pathways. Then, the STRING database established a PPI network of such DEGs and topological analysis through Cytoscape 3.7.1 software along with the machine-learning analysis by the least absolute shrinkage and selection operator (LASSO) algorithm screened out hub characteristic genes. Their efficacy was validated by external datasets using the receiver operating characteristic (ROC) curve, and gene expression and location of the most robust one was determined using single-cell sequencing and immunohistochemical staining. Finally, the promising drugs were predicted through the CTD database, and the CB-DOCK 2 and Pymol platform mimicked molecular docking.

Result

Intersection of differentially expressed genes from three datasets identified 25 shared DEGs of the three diseases, which were enriched in MHC II-mediated antigen presenting process. PPI network and LASSO machine-learning analysis determined 4 feature genes, of which the MS4A6A gene mainly expressed by macrophages was the hub gene and key immune cell type. Molecular docking simulation chosen fenretinide as the most promising medicant for MS4A6A+ macrophages.

Conclusion

MS4A6A+ macrophages were suggested to be important immune-related mediators in the progression of NAFLD, PD, and T2DM pathologies.

Innate immune cells: Key players of orchestra in modulating tumor microenvironment (TME)

The tumor microenvironment (TME) with vital role in cancer progression is composed of various cells such as endothelial cells, immune cells, and mesenchymal stem cells. In particular, innate immune cells such as macrophages, dendritic cells, myeloid-derived suppressor cells, neutrophils, innate lymphoid cells, γδT lymphocytes, and natural killer cells can either promote or suppress tumor progression when present in the TME. An increase in research on the cross-talk between the TME and innate immune cells will lead to new approaches for anti-tumoral therapeutic interventions. This review primarily focuses on the biology of innate immune cells and their main functions in the TME. In addition, it summarizes several innate immune-based immunotherapies that are currently tested in clinical trials.