Personalized tumor combination therapy optimization using the single-cell transcriptome.

BACKGROUND: The precise characterization of individual tumors and immune microenvironments using transcriptome sequencing has provided a great opportunity for successful personalized cancer treatment. However, the cancer treatment response is often characterized by in vitro assays or bulk transcriptomes that neglect the heterogeneity of malignant tumors in vivo and the immune microenvironment, motivating the need to use single-cell transcriptomes for personalized cancer treatment. METHODS: Here, we present comboSC, a computational proof-of-concept study to explore the feasibility of personalized cancer combination therapy optimization using single-cell transcriptomes. ComboSC provides a workable solution to stratify individual patient samples based on quantitative evaluation of their personalized immune microenvironment with single-cell RNA sequencing and maximize the translational potential of in vitro cellular response to unify the identification of synergistic drug/small molecule combinations or small molecules that can be paired with immune checkpoint inhibitors to boost immunotherapy from a large collection of small molecules and drugs, and finally prioritize them for personalized clinical use based on bipartition graph optimization. RESULTS: We apply comboSC to publicly available 119 single-cell transcriptome data from a comprehensive set of 119 tumor samples from 15 cancer types and validate the predicted drug combination with literature evidence, mining clinical trial data, perturbation of patient-derived cell line data, and finally in-vivo samples. CONCLUSIONS: Overall, comboSC provides a feasible and one-stop computational prototype and a proof-of-concept study to predict potential drug combinations for further experimental validation and clinical usage using the single-cell transcriptome, which will facilitate and accelerate personalized tumor treatment by reducing screening time from a large drug combination space and saving valuable treatment time for individual patients. A user-friendly web server of comboSC for both clinical and research users is available at www.combosc.top . The source code is also available on GitHub at https://github.com/bm2-lab/comboSC .

Molecular bases of morphologically diffused tumors across multiple cancer types.

Gastric cancer has two distinct subtypes: the diffuse (DGC) and the intestinal (IGC) subtypes. Morphologically, the former each consists of numerous scattered tiny tumors while the latter each has one or a few solid biomasses. The former tends to be more aggressive and takes place in younger patients than the latter. While these have long been documented, little is known about the underlying causes. Our hypothesis is that the level of sialic acid (SA) accumulation on the cancer cell surfaces is a key reason for the observed differences. Our transcriptomic data-based analyses provide evidence that (i) DGCs tend to deploy more SAs on cancer cell surfaces than IGCs; (ii) this gives rise to considerably stronger cell-cell electrostatic repulsion in DGCs due to the negative charge that each SA carries; and (iii) such repulsion drives stronger cell protrusion and metastasis. Similar observations as well as our transcriptomic data-based predictions hold for multiple other cancer types, namely breast, lung, prostate plus liver and thyroid cancers, each known to have diffuse-like vs. non-diffused subtypes as well as more aggressive behaviors like DGCs vs. IGCs. Hence, we speculate that the discovery presented here applies not only to gastric cancer but multiple and even potentially all cancer types having diffuse-like and non-diffused subtypes.

The tumor therapy landscape of synthetic lethality.

Synthetic lethality is emerging as an important cancer therapeutic paradigm, while the comprehensive selective treatment opportunities for various tumors have not yet been explored. We develop the Synthetic Lethality Knowledge Graph (SLKG), presenting the tumor therapy landscape of synthetic lethality (SL) and synthetic dosage lethality (SDL). SLKG integrates the large-scale entity of different tumors, drugs and drug targets by exploring a comprehensive set of SL and SDL pairs. The overall therapy landscape is prioritized to identify the best repurposable drug candidates and drug combinations with literature supports, in vitro pharmacologic evidence or clinical trial records. Finally, cladribine, an FDA-approved multiple sclerosis treatment drug, is selected and identified as a repurposable drug for treating melanoma with CDKN2A mutation by in vitro validation, serving as a demonstrating SLKG utility example for novel tumor therapy discovery. Collectively, SLKG forms the computational basis to uncover cancer-specific susceptibilities and therapy strategies based on the principle of synthetic lethality.

The chromatin remodeling protein INO80 contributes to the removal of H2A.Z at the p53-binding site of the p21 gene in response to doxorubicin.

Transcriptional activation of p21 (cyclin-dependent kinase inhibitor 1A) due to DNA damage often alters the distribution of histone variant H2A.Z at the p21 gene. However, whether the human INO80 complex regulates changes in H2A.Z at the p21 promoter is unclear. We show here that activation of p21 expression by doxorubicin (Doxo) in U2OS cells is required for removal of H2A.Z by INO80 at the p53-binding site proximal region (-2.2 kb) of the p21 promoter. A purified INO80 complex, but not the INO80E653Q mutant-complex, which lost DNA-sliding activity, is mainly responsible for removing H2A.Z from reconstituted nucleosomes in vitro. This activity was enhanced with MOF-mediated histone acetylation, suggesting that INO80 more readily removes H2A.Z from loosened nucleosomes. Also, co-occupancy of INO80 and H2A.Z -2.2 kb upstream of the p21 transcriptional start site (TSS) was observed. H2A.Z at this region was removed in a short time after Doxo treatment and activated p21 expression. However, p21 induction was inhibited by INO80 knockdown by delaying H2A.Z removal, indicating the need for INO80. Moreover, shMOF-mediated histone acetylation reduced recruitment of INO80 -2.2 kb upstream of p21 TSS and inhibited the removal of H2A.Z in Doxo-treated cells. These data provide new insights into the transcriptional regulation of p21 by the INO80 complex.

O-Linked N-acetylglucosamine transferase 1 regulates global histone H4 acetylation via stabilization of the nonspecific lethal protein NSL3.

The human males absent on the first (MOF)-containing histone acetyltransferase nonspecific lethal (NSL) complex comprises nine subunits including the O-linked N-acetylglucosamine (O-GlcNAc) transferase, isoform 1 (OGT1). However, whether the O-GlcNAc transferase activity of OGT1 controls histone acetyltransferase activity of the NSL complex and whether OGT1 physically interacts with the other NSL complex subunits remain unclear. Here, we demonstrate that OGT1 regulates the activity of the NSL complex by mainly acetylating histone H4 Lys-16, Lys-5, and Lys-8 via O-GlcNAcylation and stabilization of the NSL complex subunit NSL3. Knocking down or overexpressing OGT1 in human cells remarkably affected the global acetylation of histone H4 residues Lys-16, Lys-5, and Lys-8. Because OGT1 is a subunit of the NSL complex, we also investigated the function of OGT1 in this complex. Co-transfection/co-immunoprecipitation experiments combined with in vitro O-GlcNAc transferase assays confirmed that OGT1 specifically binds to and O-GlcNAcylates NSL3. In addition, wheat germ agglutinin affinity purification verified the occurrence of O-GlcNAc modification on NSL3 in cells. Moreover, O-GlcNAcylation of NSL3 by wild-type OGT1 (OGT1-WT) stabilized NSL3. This stabilization was lost after co-transfection of NSL3 with an OGT1 mutant, OGT1C964A, that lacks O-GlcNAc transferase activity. Furthermore, stabilization of NSL3 by OGT1-WT significantly increased the global acetylation levels of H4 Lys-5, Lys-8, and Lys-16 in cells. These results suggest that OGT1 regulates the activity of the NSL complex by stabilizing NSL3.