Complement and coagulation cascades pathway-related signature as a predictor of immunotherapy in metastatic urothelial cancer

Proteomic profiling and biomarker discovery for predicting the response to PD-1 inhibitor immunotherapy in gastric cancer patients

Background: Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment; however, a significant proportion of gastric cancer (GC) patients do not respond to this therapy. Consequently, there is an urgent need to elucidate the mechanisms underlying resistance to ICIs and identify robust biomarkers capable of predicting the response to ICIs at treatment initiation. Methods: In this study, we collected GC tissues from 28 patients prior to the administration of anti-programmed death 1 (PD-1) immunotherapy and conducted protein quantification using high-resolution mass spectrometry (MS). Subsequently, we analyzed differences in protein expression, pathways, and the tumor microenvironment (TME) between responders and non-responders. Furthermore, we explored the potential of these differences as predictive indicators. Finally, using machine learning algorithms, we screened for biomarkers and constructed a predictive model. Results: Our proteomics-based analysis revealed that low activity in the complement and coagulation cascades pathway (CCCP) and a high abundance of activated CD8 T cells are positive signals corresponding to ICIs. By using machine learning, we successfully identified a set of 10 protein biomarkers, and the constructed model demonstrated excellent performance in predicting the response in an independent validation set (N = 14; area under the curve [AUC] = 0.959). Conclusion: In summary, our proteomic analyses unveiled unique potential biomarkers for predicting the response to PD-1 inhibitor immunotherapy in GC patients, which may provide the impetus for precision immunotherapy.

Investigation of cellular communication and signaling pathways in tumor microenvironment for high TP53-expressing osteosarcoma cells through single-cell RNA sequencing

Osteosarcoma (OS) stands as the most prevalent primary bone cancer in children and adolescents, and its limited treatment options often result in unsatisfactory outcomes, particularly for metastatic cases. The tumor microenvironment (TME) has been recognized as a crucial determinant in OS progression. However, the intercellular dynamics between high TP53-expressing OS cells and neighboring cell types within the TME are yet to be thoroughly understood. In our study, we harnessed the single-cell RNA sequencing (scRNA-seq) technology in combination with the computational tool-Cellchat, aiming to elucidate the intercellular communication networks present within OS. Through meticulous quantitative inference and subsequent analysis of these networks, we succeeded in identifying significant signaling pathways connecting high TP53-expressing OS cells with proximate cell types, namely Macrophages, Monocytes, Endothelial Cells, and PVLs. This research brings forth a nuanced understanding of the intricate patterns and coordination involved in the TME's intercellular communication signals. These findings not only provide profound insights into the molecular mechanisms underpinning OS but also indicate potential therapeutic targets that could revolutionize treatment strategies.

A pan-cancer analysis of TNFAIP8L1 in human tumors

TNFAIP8L1, as a recently identified member in TNFAIP8 family, plays an important role in tumorigenesis. However, a pan-cancer analysis of TNFAIP8L1 in human tumors has not been conducted until now. The main purpose of study is to investigate TNFAIP8L1 during 33 different types of human tumors by using TCGA and GTEx. The pan-cancer analysis showed that TNFAIP8L1 was significantly over-expressed in 15 cancers and low-expressed in 9 cancers. There were distinct relations between TNFAIP8L1 expression and prognosis of patients with cancer. Furthermore, we also found that DNA methylation and RNA modification of TNFAIP8L1 were associated with many cancers. And then, we detected that TNFAIP8L1 level was positively associated with cancer-associated fibroblasts (CAFs) in many tumors. And, we obtained that TNFAIP8L1 expression was related with most of immune inhibitory and stimulatory genes in multiple types of tumors. We also found TNFAIP8L1 expression was correlated with most of chemokine, receptor, MHC, immunoinhibitor and immunostimulator gens in most of cancers. Moreover, we detected TNFAIP8L1 expression was associated with TMB and MSI in several tumors. Finally, TNFAIP8L1 gene had a significant positive association with 5 genes including BCL6B, DLL4, PCDH12, COL4A1 and DLL4 in the majority of tumors. GO enrichment and KEGG pathway analyses showed that TNFAIP8L1 in thepathogenesis of cancer may be related to "purine nucleoside binding," "purine ribonucleoside binding," "ECM-receptor interaction," etc. Our first pan-cancer study may provide a deep comprehending of TNFAIP8L1 in tumoeigenesis from different tumors.