Proteomics of adjacent-to-tumor samples uncovers clinically relevant biological events in hepatocellular carcinoma

Abstract

Normal adjacent tissues (NATs) of hepatocellular carcinoma (HCC) differ from healthy liver tissues and their heterogeneity may contain biological information associated with disease occurrence and clinical outcome that has yet to be fully evaluated at the proteomic level. This study provides a detailed description of the heterogeneity of NATs and the differences between NATs and healthy livers and revealed that molecular features of tumor subgroups in HCC were partially reflected in their respective NATs. Proteomic data classified HCC NATs into two subtypes (Subtypes 1 and 2), and Subtype 2 was associated with poor prognosis and high-risk recurrence. The pathway and immune features of these two subtypes were characterized. Proteomic differences between the two NAT subtypes and healthy liver tissues were further investigated using data-independent acquisition mass spectrometry, revealing the early molecular alterations associated with the progression from healthy livers to NATs. This study provides a high-quality resource for HCC researchers and clinicians and may significantly expand the knowledge of tumor NATs to eventually benefit clinical practice.

Liver Regeneration-Related Genes of Nontumor Liver Tissues Predict the Prognosis of Patients with Hepatocellular Carcinoma

“…Remarkably, we found that patients with high LR scores had better prognoses and were more similar to healthy liver tissue, which is consistent with Gao’s view: non-tumor tissues exhibited biological behavior similar to that of healthy liver tissue. 33 Previous studies have also shown that biomarkers in non-tumor tissues are associated with HCC progression, metastasis, and survival. 34 “Bile secretion” 26 “Drug metabolism-cytochrome P450” 28 and “Fatty acid degradation” 25 were all up-regulated in the high LR score group, indicating better metabolic function in their non-tumor tissues.…”

Uncovering PROTAC Sensitivity and Efficacy by Multidimensional Proteome Profiling: A Case for STAT3

“…With the advancements in proteomic technology, mass spectrometry (MS)-based proteomics plays an important role in drug research, enabling more reliable and efficient measurement for the global protein expression profiles. − The isobaric labeling quantification (ILQ) such as tandem mass tags (TMTs) has been applied for research of target degraders. − However, the isobaric labeling methods consume very expensive commercial reagents and are easily affected by ratio compression due to the cofragmentation of peptides in tandem MS (MS/MS) spectra. In recent years, data-independent acquisition (DIA) , has been developed for proteomic analysis, with quantitative accuracy and comprehensive coverage .…”