Background and Objective: Excision repair cross complementing (ERCC) group genes play important roles in the nucleotide excision repair (NER) way, which can effectively remove bulky lesions and reduce UV-caused DNA damage by environmental chemicals. Polymorphisms in ERCCs were thought to be related to prostate cancer (PCa) risk. However, it has been unclear whether this relationship is consistent. This study aimed to obtain the overall profile regarding the associations between ERCCs polymorphisms and PCa risk.

Purpose: Hepatocellular carcinoma (HCC) is the most common liver malignancy in the world, and tumor-infiltrating T cells have been shown to be closely related to the prognosis of HCC. This study investigated the potential and efficacy of T cell receptor (TCR) repertoire characterization as a biomarker for predicting survival differences. Methods: In this study, we used high-throughput sequencing technology to systematically analyze the characteristics of TCR repertoires in tumor tissues obtained from 23 long-survivors and 8 short-survivors diagnosed with HCC. Results: The TCR composition in HCC long-survivors was found to be less diverse than in the short-survivors. In addition, in the context of V and J gene segments, long-survivors showed significantly higher usage of TRBJ1-3, TRBV10-1, TRBV15, and TRBV6-5, and lower usage of TRBJ2-2. Both principal component analysis (PCA) and the motif diagram of complementary determination region 3 (CDR3) sequences could clearly discriminate short- and long-survivors. And there were five up-regulated and one down-regulated CDR3 sequences in the LS group compared with the SS group. According to the characteristics of TCR repertoire, we also established the survival-related evaluation system and the prediction model for the survival period of HCC patients. Conclusion: Our study adds to the existing knowledge of TCR rearrangement profiles in HCC patients by elucidating the differential TCR rearrangement profiles between long-term and short-term surviving HCC patients. Also, our analysis identified a number of TCR genes that are significantly associated with survival, and these may not only serve as prognostic biomarkers but may also play an important role in antigen-specific immunotherapy.

Cardiovascular and cerebrovascular diseases, often caused by atherosclerosis, are the stern cause of death worldwide, and carotid plaque play a crucial role in the development of these diseases. Tryptophan metabolism is an important pathway involved in the regulation of immune response, inflammation and vascular health. In this study, we analyzed bulk and scRNA data from carotid plaque to investigate the relevance between tryptophan metabolism and plaque formation. We identified 446 differentially expressed genes that are enriched in immune and tryptophan-related pathways. Focusing on tryptophan metabolism, we identified six key tryptophan-related differentially expressed genes: TPH1, MAOB, TDO2, KMO, KYNU, and CYP1B1. Using the six genes, we constructed a logistic regression model with an AUC of 0.75, which successfully predicted the risk of carotid plaque formation. Analysis of global and single-cell data revealed differential expression patterns and related modes of action of the six genes in carotid plaque, suggesting that they influence the development of carotid plaque through their involvement in tryptophan metabolism, lipid biosynthesis, and inflammatory responses. These tryptophan-related differentially expressed genes can be used as potential biomarkers to assess plaque risk and as therapeutic targets to manage carotid atherosclerosis by regulating tryptophan metabolism and reducing inflammation.

Background: Hepatocellular carcinoma (HCC) is developed as a consequence of chronic liver cirrhosis, and both diseases are difficult to diagnose and differentiate. Accurate noninvasive biomarkers for HCC and liver cirrhosis are urgently needed. Methods: Here we used high-throughput sequencing to characterize the B cell receptor (BCR) repertoires from 36 HCC tumor samples and 10 liver cirrhosis (LC) tissue biopsies to understand the immune alterations during hepatic carcinogenesis. Results: The principal components analysis (PCA) showed that the pattern of BCR in HCC was distinct from that in LC. As measured by Clonality and Shannon indexes, the diversity of BCR repertoire was significantly lower in HCC than in LC (P < 0.01). Conclusion: Our results corroborated that the BCR diversity and composition could be closely correlated with hepatic carcinogenesis. And BCR repertoire may be used to predict the progression of HCC and design targeting immunotherapy in the near future.

Introduction: Given the poor prognosis associated with hepatocellular carcinoma (HCC), identifying reliable biomarkers is critical to aid in prognostication and customized treatment planning. Objective: This study aimed to develop a prognostic gene signature based on anoikis- and autophagy-related genes (AARGs) to predict HCC prognosis. Methods: We analyzed differentially expressed AARGs associated with HCC prognosis using messenger RNA expression profiles and clinicopathological data from the Cancer Genome Atlas Liver Hepatocellular Carcinoma Database. Validation was performed using data from the International Cancer Genome Consortium. AARG signatures were constructed using univariate Cox regression and the least absolute shrinkage and selection operator method. Results: We identified 13 AARGs, of which nine showed significant associations with overall survival (OS). Three AARGs—baculoviral IAP repeat containing 5, mitogen-activated protein kinase 3, and BRI1-associated kinase 1—were selected to establish the prognostic AARGs signature. Statistical analyses confirmed the prognostic capacity of the model. Gene set enrichment analysis was performed to explore potential molecular mechanisms. Further investigations included assessments of clinical parameters, immune landscape, immune checkpoint blockade response, tumor stemness, and chemotherapy sensitivity. Immunohistochemistry was conducted to compare protein expression between normal and tumor tissues. Patients in the high-risk group exhibited advanced tumor stage, shorter survival time, and poorer prognosis, along with anoikis resistance, elevated autophagy, and immunosuppression. The nomogram incorporating the AARG signature showed strong predictive performance for OS. Conclusion: We developed and validated a new AARGs-based signature that effectively predicts prognosis for HCC patients.