The Thymus-Specific Serine Protease TSSP/PRSS16 Is Crucial for the Antitumoral Role of CD4+ T Cells

Integrated multiomics characterization reveals cuproptosis-related hub genes for predicting the prognosis and clinical efficacy of ovarian cancer

Background

As a prevalent malignancy in women, ovarian cancer (OC) presents a challenge in clinical practice because of its poor prognosis and poor therapeutic efficacy. The mechanism by which cuproptosis activity is accompanied by immune infiltration in OC remains unknown. Here, we investigated cuproptosis-related OC subtypes and relevant immune landscapes to develop a risk score (RS) model for survival prediction.

Methods

Cuproptosis-related genes (CRGs) were identified to construct molecular subtypes via an unsupervised clustering algorithm based on the expression profiles of survival-related CRGs in the GEO database. Single-cell datasets were used to estimate immune infiltration among subtypes. The RS oriented from molecular subtypes was developed via LASSO Cox regression in the TCGA OC dataset and independently validated in the GEO and TCGA datasets. Hub markers from RS were identified in tissues and cell lines. The function of the key gene from RS was identified in vitro.

Results

We investigated cuproptosis activity and immune infiltration to establish three clinical subtypes of OC based the differentially expressed genes (DEGs) from CRGs to create an RS model validated for clinical efficacy and prognosis. Six hub genes from the RS served as ongenic markers in OC tissues and cell lines. The function of GAS1 in the RS model revealed that it exerts oncogenic effects.

Conclusions

Our study provides a novel RS model including 6 hub genes associated with cuproptosis and immune infiltration to predict OC prognosis as well as clinical efficacy.

Blood leukocytes as a non-invasive diagnostic tool for thyroid nodules: a prospective cohort study

BACKGROUND

Thyroid nodule (TN) patients in China are subject to overdiagnosis and overtreatment. The implementation of existing technologies such as thyroid ultrasonography has indeed contributed to the improved diagnostic accuracy of TNs. However, a significant issue persists, where many patients undergo unnecessary biopsies, and patients with malignant thyroid nodules (MTNs) are advised to undergo surgery therapy.

METHODS

This study included a total of 293 patients diagnosed with TNs. Differential methylation haplotype blocks (MHBs) in blood leukocytes between MTNs and benign thyroid nodules (BTNs) were detected using reduced representation bisulfite sequencing (RRBS). Subsequently, an artificial intelligence blood leukocyte DNA methylation (BLDM) model was designed to optimize the management and treatment of patients with TNs for more effective outcomes.

RESULTS

The DNA methylation profiles of peripheral blood leukocytes exhibited distinctions between MTNs and BTNs. The BLDM model we developed for diagnosing TNs achieved an area under the curve (AUC) of 0.858 in the validation cohort and 0.863 in the independent test cohort. Its specificity reached 90.91% and 88.68% in the validation and independent test cohorts, respectively, outperforming the specificity of ultrasonography (43.64% in the validation cohort and 47.17% in the independent test cohort), albeit with a slightly lower sensitivity (83.33% in the validation cohort and 82.86% in the independent test cohort) compared to ultrasonography (97.62% in the validation cohort and 100.00% in the independent test cohort). The BLDM model could correctly identify 89.83% patients whose nodules were suspected malignant by ultrasonography but finally histological benign. In micronodules, the model displayed higher specificity (93.33% in the validation cohort and 92.00% in the independent test cohort) and accuracy (88.24% in the validation cohort and 87.50% in the independent test cohort) for diagnosing TNs. This performance surpassed the specificity and accuracy observed with ultrasonography. A TN diagnostic and treatment framework that prioritizes patients is provided, with fine-needle aspiration (FNA) biopsy performed only on patients with indications of MTNs in both BLDM and ultrasonography results, thus avoiding unnecessary biopsies.

CONCLUSIONS

This is the first study to demonstrate the potential of non-invasive blood leukocytes in diagnosing TNs, thereby making TN diagnosis and treatment more efficient in China.

Comprehensive analysis for the immune related biomarkers of platinum-based chemotherapy in ovarian cancer

BACKGROUND

Ovarian cancer (OC) is one of the most lethal gynecological malignancies. This study aimed to identify biomarkers that were sensitive to platinum-based chemotherapeutic agents and can be used in immunotherapy and explore the importance of their mechanisms of action.

METHODS

RNA-seq profiles and clinicopathological data for OC samples were obtained from The Cancer Genome Atlas (TCGA) and cBioPortal platform, respectively. Platinum-sensitive and platinum-resistant OC samples in the TCGA cohort were selected based on the clinical information. RNA-seq data for 70 OC samples withSingle-sample gene set enrichment analysis (ssGSEA) and unsupervised clustering were used to classify OC patients from the TCGA cohort into clusters with different proportions of infiltrating immune cells. ESTIMATE analysis was used to assess the immune landscape among clusters. Differential expression, univariate Cox regression, and LASSO regression analyses were performed to construct prognostic model. Spearman correlation analysis was conducted to investigate the correlations among immune checkpoint inhibitors (ICIs) and risk score, half-maximal drug inhibitory concentration (IC50) and risk score.

RESULTS

Using ssGSEA and unsupervised clustering, OC samples were divided into two clusters with different immune cell infiltration. Then, 1715 differentially expressed immune-related genes (DEIRGs) were identified between two clusters, 984 differentially expressed platinum-sensitive related genes (DEPSRGs) between 149 platinum-sensitive and 63 platinum-resistant OC samples were identified, and 5384 differentially expressed genes (DEGs) between 380 OC and 194 normal samples were detected from the TCGA cohort. Six biomarkers (GMPPB, SRPK1, STC1, PRSS16, HPDL, and SPTSSB) were detected to establish a prognostic model. The OC patients in the TCGA cohort were classified into high- and low-risk groups. The receive operating characteristic (ROC) curve was plotted and demonstrated that the prognostic model performed well with the area under ROC curve (AUC) greater than 0.6. The expressions of 5 ICIs, including CD200, TNFRSF18, CD160, CD200R1, and CD274 (PD-L1), were significantly different between two risk groups, and the risk score was significant negative associated with CTLA4, TNFRSF4, TNFRSF18, and CD274. Moreover, there were significant differences in IC50 of 10 chemo drugs between two risk groups, patients in the high-risk group could be more resistant to po0tinib, dasatinib, and neratinib.

CONCLUSION

In summary, this study constructed a novel prognostic model based on six prognostic biomarkers, including GMPPB, SRPK1, STC1, PRSS16, HPDL, and SPTSSB, which can be utilized for predicting the prognosis of OC patients. These biomarkers were the potential therapeutic targets.

Contribution of proteases to the hallmarks of aging and to age-related neurodegeneration

Protein quality control ensures the degradation of damaged and misfolded proteins. Derangement of proteostasis is a primary cause of aging and age-associated diseases. The ubiquitin-proteasome and autophagy-lysosome play key roles in proteostasis but, in addition to these systems, the human genome encodes for ~600 proteases, also known as peptidases. Here, we examine the role of proteases in aging and age-related neurodegeneration. Proteases are present across cell compartments, including the extracellular space, and their substrates encompass cellular constituents, proteins with signaling functions, and misfolded proteins. Proteolytic processing by proteases can lead to changes in the activity and localization of substrates or to their degradation. Proteases cooperate with the autophagy-lysosome and ubiquitin-proteasome systems but also have independent proteolytic roles that impact all hallmarks of cellular aging. Specifically, proteases regulate mitochondrial function, DNA damage repair, cellular senescence, nutrient sensing, stem cell properties and regeneration, protein quality control and stress responses, and intercellular signaling. The capacity of proteases to regulate cellular functions translates into important roles in preserving tissue homeostasis during aging. Consequently, proteases influence the onset and progression of age-related pathologies and are important determinants of health span. Specifically, we examine how certain proteases promote the progression of Alzheimer's, Huntington's, and/or Parkinson's disease whereas other proteases protect from neurodegeneration. Mechanistically, cleavage by proteases can lead to the degradation of a pathogenic protein and hence impede disease pathogenesis. Alternatively, proteases can generate substrate byproducts with increased toxicity, which promote disease progression. Altogether, these studies indicate the importance of proteases in aging and age-related neurodegeneration.

In vitro and in vivo functions of T cells produced in complemented thymi of chimeric mice generated by blastocyst complementation

Blastocyst complementation is an intriguing way of generating humanized animals for organ preparation in regenerative medicine and establishing novel models for drug development. Confirming that complemented organs and cells work normally in chimeric animals is critical to demonstrating the feasibility of blastocyst complementation. Here, we generated thymus-complemented chimeric mice, assessed the efficacy of anti-PD-L1 antibody in tumor-bearing chimeric mice, and then investigated T-cell function. Thymus-complemented chimeric mice were generated by injecting C57BL/6 (B6) embryonic stem cells into Foxn1^nu/nu morulae or blastocysts. Flow cytometry data showed that the chimeric mouse thymic epithelial cells (TECs) were derived from the B6 cells. T cells appeared outside the thymi. Single-cell RNA-sequencing analysis revealed that the TEC gene-expression profile was comparable to that in B6 mice. Splenic T cells of chimeric mice responded very well to anti-CD3 stimulation in vitro; CD4⁺ and CD8⁺ T cells proliferated and produced IFNγ, IL-2, and granzyme B, as in B6 mice. Anti-PD-L1 antibody treatment inhibited MC38 tumor growth in chimeric mice. Moreover, in the chimeras, anti-PD-L1 antibody restored T-cell activation by significantly decreasing PD-1 expression on T cells and increasing IFNγ-producing T cells in the draining lymph nodes and tumors. T cells produced by complemented thymi thus functioned normally in vitro and in vivo. To successfully generate humanized animals by blastocyst complementation, both verification of the function and gene expression profiling of complemented organs/cells in interspecific chimeras will be important in the near future.

Association between tumor mutation burden and immune infiltration in ovarian cancer

BACKGROUND

It remains unclear whether the tumor mutation burden (TMB) or a TMB-related signature could be prognostic indicators in ovarian cancer (OC), as potential correlations with immune infiltrates and immunotherapy responsiveness remains poorly understood.

METHODS

Data of 941 OC patients were collected from three datasets, including 587, 260, and 94 patients from The Cancer Genome Atlas (TCGA), GSE32062, and the International Cancer Genome Consortium (ICGC), respectively. TMB was calculated and correlations with clinical outcomes, immune infiltrates, and immunotherapy responsiveness were investigated in the TCGA OC cohort. Weighted gene co-expression network analysis was performed to identify TMB-related genes. A TMB-related signature was constructed and validated.

RESULTS

Higher TMB was associated with better survival in the TCGA and ICGC OC cohorts. The high-TMB group had higher CD8+ T-cell infiltration than the low-TMB group. No significant correlation was found between TMB and immunotherapy response. Furthermore, we selected 8 prognostic and TMB-related genes to construct a TMB-related signature that could distinguish between the high- and low-risk patients; its predictive power was validated in the GSE32062 and ICGC datasets. SubMap analysis suggested that patients in the low-risk group might have a better response to anti-PD1 therapy.

CONCLUSIONS

We examined the prognostic value of TMB and its potential association with immune cell infiltration and immunotherapy responsiveness in OC. A TMB-related prognostic signature consisting of 8 genes was developed and verified, which might be a promising prognostic signature for the prognosis of OC patients.

Genetic colocalization atlas points to common regulatory sites and genes for hematopoietic traits and hematopoietic contributions to disease phenotypes

BACKGROUND

Genetic associations link hematopoietic traits and disease end-points, but most causal variants and genes underlying these relationships are unknown. Here, we used genetic colocalization to nominate loci and genes related to shared genetic signal for hematopoietic, cardiovascular, autoimmune, neuropsychiatric, and cancer phenotypes.

METHODS

Our aim was to identify colocalization sites for human traits among established genome-wide significant loci. Using genome-wide association study (GWAS) summary statistics, we determined loci where multiple traits colocalized at a false discovery rate < 5%. We then identified quantitative trait loci among colocalization sites to highlight related genes. In addition, we used Mendelian randomization analysis to further investigate certain trait relationships genome-wide.

RESULTS

Our findings recapitulated developmental hematopoietic lineage relationships, identified loci that linked traits with causal genetic relationships, and revealed novel trait associations. Out of 2706 loci with genome-wide significant signal for at least 1 blood trait, we identified 1779 unique sites (66%) with shared genetic signal for 2+ hematologic traits. We could assign some sites to specific developmental cell types during hematopoiesis based on affected traits, including those likely to impact hematopoietic progenitor cells and/or megakaryocyte-erythroid progenitor cells. Through an expanded analysis of 70 human traits, we defined 2+ colocalizing traits at 2123 loci from an analysis of 9852 sites (22%) containing genome-wide significant signal for at least 1 GWAS trait. In addition to variants and genes underlying shared genetic signal between blood traits and disease phenotypes that had been previously related through Mendelian randomization studies, we defined loci and related genes underlying shared signal between eosinophil percentage and eczema. We also identified colocalizing signals in a number of clinically relevant coding mutations, including sites linking PTPN22 with Crohn's disease, NIPA with coronary artery disease and platelet trait variation, and the hemochromatosis gene HFE with altered lipid levels. Finally, we anticipate potential off-target effects on blood traits related novel therapeutic targets, including TRAIL.

CONCLUSIONS

Our findings provide a road map for gene validation experiments and novel therapeutics related to hematopoietic development, and offer a rationale for pleiotropic interactions between hematopoietic loci and disease end-points.

Genome-wide association studies for tick resistance in Bos taurus × Bos indicus crossbred cattle: A deeper look into this intricate mechanism

Rhipicephalus (Boophilus) microplus is the main cattle ectoparasite in tropical areas. Gir × Holstein crossbred cows are well adapted to different production systems in Brazil. In this context, we performed genome-wide association study (GWAS) and post-GWAS analyses for R. microplus resistance in an experimental Gir × Holstein F₂ population. Single nucleotide polymorphisms (SNP) identified in GWAS were used to build gene networks and to investigate the breed of origin for its alleles. Tick artificial infestations were performed during the dry and rainy seasons. Illumina BovineSNP50 BeadChip (Illumina Inc., San Diego, CA) and single-step BLUP procedure was used for GWAS. Post-GWAS analyses were performed by gene ontology terms enrichment and gene transcription factors networks, generated from enriched transcription factors, identified from the promoter sequences of selected gene sets. The genetic origin of marker alleles in the F₂ population was assigned using the breed of origin of alleles approach. Heritability estimates for tick counts were 0.40 ± 0.11 in the rainy season and 0.54 ± 0.11 in the dry season. The top ten 0.5-Mbp windows with the highest percentage of genetic variance explained by SNP markers were found in chromosomes 10 and 23 for both the dry and rainy seasons. Gene network analyses allowed the identification of genes involved with biological processes relevant to immune system functions (TREM1, TREM2, and CD83). Gene-transcription factors network allowed the identification of genes involved with immune functions (MYO5A, TREML1, and PRSS16). In resistant animals, the average proportion of animals showing significant SNPs with paternal and maternal alleles originated from Gir breed was 44.8% whereas the proportion of animals with both paternal and maternal alleles originated from Holstein breed was 11.3%. Susceptible animals showing both paternal and maternal alleles originated from Holstein breed represented 44.6% on average, whereas both paternal and maternal alleles originated from Gir breed animals represented 9.3%. This study allowed us to identify candidate genes for tick resistance in Gir × Holstein crossbreds in both rainy and dry seasons. According to the origin of alleles analysis, we found that most animals classified as resistant showed 2 alleles from Gir breed, while the susceptible ones showed alleles from Holstein. Based on these results, the identified genes may be thoroughly investigated in additional experiments aiming to validate their effects on tick resistance phenotype in cattle.

Thymus-specific serine protease, a protease that shapes the CD4 T cell repertoire

The lifespan of T cells is determined by continuous interactions of their T cell receptors (TCR) with self-peptide-MHC (self-pMHC) complexes presented by different subsets of antigen-presenting cells (APC). In the thymus, developing thymocytes are positively selected through recognition of self-pMHC presented by cortical thymic epithelial cells (cTEC). They are subsequently negatively selected by medullary thymic epithelial cells (mTEC) or thymic dendritic cells (DC) presenting self-pMHC complexes. In the periphery, the homeostasis of mature T cells is likewise controlled by the interaction of their TCR with self-pMHC complexes presented by lymph node stromal cells while they may be tolerized by DC presenting tissue-derived self-antigens. To perform these tasks, the different subsets of APC are equipped with distinct combination of antigen processing enzymes and consequently present specific repertoire of self-peptides. Here, we discuss one such antigen processing enzyme, the thymus-specific serine protease (TSSP), which is predominantly expressed by thymic stromal cells. In thymic DC and TEC, TSSP edits the repertoire of peptide presented by class II molecules and thus shapes the CD4 T cell repertoire.

Generation of Peptides That Promote Positive Selection in the Thymus

To establish an immunocompetent TCR repertoire that is useful yet harmless to the body, a de novo thymocyte repertoire generated through the rearrangement of genes that encode TCR is shaped in the thymus through positive and negative selection. The affinity between TCRs and self-peptides associated with MHC molecules determines the fate of developing thymocytes. Low-affinity TCR engagement with self-peptide-MHC complexes mediates positive selection, a process that primarily occurs in the thymic cortex. Massive efforts exerted by many laboratories have led to the characterization of peptides that can induce positive selection. Moreover, it is now evident that protein degradation machineries unique to cortical thymic epithelial cells play a crucial role in the production of MHC-associated self-peptides for inducing positive selection. This review summarizes current knowledge on positive selection-inducing self-peptides and Ag processing machineries in cortical thymic epithelial cells. Recent studies on the role of positive selection in the functional tuning of T cells are also discussed.

Gut bacteria and cancer

Microbiota on the mucosal surfaces of the gastrointestinal (GI) tract greatly outnumbers the cells in the human body. Effects of antibiotics indicate that GI tract bacteria may be determining the fate of distal cancers. Recent data implicate dysregulated host responses to enteric bacteria leading to cancers in extra-intestinal sites. Together these findings point to novel anti-cancer strategies aimed at promoting GI tract homeostasis.

A novel actor in antitumoral immunity: The thymus-specific serine protease TSSP/PRSS16 involved in CD4+ T-cell maturation

The maturation of a specific subset of CD4⁺ T lymphocytes in the thymus is dependent on cortical thymic epithelial cells expressing the protease thymus-specific serine protease (TSSP, also known as PRSS16). Recently, we unveiled the involvement of TSSP in tumor suppression through its effect on the CD4⁺ T compartment.