The hematopoietic stem cell marker VNN2 is associated with chemoresistance in pediatric B-cell precursor ALL

VNN2-expressing circulating monocytes exhibit unique functional characteristics and are decreased in patients with primary Sjögren's syndrome

OBJECTIVE

This study aims to elucidate the significance of VNN2 expression in peripheral blood monocytes and its clinical relevance in primary Sjögren's syndrome (pSS).

METHODS

We investigated VNN2 expression by analyzing single-cell RNA sequencing (scRNA-seq) data from peripheral blood mononuclear cells. Flow cytometry was used to detect and compare VNN2 expression in total monocytes, classical monocytes (cMo), intermediate monocytes (iMo) and non-classical monocytes (ncMo). Additionally, we examined the expression of HLA, ICAM1, CD62L, ITGAM, S100A8, S100A9, CCR2, CCR6, CX3CR1 and CXCR3 in VNN2+ and VNN2- cells. We analyzed the correlation between VNN2 expression and clinical indicators and assessed the clinical utility of VNN2+ monocytes in pSS diagnosis using receiver operating characteristic curves.

RESULTS

We observed high VNN2 expression in monocytes, with significantly higher levels in CD14++ monocytes compared to ncMo. VNN2+ monocytes exhibited decreased expression of HLA and CD62L and increased expression of ICAM1, ITGAM, S100A8, S100A9, CCR2, CCR6, CX3CR1 and CXCR3 compared to VNN2- monocytes. Although scRNA-seq data showed that VNN2 mRNA was upregulated, cell surface expression of VNN2 was decreased in monocytes from pSS patients compared to healthy controls. The reduced levels of VNN2+ monocyte subpopulations in pSS patients were negatively correlated with anti-ribosome antibody levels and positively correlated with complement 4 levels. Detection of VNN2 expression in monocytes can aid in the auxiliary diagnosis of pSS.

CONCLUSION

Monocytes expressing cell surface VNN2 are significantly reduced in pSS patients. This suggests a potential role for VNN2 in pSS development and its potential use as a diagnostic marker for pSS.

Microfluidic-based dynamic BH3 profiling predicts anticancer treatment efficacy

Precision medicine is starting to incorporate functional assays to evaluate anticancer agents on patient-isolated tissues or cells to select for the most effective. Among these new technologies, dynamic BH3 profiling (DBP) has emerged and extensively been used to predict treatment efficacy in different types of cancer. DBP uses synthetic BH3 peptides to measure early apoptotic events ('priming') and anticipate therapy-induced cell death leading to tumor elimination. This predictive functional assay presents multiple advantages but a critical limitation: the cell number requirement, that limits drug screening on patient samples, especially in solid tumors. To solve this problem, we developed an innovative microfluidic-based DBP (µDBP) device that overcomes tissue limitations on primary samples. We used microfluidic chips to generate a gradient of BIM BH3 peptide, compared it with the standard flow cytometry based DBP, and tested different anticancer treatments. We first examined this new technology's predictive capacity using gastrointestinal stromal tumor (GIST) cell lines, by comparing imatinib sensitive and resistant cells, and we could detect differences in apoptotic priming and anticipate cytotoxicity. We then validated µDBP on a refractory GIST patient sample and identified that the combination of dactolisib and venetoclax increased apoptotic priming. In summary, this new technology could represent an important advance for precision medicine by providing a fast, easy-to-use and scalable microfluidic device to perform DBP in situ as a routine assay to identify the best treatment for cancer patients.

Genomic and Transcriptomic Predictors of Response to Immune Checkpoint Inhibitors in Melanoma Patients: A Machine Learning Approach

Immune checkpoint inhibitors (ICIs) became one of the most revolutionary cancer treatments, especially in melanoma. While they have been proven to prolong survival with lesser side effects compared to chemotherapy, the accurate prediction of response remains to be an unmet gap. Thus, we aim to identify accurate clinical and transcriptomic biomarkers for ICI response in melanoma. We also provide mechanistic insight into how high-performing markers impose their effect on the tumor microenvironment (TME). Clinical and transcriptomic data were retrieved from melanoma studies administering ICIs from cBioportal and GEO databases. Four machine learning models were developed using random-forest classification (RFC) entailing clinical and genomic features (RFC7), differentially expressed genes (DEGs, RFC-Seq), survival-related DEGs (RFC-Surv) and a combination model. The xCELL algorithm was used to investigate the TME. A total of 212 ICI-treated melanoma patients were identified. All models achieved a high area under the curve (AUC) and bootstrap estimate (RFC7: 0.71, 0.74; RFC-Seq: 0.87, 0.75; RFC-Surv: 0.76, 0.76, respectively). Tumor mutation burden, GSTA3, and VNN2 were the highest contributing features. Tumor infiltration analyses revealed a direct correlation between upregulated genes and CD8+, CD4+ T cells, and B cells and inversely correlated with myeloid-derived suppressor cells. Our findings confirmed the accuracy of several genomic, clinical, and transcriptomic-based RFC models, that could further support the use of TMB in predicting response to ICIs. Novel genes (GSTA3 and VNN2) were identified through RFC-seq and RFC-surv models that could serve as genomic biomarkers after robust validation.

Integrated analysis of Helicobacter pylori-related prognostic gene modification patterns in the tumour microenvironment of gastric cancer

Background

Helicobacter pylori (HP) infection is one of the leading causes of gastric cancer (GC). However, the interaction between HP and the TME, and its carcinogenic mechanism remains unknown.

Methods

The HP-related prognostic genes were identified based on HP infection-related gene markers and HP infection sample datasets by risk method and NMF algorithm. Principal component analysis (PCA) algorithm was used to constructed the HPscore system. The “limma” R package was employed to determine differentially expressed genes. In addition, the R packages, such as “xCell” and “GSVA”, was used to analyze the relationship between the HPscore and tumor microenvironment. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to verify the expression levels of 28 HP-related prognostic genes in tissues.

Results

We successfully identified 28 HP-related prognostic genes that accurately classified the GC population. There are significant differences in survival between different subgroups (high-, low-risk and cluster_1,2). Thereafter, the HPscore system was constructed to evaluate the signatures of the 28 HP-related prognostic genes. The overall survival rate in the high-HPscore group was poor and immunological surveillance was reduced, whereas the low-HPscore group had a survival advantage and was related to the inflammatory response. HPscore was also strongly correlated with the tumour stage, TME cell infiltration and stemness. The qRT-PCR results showed that DOCK4 expression level of 28 HP-related prognostic genes was higher in gastric cancer tissues than in adjacent tissues.

Conclusions

HP signatures play a crucial role in the TME and tumourigenesis. HPscore evaluation of a single tumour sample can help identify the TME characteristics and the carcinogenic mechanism of GC patients infected with HP, based on which personalized treatment can be administered.

Verification of immunology-related genetic associations in BPD supports ABCA3 and five other genes

BACKGROUND

Inflammatory processes are key drivers of bronchopulmonary dysplasia (BPD), a chronic lung disease in preterm infants. In a large sample, we verify previously reported associations of genetic variants of immunology-related genes with BPD.

METHODS

Preterm infants with a gestational age ≤32 weeks from PROGRESS and the German Neonatal Network (GNN) were included. Through a consensus case/control definition, 278 BPD cases and 670 controls were identified. We identified 49 immunity-related genes and 55 single-nucleotide polymorphisms (SNPs) previously associated with BPD through a comprehensive literature survey. Additionally, a quantitative genetic association analysis regarding oxygen supplements, mechanical ventilation, and continuous positive air pressure (CPAP) was performed.

RESULTS

Five candidate SNPs were nominally associated with BPD-related phenotypes with effect directions not conflicting the original studies: rs11265269-CRP, rs1427793-NUAK1, rs2229569-SELL, rs1883617-VNN2, and rs4148913-CHST3. Four of these genes are involved in cell adhesion. Extending our analysis to all well-imputed SNPs of all candidate genes, the strongest association was rs45538638-ABCA3 with CPAP (p = 4.9 × 10^-7, FDR = 0.004), an ABC transporter involved in surfactant formation.

CONCLUSIONS

Most of the previously reported associations could not be replicated. We found additional support for SNPs in CRP, NUAK1, SELL, VNN2, and ABCA3. Larger studies and meta-analyses are required to corroborate these findings.

IMPACT

Larger cohort for improved statistical power to detect genetic associations with bronchopulmonary dysplasia (BPD). Most of the previously reported genetic associations with BPD could not be replicated in this larger study. Among investigated immunological relevant candidate genes, additional support was found for variants in genes CRP, NUAK1, SELL, VNN2, and CHST3, four of them related to cell adhesion. rs45538638 is a novel candidate SNP in reported candidate gene ABC-transporter ABCA3. Results help to prioritize molecular candidate pathomechanisms in follow-up studies.

GPI-80 Augments NF-κB Activation in Tumor Cells

Recent studies have discovered a relationship between glycosylphosphatidylinositol (GPI)-anchored protein 80 (GPI-80)/VNN2 (80 kDa GPI-anchored protein) and malignant tumors. GPI-80 is known to regulate neutrophil adhesion; however, the action of GPI-80 on tumors is still obscure. In this study, although the expression of GPI-80 mRNA was detectable in several tumor cell lines, the levels of GPI-80 protein were significantly lower than that in neutrophils. To clarify the function of GPI-80 in tumor cells, GPI-80-expressing cells and GPI-80/VNN2 gene-deleted cells were established using PC3 prostate cancer cells. In GPI-80-expressing cells, GPI-80 was mainly detected in vesicles. Furthermore, soluble GPI-80 in the conditioned medium was associated with the exosome marker CD63 and was also detected in the plasma obtained from prostate cancer patients. Unexpectedly, cell adhesion and migration of GPI-80-expressing PC3 cells were not modulated by anti-GPI-80 antibody treatment. However, similar to the GPI-80 family molecule, VNN1, the pantetheinase activity and oxidative state were augmented in GPI-80-expressing cells. GPI-80-expressing cells facilitated non-adhesive proliferation, slow cell proliferation, NF-κB activation and IL-1β production. These phenomena are known to be induced by physiological elevation of the oxidative state. Thus, these observations indicated that GPI-80 affects various tumor responses related to oxidation.