Proteomic profiling identifies outcome-predictive markers in patients with peripheral T-cell lymphoma, not otherwise specified

Single-cell and spatial transcriptomics reveal a high glycolysis B cell and tumor-associated macrophages cluster correlated with poor prognosis and exhausted immune microenvironment in diffuse large B-cell lymphoma

BACKGROUND

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous malignancy characterized by varied responses to treatment and prognoses. Understanding the metabolic characteristics driving DLBCL progression is crucial for developing personalized therapies.

METHODS

This study utilized multiple omics technologies including single-cell transcriptomics (n = 5), bulk transcriptomics (n = 966), spatial transcriptomics (n = 10), immunohistochemistry (n = 34), multiple immunofluorescence (n = 20) and to elucidate the metabolic features of highly malignant DLBCL cells and tumor-associated macrophages (TAMs), along with their associated tumor microenvironment. Metabolic pathway analysis facilitated by scMetabolism, and integrated analysis via hdWGCNA, identified glycolysis genes correlating with malignancy, and the prognostic value of glycolysis genes (STMN1, ENO1, PKM, and CDK1) and TAMs were verified.

RESULTS

High-glycolysis malignant DLBCL tissues exhibited an immunosuppressive microenvironment characterized by abundant IFN_TAMs (CD68+CXCL10+PD-L1+) and diminished CD8+ T cell infiltration. Glycolysis genes were positively correlated with malignancy degree. IFN_TAMs exhibited high glycolysis activity and closely communicating with high-malignancy DLBCL cells identified within datasets. The glycolysis score, evaluated by seven genes, emerged as an independent prognostic factor (HR = 1.796, 95% CI: 1.077-2.995, p = 0.025 and HR = 2.631, 95% CI: 1.207-5.735, p = 0.015) along with IFN_TAMs were positively correlated with poor survival (p < 0.05) in DLBCL. Immunohistochemical validation of glycolysis markers (STMN1, ENO1, PKM, and CDK1) and multiple immunofluorescence validation of IFN_TAMs underscored their prognostic value (p < 0.05) in DLBCL.

CONCLUSIONS

This study underscores the significance of glycolysis in tumor progression and modulation of the immune microenvironment. The identified glycolysis genes and IFN_TAMs represent potential prognostic markers and therapeutic targets in DLBCL.

EBV-Related Lymphoproliferative Diseases: A Review in Light of New Classifications

Epstein-Barr virus (EBV) is a prevalent virus that can be detected in the vast majority of the population. Most people are asymptomatic and remain chronically infected throughout their lifetimes. However, in some populations, EBV has been linked to a variety of B-cell lymphoproliferative disorders (LPDs), such as Burkitt lymphoma, classic Hodgkin lymphoma, and other LPDs. T-cell LPDs have been linked to EBV in part of peripheral T-cell lymphomas, angioimmunoblastic T-cell lymphomas, extranodal nasal natural killer/T-cell lymphomas, and other uncommon histotypes. This article summarizes the current evidence for EBV-associated LPDs in light of the upcoming World Health Organization classification and the 2022 ICC classification.

Proteomics identifies apoptotic markers as predictors of histological transformation in patients with follicular lymphoma

Follicular lymphoma (FL) is an indolent lymphoma with a generally favorable prognosis. However, histological transformation (HT) to a more aggressive disease leads to markedly inferior outcomes. This study aims to identify biological differences predictive of HT at the time of initial FL diagnosis. We show differential protein expression between diagnostic lymphoma samples from patients with subsequent HT (subsequently-transforming FL [st-FL]; n = 20) and patients without HT (nontransforming FL [nt-FL]; n = 34) by label-free quantification nano liquid chromatography-tandem mass spectrometry analysis. Protein profiles identified patients with high risk of HT. This was accompanied by disturbances in cellular pathways influencing apoptosis, the cytoskeleton, cell cycle, and immune processes. Comparisons between diagnostic st-FL samples and paired transformed FL (n = 20) samples demonstrated differential protein profiles and disrupted cellular pathways, indicating striking biological differences from the time of diagnosis up to HT. Immunohistochemical analysis of apoptotic proteins, CASP3, MCL1, BAX, BCL-xL, and BCL-rambo, confirmed higher expression levels in st-FL than in nt-FL samples (P < .001, P = .015, P = .003, P = .025, and P = .057, respectively). Moreover, all 5 markers were associated with shorter transformation-free survival (TFS; P < .001, P = .002, P < .001, P = .069, and P = .010, respectively). Notably, combining the expression of these proteins in a risk score revealed increasingly inferior TFS with an increasing number of positive markers. In conclusion, proteomics identified altered protein expression profiles (particularly apoptotic proteins) at the time of FL diagnosis, which predicted later transformation.

Evaluating a Panel of Autoantibodies Against Tumor-Associated Antigens in Human Osteosarcoma

Background: The aim of this study was to identify a panel of candidate autoantibodies against tumor-associated antigens in the detection of osteosarcoma (OS) so as to provide a theoretical basis for constructing a non-invasive serological diagnosis method in early immunodiagnosis of OS.

Methods: The serological proteome analysis (SERPA) approach was used to select candidate anti-TAA autoantibodies. Then, indirect enzyme-linked immunosorbent assay (ELISA) was used to verify the expression levels of eight candidate autoantibodies in the serum of 51 OS cases, 28 osteochondroma (OC), and 51 normal human sera (NHS). The rank-sum test was used to compare the content of eight autoantibodies in the sera of three groups. The diagnostic value of each indicator for OS was analyzed by an ROC curve. Differential autoantibodies between OS and NHS were screened. Then, a binary logistic regression model was used to establish a prediction logistical regression model.

Results: Through ELISA, the expression levels of seven autoantibodies (ENO1, GAPDH, HSP27, HSP60, PDLIM1, STMN1, and TPI1) in OS patients were identified higher than those in healthy patients (p < 0.05). By establishing a binary logistic regression predictive model, the optimal panel including three anti-TAAs (ENO1, GAPDH, and TPI1) autoantibodies was screened out. The sensitivity, specificity, Youden index, accuracy, and AUC of diagnosis of OS were 70.59%, 86.27%, 0.5686, 78.43%, and 0.798, respectively.

Conclusion: The results proved that through establishing a predictive model, an optimal panel of autoantibodies could help detect OS from OC or NHS at an early stage, which could be used as a promising and powerful tool in clinical practice.

Alpha-Enolase (ENO1) Correlates with Invasiveness of Cutaneous Melanoma—An In Vitro and a Clinical Study

Simple Summary

Alpha-enolase (ENO1) undergoes accentuated overexpression in several solid cancers, but little is known about its status in cutaneous melanoma. The aim of this study was to investigate the prognostic significance of ENO1 in surgical resections from melanoma patients and to assess its expression and enzymatic activity in several melanoma cell lines. In clinical analysis, the overexpression of ENO1 in melanoma cells was significantly correlated with advanced clinical stage, presence of metastases in regional lymph nodes, and shorter cancer-specific overall survival and disease-free survival. We also demonstrated high expression of ENO1 in melanoma cell lines compared with normal melanocytes. Our study, which extends previous in vitro research, makes the alpha-enolase a candidate for a promising diagnostic and therapeutic target for various types of cancers. Consequently, additional testing of ENO1 as a target for melanoma therapy is necessary.

Abstract

Alpha-enolase (ENO1) is a glycolytic metalloenzyme, and its overexpression occurs in numerous cancers, contributing to cancer cell survival, proliferation, and maintenance of the Warburg effect. Patients with an overexpression of ENO1 have a poor prognosis. The aim of the present study was to investigate the prognostic significance of ENO1 in surgical resections from 112 melanoma patients and to assess its expression and enzymatic activity in normoxia and hypoxia in several melanoma cell lines. Overexpression of ENO1 in tumor cells from patients was correlated with unfavorable prognosticators such as Breslow thickness, Clark level, mitotic activity, and the presence of ulceration. The expression of ENO1 also positively correlated with a greater thickness of the neoplastic infiltrate and a worse long-term prognosis for patients with cutaneous melanoma. We report significantly higher expression of ENO1 in melanoma cell lines in comparison to normal melanocytes. To conclude, our in vitro and clinical models showed that overexpression of ENO1 promotes invasiveness of melanoma cells and correlates with aggressive clinical behavior. These observations open the way to further search of a potential prognostic and therapeutic target in cutaneous melanoma.

Proteomic Profiling Differentiates Lymphoma Patients with and without Concurrent Myeloproliferative Neoplasia

Simple Summary

Patients are diagnosed with myeloproliferative neoplasia (MPN) and lymphoma more frequently in the population than expected, which has led to the hypothesis that the two malignancies may, in some cases, be pathogenetically related. In this study, lymphoma patients with and without MPN show subtle but important differences in the protein expression that enables the clustering of the lymphomas, thus indicating the differences at the molecular level between the lymphoma malignancies with and without MPN, and strengthening the hypothesis that the lymphoma and MPN may be biologically related.

Abstract

Myeloproliferative neoplasia (MPN) and lymphoma are regarded as distinct diseases with different pathogeneses. However, patients that are diagnosed with both malignancies occur more frequently in the population than expected. This has led to the hypothesis that the two malignancies may, in some cases, be pathogenetically related. Using a mass spectrometry-based proteomic approach, we show that pre-treatment lymphoma samples from patients with both MPN and lymphoma, either angioimmunoblastic T-cell lymphoma (MPN-AITL) or diffuse large B-cell lymphoma (MPN-DLBCL), show differences in protein expression compared with reference AITL or DLBCL samples from patients without MPN. A distinct clustering of samples from patients with and without MPN was evident for both AITL and DLBCL. Regarding MPN-AITL, a pathway analysis revealed disturbances of cellular respiration as well as oxidative metabolism, and an immunohistochemical evaluation further demonstrated the differential expression of citrate synthase and DNAJA2 protein (p = 0.007 and p = 0.015). Interestingly, IDH2 protein also showed differential expression in the MPN-AITL patients, which contributes to the growing evidence of this protein’s role in both myeloid neoplasia and AITL. In MPN-DLBCL, the disturbed pathways included a significant downregulation of protein synthesis as well as a perturbation of signal transduction. These results imply an underlying disturbance of tumor molecular biology, and in turn an alternative pathogenesis for tumors in these patients with both myeloid and lymphoid malignancies.

Proteomic Characterization of Colorectal Cancer Tissue from Patients Identifies Novel Putative Protein Biomarkers

Colorectal cancer (CRC) is one of the leading causes of cancer-related death over the world. There is a great need for biomarkers capable of early detection and as targets for treatment. Differential protein expression was investigated with two-dimensional gel electrophoresis (2D-PAGE) followed by identification with liquid chromatography–tandem mass spectrometry (LC-MS/MS) in CRC patient tissue from (i) the peripheral part of the tumor, (ii) the central part of the tumor as well as from (iii) a non-involved part of the colorectal tissue. The expression patterns of six identified proteins were further evaluated by one-dimensional Western blot (1D-WB) analysis of the CRC tissue. Proteins that were perturbed in expression level in the peripheral or in the central part of the tumor as compared with the non-involved part included S100A11, HNRNPF, HNRNPH1 or HNRNPH2, GSTP1, PKM and FABP1. These identified markers may have future diagnostic potential or may be novel treatment targets after further evaluation in larger patient cohorts.

Identification of a six-gene metabolic signature predicting overall survival for patients with lung adenocarcinoma

Background

Lung cancer is the leading cause of cancer-related deaths worldwide. Lung adenocarcinoma (LUAD) is one of the main subtypes of lung cancer. Hundreds of metabolic genes are altered consistently in LUAD; however, their prognostic role remains to be explored. This study aimed to establish a molecular signature that can predict the prognosis in patients with LUAD based on metabolic gene expression.

Methods

The transcriptome expression profiles and corresponding clinical information of LUAD were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. The differentially expressed genes (DEGs) between LUAD and paired non-tumor samples were identified by the Wilcoxon rank sum test. Univariate Cox regression analysis and the lasso Cox regression model were used to construct the best-prognosis molecular signature. A nomogram was established comprising the prognostic model for predicting overall survival. To validate the prognostic ability of the molecular signature and the nomogram, the Kaplan-Meier survival analysis, Cox proportional hazards model, and receiver operating characteristic analysis were used.

Results

The six-gene molecular signature (PFKP, PKM, TPI1, LDHA, PTGES, and TYMS) from the DEGs was constructed to predict the prognosis. The molecular signature demonstrated a robust independent prognostic ability in the training and validation sets. The nomogram including the prognostic model had a greater predictive accuracy than previous systems. Furthermore, a gene set enrichment analysis revealed several significantly enriched metabolic pathways, which suggests a correlation of the molecular signature with metabolic systems and may help explain the underlying mechanisms.

Conclusions

Our study identified a novel six-gene metabolic signature for LUAD prognosis prediction. The molecular signature could reflect the dysregulated metabolic microenvironment, provide potential biomarkers for predicting prognosis, and indicate potential novel metabolic molecular-targeted therapies.

Perturbations of urea cycle enzymes during posthepatectomy rat liver failure

Posthepatectomy liver failure (PHLF) may occur after extended partial hepatectomy (PH). If malignancy is widespread in the liver, the size of PH and hence the size of the future liver remnant (FLR) may limit curability. We aimed to characterize differences in protein expression between different sizes of FLRs and identify proteins specific to the regenerative process of minimal-size FLR (MSFLR), with special focus on postoperative day (POD) 1 when PHLF is present. A total of 104 male Wistar rats were subjected to 30, 70, or 90% PH (MSFLR in rats), sham operation, or no operation. Blood and liver tissue were harvested at POD1, 3, and 5 (n = 8 per group). Protein expression was assessed by proteomic profiling by unsupervised two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) liquid chromatography tandem mass spectrometry (LC-MS/MS), followed by supervised selected reaction monitoring (SRM)-MS/MS. In all, 1,035 protein spots were detected, 54 of which were significantly differentially expressed between groups and identifiable. During PHLF after PH(90%) at POD1, urea cycle and related proteins showed significant perturbations, including the urea cycle flux-regulating enzyme of carbamoyl phosphate synthase-1, ornithine transcarbamylase, and arginase-1, as well as the ornithine aminotransferase and propionyl-CoA carboxylase alpha chain. Plasma-ammonia increased significantly at POD1 after PH(90%), followed by a prompt decrease. At the protein level, we found perturbations of urea cycle and related enzymes in the MSFLR during PHLF. Our results suggest that these perturbations may augment urea cycle function, which may be pivotal for increased ammonia elimination after extensive PHs and potential PHLF.NEW & NOTEWORTHY Posthepatectomy liver failure (PHLF) is associated with high mortality. In a rat model of 90% hepatectomy, PHLF is present. Our results on liver tissue proteomics suggest that the ability of the liver remnant to sufficiently eliminate ammonia may be brought about by perturbation related to urea cycle proteins and that enhancing the urea cycle capacity may play a key role in surviving PHLF.