Enhancing multiple myeloma staging: a novel cell death risk model approach.

The prognostication of survival trajectories in multiple myeloma (MM) patients presents a substantial clinical challenge. Leveraging transcriptomic and clinical profiles from an expansive cohort of 2,088 MM patients, sourced from the Gene Expression Omnibus and The Cancer Genome Atlas repositories, we applied a sophisticated nested lasso regression technique to construct a prognostic model predicated on 28 gene pairings intrinsic to cell death pathways, thereby deriving a quantifiable risk stratification metric. Employing a threshold of 0.15, we dichotomized the MM samples into discrete high-risk and low-risk categories. Notably, the delineated high-risk cohort exhibited a statistically significant diminution in survival duration, a finding which consistently replicated across both training and external validation datasets. The prognostic acumen of our cell death signature was further corroborated by TIME ROC analyses, with the model demonstrating robust performance, evidenced by AUC metrics consistently surpassing the 0.6 benchmark across the evaluated arrays. Further analytical rigor was applied through multivariate COX regression analyses, which ratified the cell death risk model as an independent prognostic determinant. In an innovative stratagem, we amalgamated this risk stratification with the established International Staging System (ISS), culminating in the genesis of a novel, refined ISS categorization. This tripartite classification system was subjected to comparative analysis against extant prognostic models, whereupon it manifested superior predictive precision, as reflected by an elevated C-index. In summation, our endeavors have yielded a clinically viable gene pairing model predicated on cellular mortality, which, when synthesized with the ISS, engenders an augmented prognostic tool that exhibits pronounced predictive prowess in the context of multiple myeloma.

The miR-641-STIM1 and SATB1 axes play important roles in the regulation of the Th17/Treg balance in ITP.

Immune thrombocytopenia (ITP) is an autoimmune disease caused by T-cell dysfunction. Recently, several studies have shown that a disturbed Th17/Treg balance contributes to the development of ITP. MicroRNAs (miRNAs) are small noncoding RNA moleculesthat posttranscriptionally regulate gene expression. Emerging evidences have demonstrated that miRNAs play an important role in regulating the Th17/Treg balance. In the present study, we found that miR-641 was upregulated in ITP patients. In primary T cells, overexpression of miR-641 could cause downregulation of its target genes STIM1 and SATB1, thus inducing a Th17 (upregulated)/Treg (downregulated) imbalance. Inhibition of miR-641 by a miR-641 sponge in primary T cells of ITP patients or by antagomiR-641 in an ITP murine model could cause upregulation of STIM1 and SATB1, thus restoring Th17/Treg homeostasis. These results suggested that the miR-641-STIM/SATB1 axis plays an important role in regulating the Th17/Treg balance in ITP.

A Risk Stratification System in Myeloma Patients with Autologous Stem Cell Transplantation.

Autologous stem cell transplantation (ASCT) has been a mainstay in myeloma treatment for over three decades, but patient prognosis post-ASCT varies significantly. In a retrospective study of 5259 patients with multiple myeloma (MM) at the University of Arkansas for Medical Sciences undergoing ASCT with a median 57-month follow-up, we divided the dataset into training (70%) and validation (30%) subsets. Employing univariable and multivariable Cox analyses, we systematically assessed 29 clinical variables, identifying crucial adverse prognostic factors, such as extended duration between MM diagnosis and ASCT, elevated serum ferritin, and reduced transferrin levels. These factors could enhance existing prognostic models. Additionally, we pinpointed significant poor prognosis markers like high serum calcium and low platelet counts, though they are applicable to a smaller patient population. Utilizing seven easily accessible high-risk variables, we devised a four-stage system (ATM4S) with primary stage borders determined through K-adaptive partitioning. This staging system underwent validation in both the training dataset and an independent cohort of 514 ASCT-treated MM patients from the University of Iowa. We also explored cytogenetic risk factors within this staging system, emphasizing its potential clinical utility for refining prognostic assessments and guiding personalized treatment approaches.

Plasmablastic lymphoma: current knowledge and future directions.

Plasmablastic lymphoma (PBL) is an aggressive non-Hodgkin lymphoma associated with HIV infection and immunodeficiency. However, PBL can also be seen immunocompetent individuals in recent studies. PBL was characterized by distinct clinical and pathological features, such as plasmablastic morphology and universal expression of plasma cell markers. The clinicopathologic features were different between HIV-negative and HIV-positive patients. Gene expression analysis identified the unique molecular feature in PBL, including frequent c-MYC rearrangement and downregulation of BCR signaling pathway. Despite the recent advances in the treatment of PBL, the prognosis of PBL patients remains dismal. The objectives of this review are to summarize the current knowledge on the epidemiology, molecular profiles, clinical and pathological features, differential diagnosis, treatment strategies, prognostic factors, and potential novel therapeutic approaches in PBL patients.

Low-Energy Ion Implantation and Deep-Mesa Si-Avalanche Photodiodes with Improved Fabrication Process.

Since the avalanche phenomenon was first found in bulk materials, avalanche photodiodes (APDs) have been exclusively investigated. Among the many devices that have been developed, silicon APDs stand out because of their low cost, performance stability, and compatibility with CMOS. However, the increasing industrial needs pose challenges for the fabrication cycle time and fabrication cost. In this work, we proposed an improved fabrication process for ultra-deep mesa-structured silicon APDs for photodetection in the visible and near-infrared wavelengths with improved performance and reduced costs. The improved process reduced the complexity through significantly reduced photolithography steps, e.g., half of the steps of the existing process. Additionally, single ion implantation was performed under low energy (lower than 30 keV) to further reduce the fabrication costs. Based on the improved ultra-concise process, a deep-mesa silicon APD with a 140 V breakdown voltage was obtained. The device exhibited a low capacitance of 500 fF, the measured rise time was 2.7 ns, and the reverse bias voltage was 55 V. Moreover, a high responsivity of 103 A/W@870 nm at 120 V was achieved, as well as a low dark current of 1 nA at punch-through voltage and a maximum gain exceeding 1000.

ALYREF (Aly/REF export factor): A potential biomarker for predicting cancer occurrence and therapeutic efficacy.

5-Methylcytosine (m5C) methylation is present in almost all types of RNA as an essential epigenetic modification. It is dynamically modulated by its associated enzymes, including m5C methyltransferases (NSUN, DNMT and TRDMT family members), demethylases (TET family and ALKBH1) and binding proteins (YTHDF2, ALYREF and YBX1). Among them, aberrant expression of the RNA-binding protein ALYREF can facilitate a variety of malignant phenotypes such as maintenance of proliferation, malignant heterogeneity, metastasis, and drug resistance to cell death through different regulatory mechanisms, including pre-mRNA processing, mRNA stability, and nuclear-cytoplasmic shuttling. The induction of these cellular processes by ALYREF results in treatment resistance and poor outcomes for patients. However, there are currently few reports of clinical applications or drug trials related to ALYREF. In addition, the looming observations on the role of ALYREF in the mechanisms of carcinogenesis and disease prognosis have triggered considerable interest, but critical evidence is not available. For example, animal experiments and ALYREF small molecule inhibitor trials. In this review, we, therefore, revisit the literature on ALYREF and highlight its importance as a prognostic biomarker for early prevention and as a therapeutic target.

Identification and validation of 5-methylcytosine-associated genes in diffuse large B-cell lymphoma.

5-methylcytosine modifications play a significant role in carcinogenesis; however, studies exploring 5-methylcytosine-related genes in diffuse large B-cell lymphoma patients are lacking. In this study, we aimed to understand the potential role and clinical prognostic impact of 5-methylcytosine regulators in diffuse large B-cell lymphoma and identify a prognostic biomarker based on 5-methylcytosine-associated genes. Gene expression profiles and corresponding clinical information of diffuse large B-cell lymphoma patients and normal controls were obtained from The Cancer Genome Atlas, Gene Expression Omnibus, and Genotype-Tissue Expression databases. Diffuse large B-cell lymphoma was divided into three clusters according to the 5-methylcytosine regulators, and differentially expressed genes were screened among the three clusters. Univariate Cox and Lasso-Cox regression analyses were used to screen prognostic genes and construct a prognostic risk model. Kaplan-Meier curve analysis, univariate and multivariate Cox regression analyses, and time-dependent receiver operator characteristic curve analysis were used to evaluate prognostic factors. GSVA was used to enrich potential pathways associated with 5-methylcytosine modification patterns. SsGSEA and CIBERSORT were used to assess immune cell infiltration. Six 5-methylcytosine-related genes (TUBB4A, CD3E, ZNF681, HAP1, IL22RA2, and POSTN) were used to construct a prognostic risk model, which was proved to have a good predictive effect. In addition, univariate and multivariate Cox regression risk scores were independent prognostic factors for diffuse large B-cell lymphoma. Further analysis showed that the 5-methylcytosine risk score was significantly correlated with immune cell infiltration and immune checkpoint of diffuse large B-cell lymphoma. Our study reveals for the first time a potential role for 5-methylcytosine modifications in diffuse large B-cell lymphoma, provides novel insights for future studies on diffuse large B-cell lymphoma, and offers potential prognostic biomarkers and therapeutic targets for patients with diffuse large B-cell lymphoma.

The Aurora kinase inhibitor AT9283 inhibits Burkitt lymphoma growth by regulating Warburg effect.

Objective: To investigate the effect of the kinase inhibitor AT9283 on Burkitt lymphoma (BL) cells and elucidate the underlying mechanisms. Methods: The effect of AT9283 on the proliferation of BL cell lines was tested using the MTT assay. Apoptosis and cell cycle were measured by flow cytometry. The proteins associated with the cell cycle, apoptosis, and the Warburg effect were detected using Western blotting. Alterations in glycolytic metabolism in terms of glucose intake and lactate concentrations were determined by glucose and lactate assays. Results: The current study utilized the GEPIA, the Human Protein Atlas (HAP) database and immunohistochemistry to conduct analyses, which revealed a high expression of Aurora kinases and Warburg effect-related proteins in malignant B-cell lymphoma tissues. AT9283 significantly inhibited the cell proliferation of BL cells and induced G2/M arrest. Additionally, AT9283 induced apoptosis in BL cells and reversed the Warburg effect by increasing glucose uptake and reducing lactate production. Moreover, the protein expression of hexokinase 2, pyruvate kinase M2, and lactate dehydrogenase A was significantly suppressed by AT9283, possibly through the inhibition of c-Myc and HIF-1α protein expression. Conclusion: The reversal of the Warburg effect in BL cells and the subsequent inhibition of cell proliferation and induction of apoptosis were observed by targeting Aurora A and Aurora B with AT9283. This finding may present new therapeutic options and targets for BL.

Advances in diagnosis, treatment and prognostic factors of gastrointestinal DLBCL.

Gastrointestinal diffuse large B-cell lymphoma (GI-DLBCL) is an extremely aggressive form of B-cell non-Hodgkin lymphoma (BNHL) which has complex histological characteristics and manifests a high degree of heterogeneity in terms of clinical, morphological, immunological, and genetic features. GI-DLBCL mainly spreads by infiltrating neighboring lymph nodes, and common gastrointestinal complications (GICS) such as obstruction, perforation, or bleeding, frequently arise during the progression of the disease, posing significant challenges in both diagnosing and treating the condition. Meanwhile, the incidence of GI-DLBCL has been gradually increasing in recent years, and its strong invasiveness makes it prone to being misdiagnosed or completely missed. In clinical practice, over half of the patients diagnosed with the disease are in stage III or stage IV. What makes it worse is that certain patients may not exhibit a favorable response to chemotherapy. All these lead to intricacies in management of this disease. Unfortunately, there is currently no large prospective study or evidence-based medical evidence to provide clear guidance on treatment decisions for this specific type of lymphoma. Neither do physicians have a consensus regarding the optimal approach to address this condition. Recent studies have identified the presence of various prognostic factors that significantly impact survival in GI-DLBCL, which demonstrates the unique particularity of GI-DLBCL, and could help optimize the clinical decision.

Association between polycystic ovary syndrome and risk of non-alcoholic fatty liver disease: a meta-analysis.

INTRODUCTION: There have been many studies assessing whether abnormal metabolic and hormone levels among women with polycystic ovary syndrome (PCOS) are associated with a greater risk of non-alcoholic fatty liver disease (NAFLD). However, previous studies repported no consistent outcomes. To provide a comprehensive evaluation regarding the role of PCOS in the risk of NAFLD, we updated the published literature and conducted this systemic review and meta-analysis. MATERIAL AND METHODS: Electronic databases (Web of Science and PubMed) were searched for literature up to October 2022. We used STATA 12.0 software to compute odds ratios (ORs) and 95% confidence intervals (CIs), to evaluate the association between PCOS and risk of NAFLD. RESULTS: The study indicated that PCOS was significantly related to an elevated risk of NAFLD (OR = 2.93, 95% CI 2.38 to 3.62, I2 = 83.7%, p < 0.001). Meta-regression analysis showed that age and body mass index (BMI) were not responsible for heterogeneity across the studies (age: p = 0.096; BMI: p = 0.418). Sensitivity analysis indicated no alteration in the direction of effect when any study was eliminated. Begg's test, Egger's test, Begg's test, and funnel plot indicated a significant risk of publication bias (Egger's test: p = 0.028; Begg's test: p < 0.001). CONCLUSION: This meta-analysis reported that PCOS was associated with an elevated risk of NAFLD. Early proper detection of NAFLD for PCOS women is essential. All patients with PCOS should undergo appropriate diagnostics for early detection of fatty liver and fibrosis.

Application of R2-ISS risk stratification to patients with multiple myeloma treated with autologous stem cell transplants at UAMS.

The Second Revision of the International Staging System (R2-ISS) was published in 2022 and has been validated in several cohorts of patients with multiple myeloma (MM). In this study, we investigated a total of 860 patients with MM who received an upfront autologous stem cell transplantation between 2001 and 2021. The median age of the patients was 60 years, with a median overall survival (OS) of 123 months and median progression-free survival (PFS) of 70 months. We collected the variables included in the ISS, R-ISS, and R2-ISS systems as well as additional standard variables. Our analyses demonstrated that all 3 ISS series systems (ISS, R-ISS, and R2-ISS) exhibited robust discrimination in terms of both OS and PFS among our study cohort. The ISS system effectively stratified patients into 3 risk groups, whereas the R-ISS system accurately identified patients at extremely high or low risk. The R2-ISS system further refined risk stratification by dividing patients into 4 more balanced risk groups. Furthermore, we specifically focused on identifying variables that distinguished patients with OS < 3 years and OS > 10 years within the low-risk R2-ISS stages (I and II) and high-risk R2-ISS stages (III and IV). Our findings revealed that age, hemoglobin, and 1p deletion significantly influenced the classification of patients in the low-risk R2-ISS stage. Additionally, serum light chain, platelet count, age, and the presence of the t(14;16) translocation were found to affect high-risk classification.

Advances in the pathogenesis and therapeutic strategies of angioimmunoblastic T-cell lymphoma.

Angioimmunoblastic T-cell lymphoma (AITL) is an aggressive subtype of peripheral T-cell lymphomas with its cell origin determined to be follicular helper T-cells. AITL is characterized by a prominent tumor microenvironment involving dysregulation of immune cells, signaling pathways, and extracellular matrix. Significant progress has been made in the molecular pathophysiology of AITL, including genetic mutations, immune metabolism, hematopoietic-derived microenvironment, and non-hematopoietic microenvironment cells. Early diagnosis, detection of severe complications, and timely effective treatment are crucial for managing AITL. Treatment typically involves various combination chemotherapies, but the prognosis is often poor, and relapsed and refractory AITL remains challenging, necessitating improved treatment strategies. Therefore, this article provides an overview of the pathogenesis and latest advances in the treatment of AITL, with a focus on potential therapeutic targets, novel treatment strategies, and emerging immunotherapeutic approaches.

Immune infiltration and drug specificity analysis of different subtypes based on functional status in angioimmunoblastic T-cell lymphoma.

Angioimmunoblastic T-cell lymphoma (AITL) is a subtype of peripheral T-cell lymphoma (PTCL) strongly correlated with worse clinical outcomes. However, the role of characteristic pathway-related genes in patients with AITL (e.g., subtype typing and pathogenesis) remains unknown. In this study, we intended to understand the potential role and prognostic value of characteristic pathways in AITL and identified a model for subtype identification based on pathway-related functional status. Transcriptomic (RNA-seq) data were obtained from the Gene Expression Omnibus database for three sets of tumor tissues from AITL patients. AITL was divided into three clusters based on the pathway profile of patients and the best clustering k = 3, and differentially expressed genes (DEGs) in the three clusters were analyzed. The top 45 important variables associated with characteristic pathways, such as Huntington's disease, VEGF signaling pathway, nucleotide excision repair, ubiquitin-mediated proteolysis, purine metabolism, olfactory transduction, etc., were used to construct a subtype identification model. The model was experimentally validated and proved to possess good predictive efficacy. In addition, pathway-related subtype typing was significantly associated with different immune cell infiltration in AITL. Further analysis revealed that the drug IC50 values predicted also differed markedly among the different subtypes, thus further identifying some subtype-specific drugs. Our study indicates a potential role of characteristic pathways in AITL staging for the first time, provides novel insights for future research targeting AITL, and points to potential therapeutic options for patients with different subtypes of AITL.

Tumor-associated macrophages: new insights on their metabolic regulation and their influence in cancer immunotherapy.

Tumor-associated macrophages (TAMs) are a dynamic and heterogeneous cell population of the tumor microenvironment (TME) that plays an essential role in tumor formation and progression. Cancer cells have a high metabolic demand for their rapid proliferation, survival, and progression. A comprehensive interpretation of pro-tumoral and antitumoral metabolic changes in TAMs is crucial for comprehending immune evasion mechanisms in cancer. The metabolic reprogramming of TAMs is a novel method for enhancing their antitumor effects. In this review, we provide an overview of the recent research on metabolic alterations of TAMs caused by TME, focusing primarily on glucose, amino acid, and fatty acid metabolism. In addition, this review discusses antitumor immunotherapies that influence the activity of TAMs by limiting their recruitment, triggering their depletion, and re-educate them, as well as metabolic profiles leading to an antitumoral phenotype. We highlighted the metabolic modulational roles of TAMs and their potential to enhance immunotherapy for cancer.

Growth and Dark Current Analysis of GaSb- and InP-Based Metamorphic In0.8Ga0.2As Photodetectors.

Short-wavelength infrared photodetectors based on metamorphic InGaAs grown on GaSb substrates and InP substrates are demonstrated. The devices have a pBn structure that employs an AlGaAsSb thin layer as the electron barrier to suppress dark current density. The strain effect on the electrical performance of the devices was specifically studied through the growth of the pBn structure on different substrates, e.g., InP and GaSb, via a specific buffering technique to optimize material properties and minimize dark current. A lower device dark current density, down to 1 × 10-2 A/cm2 at room temperature (295 K), was achieved for the devices grown on the GaSb substrate compared to that of the devices on the InP substrate (8.6 × 10-2 A/cm2). The improved properties of the high-In component InGaAs layer and the AlGaAsSb electron barrier give rise to the low dark current of the photodetector device.

A New Type of Endometrial Cancer Models in Mice Revealing the Functional Roles of Genetic Drivers and Exploring their Susceptibilities.

Endometrial cancer (EC) is the most common female reproductive tract cancer and its incidence has been continuously increasing in recent years. The underlying mechanisms of EC tumorigenesis remain unclear, and efficient target therapies are lacking, for both of which feasible endometrial cancer animal models are essential but currently limited. Here, an organoid and genome editing-based strategy to generate primary, orthotopic, and driver-defined ECs in mice is reported. These models faithfully recapitulate the molecular and pathohistological characteristics of human diseases. The authors names these models and similar models for other cancers as organoid-initiated precision cancer models (OPCMs). Importantly, this approach can conveniently introduce any driver mutation or a combination of driver mutations. Using these models,it is shown that the mutations in Pik3ca and Pik3r1 cooperate with Pten loss to promote endometrial adenocarcinoma in mice. In contrast, the Kras G12D mutati led to endometrial squamous cell carcinoma. Then, tumor organoids are derived from these mouse EC models and performed high-throughput drug screening and validation. The results reveal distinct vulnerabilities of ECs with different mutations. Taken together, this study develops a multiplexing approach to model EC in mice and demonstrates its value for understanding the pathology of and exploring the potential treatments for this malignancy.