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.

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.

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.

BP­1­102 exerts antitumor effects on T­cell acute lymphoblastic leukemia cells by suppressing the JAK2/STAT3/c­Myc signaling pathway.

Drug resistance and relapse of T-cell acute lymphoblastic leukemia (T-ALL) remain significant concerns for physicians; hence, the development and screening of effective targeted drugs remain important. Considering that STAT3 is emerging as a potential therapeutic target for T-ALL, T-ALL cell lines (MOLT-4 and CUTLL1) were treated with BP-1-102, a small-molecule inhibitor that blocks STAT3 phosphorylation. Cell Counting Kit-8 assay and colony formation assay results showed that BP-1-102 inhibited T-ALL cell proliferation and colony formation. Flow cytometry and morphological results demonstrated that BP-1-102 dramatically induced apoptosis and caused cell cycle arrest at the G0/G1 phase in T-ALL cell lines. Western blotting results indicated that BP-1-102 suppressed the JAK2/STAT3/c-Myc pathway activity in T-ALL cell lines. In conclusion, BP-1-102 suppressed the JAK2/STAT3/c-Myc signaling pathway in T-ALL cells and exerted various antitumor effects, representing a promising targeted antitumor inhibitor.

Research progress on epigenetics of small B-cell lymphoma

Small B-cell lymphoma is the classification of B-cell chronic lymphoproliferative disorders that include chronic lymphocytic leukaemia/small lymphocytic lymphoma, follicular lymphoma, mantle cell lymphoma, marginal zone lymphoma, lymphoplasmacytic lymphoma/Waldenstrom macroglobulinemia. The clinical presentation is somewhat heterogeneous, and its occurrence and development mechanisms are not yet precise and may involve epigenetic changes. Epigenetic alterations mainly include DNA methylation, histone modification, and non-coding RNA, which are essential for genetic detection, early diagnosis, and assessment of treatment resistance in small B-cell lymphoma. As chronic lymphocytic leukemia/small lymphocytic lymphoma has already been reported in the literature, this article focuses on small B-cell lymphomas such as follicular lymphoma, mantle cell lymphoma, marginal zone lymphoma, and Waldenstrom macroglobulinemia. It discusses recent developments in epigenetic research to diagnose and treat this group of lymphomas. This review provides new ideas for the treatment and prognosis assessment of small B-cell lymphoma by exploring the connection between small B-cell lymphoma and epigenetics. (AU)

Research progress on epigenetics of small B-cell lymphoma.

Small B-cell lymphoma is the classification of B-cell chronic lymphoproliferative disorders that include chronic lymphocytic leukaemia/small lymphocytic lymphoma, follicular lymphoma, mantle cell lymphoma, marginal zone lymphoma, lymphoplasmacytic lymphoma/Waldenstrom macroglobulinemia. The clinical presentation is somewhat heterogeneous, and its occurrence and development mechanisms are not yet precise and may involve epigenetic changes. Epigenetic alterations mainly include DNA methylation, histone modification, and non-coding RNA, which are essential for genetic detection, early diagnosis, and assessment of treatment resistance in small B-cell lymphoma. As chronic lymphocytic leukemia/small lymphocytic lymphoma has already been reported in the literature, this article focuses on small B-cell lymphomas such as follicular lymphoma, mantle cell lymphoma, marginal zone lymphoma, and Waldenstrom macroglobulinemia. It discusses recent developments in epigenetic research to diagnose and treat this group of lymphomas. This review provides new ideas for the treatment and prognosis assessment of small B-cell lymphoma by exploring the connection between small B-cell lymphoma and epigenetics.

The Research Progress in Physiological and Pathological Functions of TRAF4.

Tumour necrosis factor receptor-associated factor 4 (TRAF4) is a member of the TRAF protein family, a cytoplasmic bridging molecule closely associated with various immune functions. The physiological processes of TRAF4 are mainly involved in embryonic development, cell polarity, cell proliferation, apoptosis, regulation of reactive oxygen species production. TRAF4 is overexpressed in a variety of tumors and regulates the formation and development of a variety of tumors. In this review, we summarize the physiological and pathological regulatory functions of TRAF4 and focus on understanding the biological processes involved in this gene, to provide a reference for further studies on the role of this gene in tumorigenesis and development.

Identification of diagnosis and prognosis gene markers in B-ALL with ETV6-RUNX1 fusion by integrated bioinformatics analysis.

B-acute lymphoblastic leukemia (B-ALL) is characterized by clonal expansion of immature B-lymphocytes in the bone marrow, blood, or other tissues. Chromosomal translocations have often been reported in B-ALL, which are important for its prognosis. B-ALL patients with ETV6-RUNX1 fusion have favorable outcomes, but the mechanisms remain to be clarified. In the present study, we crossed the selected WGCNA module genes and differential expression genes to obtain core genes, and random forest algorithm, a type of supervised learning analysis, was conducted to evaluate the importance of those core genes in distinguishing B-ALL samples with ETV6-RUNX2 fusion with extracting 5 genes as gene markers for ETV6-RUNX2 fusion. Moreover, we calculated the immune infiltration profiles and screened out the ETV6-RUNX2 association immune cells using the CIBERSORT algorithm. In conclusion, combined with various solid informatics methods, we depicted the underlying molecular and immune mechanism of ETV6-RUNX2 fusion and providing potential biological targets for diagnosing and treating B-ALL in the future.