International Prognostic Index-Based Immune Prognostic Model for Diffuse Large B-Cell Lymphoma

Should we use nomograms for risk predictions in diffuse large B cell lymphoma patients? A systematic review

Models based on risk stratification are increasingly reported for Diffuse large B cell lymphoma (DLBCL). Due to a rising interest in nomograms for cancer patients, we aimed to review and critically appraise prognostic models based on nomograms in DLBCL patients. A literature search in PubMed/Embase identified 59 articles that proposed prognostic models for DLBCL by combining parameters of interest (e.g., clinical, laboratory, immunohistochemical, and genetic) between January 2000 and 2024. Of them, 40 studies proposed different gene expression signatures and incorporated them into nomogram-based prognostic models. Although most studies assessed discrimination and calibration when developing the model, many lacked external validation. Current nomogram-based models for DLBCL are mainly developed from publicly available databases, lack external validation, and have no applicability in clinical practice. However, they may be helpful in individual patient counseling, although careful considerations should be made regarding model development due to possible limitations when choosing nomograms for prognostication.

Pentraxin 3: A promising therapeutic target for cardiovascular diseases

Cardiovascular disease (CVD) is the primary global cause of death, and inflammation is a crucial factor in the development of CVDs. The acute phase inflammatory protein pentraxin 3 (PTX3) is a biomarker reflecting the immune response. Recent research indicates that PTX3 plays a vital role in CVDs and has been investigated as a possible biomarker for CVD in clinical trials. PTX3 is implicated in the progression of CVDs through mechanisms such as exacerbating vascular endothelial dysfunction, affecting angiogenesis, and regulating inflammation and oxidative stress. This review summarized the structure and function of PTX3, focusing on its multifaceted effects on CVDs, such as atherosclerosis, myocardial infarction, and hypertension. This may help in explaining the varying PTX3 functions and usage, as well as in utilizing target organs to manage diseases. Moreover, elucidating the opposite role of PTX3 in the cardiovascular system will demonstrate the therapeutic and predictive potential in human diseases.

Role of long pentraxin PTX3 in cancer

Cancer has become a leading cause of death and disease burden worldwide, closely related to rapid socioeconomic development. However, the fundamental reason is the lack of comprehensive understanding of the mechanism of cancer, accurate identification of preclinical cancer, and effective treatment of the disease. Therefore, it is particularly urgent to study specific mechanisms of cancer and develop effective prediction and treatment methods. Long Pentraxin PTX3 is a soluble pattern recognition molecule produced by various cells in inflammatory sites, which plays a role as a promoter or suppressor of cancer in multiple tumors through participating in innate immune response, neovascularization, energy metabolism, invasion, and metastasis mechanisms. Based on this, this article mainly reviews the role of PTX3 in various cancers.

The genetic polymorphisms of immune-related genes contribute to the susceptibility and survival of lymphoma

BACKGROUND

Though immunological abnormalities have been proven involved in the pathogenesis of lymphoma, the underlying mechanism remains unclear.

METHODS

We investigated 25 single nucleotide polymorphisms (SNPs) of 21 immune-related genes and explored their roles in lymphoma. The genotyping assay of the selected SNPs was used by the Massarray platform. Logistic regression and Cox proportional hazards models were used to analyze the associations of SNPs and the susceptibility of lymphoma or clinical characteristics of lymphoma patients. In addition, Least Absolute Shrinkage and Selection Operator regression was used to further analyze the relationships with the survival of lymphoma patients and candidate SNPs, and the significant difference between genotypes was verified by the expression of RNA.

RESULTS

By comparing 245 lymphoma patients with 213 healthy controls, we found eight important SNPs related to the susceptibility of lymphoma, which were involved in JAK-STAT, NF-κB and other functional pathways. We further analyzed the relationships between SNPs and clinical characteristics. Our results showed that both IL6R (rs2228145) and STAT5B (rs6503691) significantly contributed to the Ann Arbor stages of lymphoma. And the STAT3 (rs744166), IL2 (rs2069762), IL10 (rs1800871), and PARP1 (rs907187) manifested a significant relationship with the peripheral blood counts in lymphoma patients. More importantly, the IFNG (rs2069718) and IL12A (rs6887695) were associated with the overall survival (OS) of lymphoma patients remarkably, and the adverse effects of GC genotypes could not be offset by Bonferroni correction for multiple comparison in rs6887695 especially. Moreover, we determined that the mRNA expression levels of IFNG and IL12A were significantly decreased in patients with shorter-OS genotypes.

CONCLUSIONS

We used multiple methods of analysis to predict the correlations between lymphoma susceptibility, clinical characteristics or OS with SNPs. Our findings reveal that immune-related genetic polymorphisms contribute to the prognosis and treatment of lymphoma, which may serve as promising predictive targets.

B-Cell Receptor Signaling Is Thought to Be a Bridge between Primary Sjogren Syndrome and Diffuse Large B-Cell Lymphoma

Primary Sjogren syndrome (pSS) is the second most common autoimmune disorder worldwide, which, in the worst scenario, progresses to Non-Hodgkin Lymphoma (NHL). Despite extensive studies, there is still a lack of knowledge about developing pSS for NHL. This study focused on cells' signaling in pSS progression to the NHL type of diffuse large B-cell lymphoma (DLBCL). Using bulk RNA and single cell analysis, we found five novel pathologic-independent clusters in DLBCL based on cells' signaling. B-cell receptor (BCR) signaling was identified as the only enriched signal in DLBCL and pSS peripheral naive B-cells or salivary gland-infiltrated cells. The evaluation of the genes in association with BCR has revealed that targeting CD79A, CD79B, and LAMTOR4 as the shared genes can provide novel biomarkers for pSS progression into lymphoma.

Aggressive diffuse large B-cell lymphoma manifested by splenic rupture progressed 2 months after transverse myelitis: an autopsy case report

Background

Splenic rupture by diffuse large B-cell lymphoma (DLBCL), which usually progresses insidiously, is extremely rare.

Case Presentation

A 60-year-old man presented with paralysis in his lower left extremity. A magnetic resonance imaging suggested transverse myelitis. No lymphadenopathy or organomegaly was noted. Two months after remission, he was referred to the emergency department complaining of presyncope. He was in preshock due to splenic rupture, and underwent laparotomy after attempts of transcatheter arterial embolization. Splenomegaly, hepatomegaly, and disseminated enlarged lymph nodes were observed. Histological examinations of the resected spleen showed DLBCL. He died of multiple organ failure associated with intractable bleeding. His autopsy revealed diffuse systemic invasions of lymphoma cells except for the brain and spinal cord. Microscopically, the spinal cord showed macular incomplete necrosis and histiocytic infiltration, suggestive of hemophagocytic syndrome.

Conclusion

The progression of DLBCL in our case is drastically rapid. Undiagnosed transverse myelitis preceded the onset.

An Externally Validated Nomogram for Predicting the Overall Survival of Patients With Diffuse Large B-Cell Lymphoma Based on Clinical Characteristics and Systemic Inflammatory Markers

Background: Systemic inflammatory indicators are clinically significant in guiding diffuse large B-cell lymphoma (DLBCL) prognosis. However, which inflammatory markers are the best predictors of DLBCL prognosis is still unclear. In this study, we aimed to create a nomogram based on the best inflammatory markers and clinical indicators to predict the overall survival of patients with DLBCL. Patients and methods: We analyzed data from 423 DLBCL patients from two institutions and divided them into a training set, an internal validation set, and an external validation set (n = 228, 97, and 98, respectively). The least absolute shrinkage and selection operator and Cox regression analysis were used to develop nomograms. We assessed model fit using the Akaike information criterion and Bayesian information criterion. The concordance index (C-index), calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) were used to assess the nomogram's predictive performance and clinical net benefit and compared with the International Prognostic Index (IPI) and National Comprehensive Cancer Network (NCCN)-IPI. Results: The inclusion variables for the nomogram model were age, Eastern Cooperative Oncology Group performance status, lactate dehydrogenase level, the systemic immune-inflammation index (SII), the prognostic nutritional index (PNI), and β-2 microglobulin (β-2 MG) level. In the training cohort, the nomogram showed better goodness of fit than the IPI and NCCN-IPI. The C-index of the nomogram (0.804, 95% CI: 0.751-0.857) outperformed the IPI (0.690, 95% CI: 0.629-0.751) and NCCN-IPI (0.691, 95% CI: 0.632-0.750). The calibration curve, ROC curve, and DCA curve analysis showed that the nomogram has satisfactory predictive power and clinical utility. Similar results were found in the validation cohort. Conclusion: The nomogram integrated with the clinical characteristics and inflammatory markers is beneficial to predict the prognosis of patients with DLBCL.

Analysis of the regulatory mechanisms of prognostic immune factors in thyroid cancer

Objective

To explore the regulatory mechanism of immune prognostic factors in thyroid cancer.

Methods

Based on the TCGA database and GEO database, this study used bioinformatics methods to study the potential regulatory mechanism of thyroid cancer prognosis, analyzed the differentially expressed genes and differential miRNAs between thyroid cancer and normal paracancerous tissues by R software, and constructed lasso risk factors. The immune prognostic factors of thyroid cancer were obtained from the model, and the miRDB website was used to predict the possibility of differential miRNA target binding of the immune prognostic factors and correlation analysis was performed, and finally verified by cell experiments.

Results

There were 1413 differentially expressed genes between thyroid cancer and normal paracancerous tissues, among which 21 immune-related genes were prognostic factors with significant differences in expression; lasso risk model obtained AKAP12, APOC1, TIMP3, ADAMTS9, ANK2, HTRA3, SYNDIG1 , ADAMTS5 and DACT1 were nine prognostic factors. A total of 58 differential miRNAs were found in thyroid cancer tissues and non-cancerous tissues. The possibility of differential miRNA targeting and binding of immune prognostic factors on the miRDB website and cell experiments was analyzed.

Conclusions

The potential miRNA regulatory mechanism of immune prognostic factors in thyroid cancer has been explored.

HUNK Gene Alterations in Breast Cancer

Hormonally upregulated neu-associated kinase (HUNK) is a serine/threonine (S/T) protein kinase related to the adenosine monophosphate-activated protein kinase (AMPK) family of kinases. HUNK was originally discovered using a screen to identify kinases expressed in the mouse mammary gland. Therefore, the majority of studies to date have been carried out in models specific to this tissue, and the kinase was named to reflect its mammary gland-specific physiology and pathology. Prior studies show a clear pathogenic role for HUNK in breast cancer. HUNK is upregulated in response to oncogenic HER2/neu and Akt, and there is strong evidence that HUNK is critical for the survival of breast cancer cells. Further evidence shows that inhibiting HUNK using a variety of breast cancer models, including those that are resistant, inhibits tumorigenesis and metastasis. However, HUNK alterations are infrequent. Here, the incidence and consequence of HUNK alterations in breast cancer is reviewed using data mined from the online database cBioPortal and considered in relation to prior research studies.