Multivariate transcriptome analysis identifies networks and key drivers of chronic lymphocytic leukemia relapse risk and patient survival

Unveiling overlooked pathways: The uric acid catabolism genes in the human genome

In hominids, including Homo sapiens, uric acid is the end product of purine catabolism. In contrast, other placental mammals further degrade uric acid to (S)-allantoin by enzymes such as urate oxidase (uricase), HIU hydrolase (HIUase), and OHCU decarboxylase. Some organisms, such as frogs and fish, hydrolyze (S)-allantoin to allantoate and eventually to (S)-ureidoglycolate and urea, while marine invertebrates convert urea to ammonium. In H. sapiens, mutations in the uricase gene led to a reduction in the selective pressure for maintaining the integrity of the genes encoding the other enzymes of the purine catabolism pathway, resulting in an accumulation of uric acid. The hyperuricemia resulting from this accumulation is associated with gout, cardiovascular disease, diabetes, and preeclampsia. Many commonly used drugs, such as aspirin, can also increase uric acid levels. Despite the apparent absence of these enzymes in H. sapiens, there appears to be production of transcripts for uricase (UOX), HIUase (URAHP), OHCU decarboxylase (URAD), and allantoicase (ALLC). While some URAHP transcripts are classified as long non-coding RNAs (lncRNAs), URAD and ALLC produce protein-coding transcripts. Given the presence of these transcripts in various tissues, we hypothesized that they may play a role in the regulation of purine catabolism and the pathogenesis of diseases associated with hyperuricemia. Here, we specifically investigate the unique aspects of purine catabolism in H. sapiens, the effects mutations of the uricase gene, and the potential regulatory role of the corresponding transcripts. These findings open new avenues for research and therapeutic approaches for the treatment of hyperuricemia and related diseases.

Multiple omics levels of chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is a lymphoproliferative malignancy characterized by the proliferation of functionally mature but incompetent B cells. It is the most prevalent type of leukemia in Western populations, accounting for approximately 25% of new leukemia cases. While recent advances, such as ibrutinib and venetoclax treatment have improved patient outlook, aggressive forms of CLL such as Richter transformation still pose a significant challenge. This discrepancy may be due to the heterogeneity of factors contributing to CLL development at multiple -omics levels. However, information on the omics of CLL is fragmented, hindering multi-omics-based research into potential treatment options. To address this, we aggregated and presented a selection of important aspects of various omics levels of the disease in this review. The purpose of the present literature analysis is to portray examples of CLL studies from different omics levels, including genomics, epigenomics, transcriptomics, epitranscriptomics, proteomics, epiproteomics, metabolomics, glycomics and lipidomics, as well as those identified by multi-omics approaches. The review includes the list of 102 CLL-associated genes with relevant genomics information. While single-omics studies yield substantial and useful data, they omit a significant level of complex biological interplay present in the disease. As multi-omics studies integrate several different layers of data, they may be better suited for complex diseases such as CLL and have thus far yielded promising results. Future multi-omics studies may assist clinicians in improved treatment choices based on CLL subtypes as well as allow the identification of novel biomarkers and targets for treatments.

B-1 derived anti-Thy-1 B cells in old aged mice develop lymphoma/leukemia with high expression of CD11b and Hamp2 that different from TCL1 transgenic mice

Human old aged unmutated chronic lymphocytic leukemia U-CLL are the TCL1+ZAP70+CD5+ B cells. Since CD5 makes the BCR signaling tolerance, ZAP70 increased in U-CLL not only TCL1+ alone. In mice, TCL1 (TCL1A) is the negative from neonate to old aged, as TC-. VH8-12/Vk21-5 is the anti-thymocyte/Thy-1 autoreactive ATA B cell. When ATA μκTg generation in mice, ATA B cells are the neonate generated CD5+ B cells in B-1, and in the middle age, CD5+ can be down or continuously CD5+, then, old aged CLL/lymphoma generation with increased CD11b in TC-ZAP70-CD5- or TC-ZAP70+CD5+. In this old aged TC-ATA B microarray analysis showed most similar to human CLL and U-CLL, and TC-ZAP70+CD5+ showed certain higher present as U-CLL. Original neonate ATA B cells showed with several genes down or further increase in old aged tumor, and old aged T-bet+CD11c+, CTNNB1hi, HMGBhi, CXCR4hi, DPP4hi and decreased miR181b. These old aged increased genes and down miR181b are similar to human CLL. Also, in old age ATA B cell tumor, high CD38++CD44++, increased Ki67+ AID+, and decreased CD180- miR15Olow are similar to U-CLL. In this old aged ATA B, increased TLR7,9 and Wnt10b. TC+Tg generated with ATAμκTg mice occurred middle age tumor as TC+ZAP70-CD5+ or TC+ZAP70+CD5+, with high NF-kB1, TLR4,6 and Wnt5b,6 without increased CD11b. Since neonatal state to age with TC+Tg continuously, middle age CLL/lymphoma generation is not similar to old aged generated, however, some increased in TC+ZAP70+ are similar to the old age TC- ATA B tumor. Then, TC- ATA B old age tumor showed some difference to human CLL. ATA B cells showed CD11b+CD22++, CD24 down, and hepcidin Hamp2++ with iron down. This mouse V8-12 similar to human V2-5, and V2-5 showed several cancers with macrophages/neutrophils generated hepcidin+ ironlow or some showed hepcidin- iron+ with tumor, and mouse V8-12 with different Vk19-17 generate MZ B cells strongly increased macrophage++ in old aged and generated intestine/colon tumor. Conclusion, neonate generated TC-ATA B1 cells in old aged tumor generation are CD11b+ in the leukemia CLL together with lymphoma cancer with hepcidin-related Hamp2++ in B-1 cell generation to control iron.

BCL3 rearrangements in B-cell lymphoid neoplasms occur in two breakpoint clusters associated with different diseases

The t(14;19)(q32;q13) often juxtaposes BCL3 with immunoglobulin heavy chain (IGH) resulting in overexpression of the gene. In contrast to other oncogenic translocations, BCL3 rearrangement (BCL3-R) has been associated with a broad spectrum of lymphoid neoplasms. Here we report an integrative whole-genome sequence, transcriptomic, and DNA methylation analysis of 13 lymphoid neoplasms with BCL3-R. The resolution of the breakpoints at single base-pair revealed that they occur in two clusters at 5' (n=9) and 3' (n=4) regions of BCL3 associated with two different biological and clinical entities. Both breakpoints were mediated by aberrant class switch recombination of the IGH locus. However, the 5' breakpoints (upstream) juxtaposed BCL3 next to an IGH enhancer leading to overexpression of the gene whereas the 3' breakpoints (downstream) positioned BCL3 outside the influence of the IGH and were not associated with its expression. Upstream BCL3-R tumors had unmutated IGHV, trisomy 12, and mutated genes frequently seen in chronic lymphocytic leukemia (CLL) but had an atypical CLL morphology, immunophenotype, DNA methylome, and expression profile that differ from conventional CLL. In contrast, downstream BCL3-R neoplasms were atypical splenic or nodal marginal zone lymphomas (MZL) with mutated IGHV, complex karyotypes and mutated genes typical of MZL. Two of the latter four tumors transformed to a large B-cell lymphoma. We designed a novel fluorescence in situ hybridization assay that recognizes the two different breakpoints and validated these findings in 17 independent tumors. Overall, upstream or downstream breakpoints of BCL3-R are mainly associated with two subtypes of lymphoid neoplasms with different (epi)genomic, expression, and clinicopathological features resembling atypical CLL and MZL, respectively.

JW. Multivariant Transcriptome Analysis Identifies Modules and Hub Genes Associated with Poor Outcomes in Newly Diagnosed Multiple Myeloma Patients

The molecular mechanisms underlying chemoresistance in some newly diagnosed multiple myeloma (MM) patients receiving standard therapies (lenalidomide, bortezomib, and dexamethasone) are poorly understood. Identifying clinically relevant gene networks associated with death due to MM may uncover novel mechanisms, drug targets, and prognostic biomarkers to improve the treatment of the disease. This study used data from the MMRF CoMMpass RNA-seq dataset (N = 270) for weighted gene co-expression network analysis (WGCNA), which identified 21 modules of co-expressed genes. Genes differentially expressed in patients with poor outcomes were assessed using two independent sample t-tests (dead and alive MM patients). The clinical performance of biomarker candidates was evaluated using overall survival via a log-rank Kaplan-Meier and ROC test. Four distinct modules (M10, M13, M15, and M20) were significantly correlated with MM vital status and differentially expressed between the dead (poor outcomes) and the alive MM patients within two years. The biological functions of modules positively correlated with death (M10, M13, and M20) were G-protein coupled receptor protein, cell-cell adhesion, cell cycle regulation genes, and cellular membrane fusion genes. In contrast, a negatively correlated module to MM mortality (M15) was the regulation of B-cell activation and lymphocyte differentiation. MM biomarkers CTAG2, MAGEA6, CCND2, NEK2, and E2F2 were co-expressed in positively correlated modules to MM vital status, which was associated with MM's lower overall survival.