Prognostic factors in CLL
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Cholesterol homeostasis and lipid raft dynamics at the basis of tumor-induced immune dysfunction in chronic lymphocytic leukemia
Autologous T-cell therapies show limited efficacy in chronic lymphocytic leukemia (CLL), where acquired immune dysfunction prevails. In CLL, disturbed mitochondrial metabolism has been linked to defective T-cell activation and proliferation. Recent research suggests that lipid metabolism regulates mitochondrial function and differentiation in T cells, yet its role in CLL remains unexplored. This comprehensive study compares T-cell lipid metabolism in CLL patients and healthy donors, revealing critical dependence on exogenous cholesterol for human T-cell expansion following TCR-mediated activation. Using multi-omics and functional assays, we found that T cells present in viably frozen samples of patients with CLL (CLL T cells) showed impaired adaptation to cholesterol deprivation and inadequate upregulation of key lipid metabolism transcription factors. CLL T cells exhibited altered lipid storage, with increased triacylglycerols and decreased cholesterol, and inefficient fatty acid oxidation (FAO). Functional consequences of reduced FAO in T cells were studied using samples from patients with inherent FAO disorders. Reduced FAO was associated with lower T-cell activation but did not affect proliferation. This implicates low cholesterol levels as a primary factor limiting T-cell proliferation in CLL. CLL T cells displayed fewer and less clustered lipid rafts, potentially explaining the impaired immune synapse formation observed in these patients. Our findings highlight significant disruptions in lipid metabolism as drivers of functional deficiencies in CLL T cells, underscoring the pivotal role of cholesterol in T-cell proliferation. This study suggests that modulating cholesterol metabolism could enhance T-cell function in CLL, presenting novel immunotherapeutic approaches to improve outcome in this challenging disease.
Genomic characterization of chronic lymphocytic leukemia in patients of African ancestry
Despite the considerable effort to characterize the genomic landscape of chronic lymphocytic leukemia (CLL), published data have been almost exclusively derived from patients of European Ancestry (EA), with significant underrepresentation of minorities, including patients of African Ancestry (AA). To begin to address this gap, we evaluated whether differences exist in the genetic and transcriptomic features of 157 AA and 440 EA individuals diagnosed with CLL. We sequenced 59 putative driver genes and found an increased frequency of high-impact mutations in AA CLL, including genes of the DNA damage repair (DDR) pathway. Telomere erosion was also increased in AA CLL, amplifying the notion of increased genomic instability in AA CLL. Furthermore, we found transcription enrichment of the Tumor Necrosis Factor-alpha (TNFα) Signaling via NF-κB pathway in AA CLL compared to EA CLL, suggesting that tumor promoting inflammation plays an important role in AA CLL. In summary, these results suggest that genomic instability and NF-kB activation is more prevalent in AA CLL than EA CLL.
Transcriptomic clustering of chronic lymphocytic leukemia: molecular subtypes based on Bruton’s tyrosine kinase expression levels
Historically, CLL prognostication relied on disease burden, reflected in clinical stage. Later, chromosome abnormalities and genomics suggested several CLL subtypes which were aligned with response to therapy. Gene expression profiling data identified pathways associated with CLL progression. We hypothesized that transcriptome and proteome may identify functional omics associated with CLL nosology. As a test cohort, we utilized publicly available treatment-naïve CLL transcriptomics data (n = 130) and did consensus clustering that identified BTK-expression-based clusters. The BTK-High and BTK-Low clusters were validated in public and our in-house databases (n = >550 CLL patients). To associate with functional relevance, we took samples from 151 previously treated patient with CLL and analyzed them using RNA sequencing and reverse-phase protein array. Transcript levels were strongly correlated with BTK protein levels. BTK-High subtype showed increased CCL3/CCL4 levels and disease burden such as high WBC. BTK-Low subtype showed down-regulated mRNA/proteins of DNA-repair pathway and increased DNA-damage-response, which may have contributed to enrichment of inflammatory pathway. BTK-Low subtype was rich in proapoptotic gene and protein expression and relied less on BCR pathway. High-BTK subgroup was enriched in replication/repair pathway and transcription machinery. In conclusion, profiling of 5 datasets of ~700 patients revealed unique BTK-associated expression clusters in CLL.
Multiomic quantification of the KRAS mutation dosage improves the preoperative prediction of survival and recurrence in patients with pancreatic ductal adenocarcinoma
Most cancer mutation profiling studies are laboratory-based and lack direct clinical application. For clinical use, it is necessary to focus on key genes and integrate them with relevant clinical variables. We aimed to evaluate the prognostic value of the dosage of the KRAS G12 mutation, a key pancreatic ductal adenocarcinoma (PDAC) variant and to investigate the biological mechanism of the prognosis associated with the dosage of the KRAS G12 mutation. In this retrospective cohort study, we analyzed 193 surgically treated patients with PDAC between 2009 and 2016. RNA, whole-exome, and KRAS-targeted sequencing data were used to estimate the dosage of the KRAS G12 mutant. Our prognostic scoring system included the mutation dosage from targeted sequencing ( > 0.195, 1 point), maximal tumor diameter at preoperative imaging ( > 20 mm, 1 point), and carbohydrate antigen 19-9 levels ( > 150 U/mL, 1 point). The KRAS mutation dosage exhibited comparable performance with clinical variables for survival prediction. High KRAS mutation dosages activated the cell cycle, leading to high mutation rates and poor prognosis. According to prognostic scoring systems that integrate mutation dosage with clinical factors, patients with 0 points had superior median overall survival of 97.0 months and 1-year, 3-year, and 5-year overall survival rates of 95.8%, 70.8%, and 66.4%, respectively. In contrast, patients with 3 points had worse median overall survival of only 16.0 months and 1-year, 3-year, and 5-year overall survival rates of 65.2%, 8.7%, and 8.7%, respectively. The incorporation of the KRAS G12 mutation dosage variable into prognostic scoring systems can improve clinical variable-based survival prediction, highlighting the feasibility of an integrated scoring system with clinical significance.
High WEE1 expression is independently linked to poor survival in multiple myeloma
Current prognostic scores in multiple myeloma (MM) currently rely on disease burden and a limited set of genomic alterations. Some studies have suggested gene expression panels may predict clinical outcomes, but none are presently utilized in clinical practice. The tyrosine kinase WEE1 is a critical cell cycle regulator during the S-phase and G2M checkpoint. Abnormal WEE1 expression has been implicated in multiple cancers including breast, ovarian, and gastric cancers, but its prognostic signal in MM has not been thoroughly reported. We, therefore, analyzed the MMRF CoMMpass dataset (N = 659) and identified a high-risk group (top tertile) and a low-risk group (bottom tertile) based on WEE1 expression sorted in descending order. PFS was significantly different (p < 1e-9) between the groups, which was validated in two independent microarray gene expression profiling (GEP) datasets from the Total Therapy 2 (N = 341) and 3 (N = 214) trials. Our results show that WEE1 expression is prognostic independent of known biomarkers, differentiates outcomes associated with known markers, is upregulated independently of its interacting neighbors, and is associated with dysregulated P53 pathways. This suggests that WEE1 expression levels may have clinical utility in prognosticating outcomes in newly diagnosed MM and may support the application of WEE1 inhibitors to MM preclinical models. Determining the causes of abnormal WEE1 expression may uncover novel therapeutic pathways.
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