A copper-linked RNA pattern that may predict outcomes and guide treatment in a common type of lymphoma

Diffuse large B cell lymphoma (DLBCL) is the most common type of non-Hodgkin’s lymphoma. Due to the high heterogeneity of DLBCL, treatment response and prognosis vary widely among DLBCL patients¹. Currently, the first-line treatment regimen for DLBCL patients is R-CHOP, including rituximab plus cyclophosphamide, doxorubicin, vincristine and prednisone². Approximately 60% of patients with DLBCL achieve remission following R-CHOP regimen, while around 40% of patients remain unresponsive and 10–15% are classified as primary refractory cases³. At present, the International Prognostic Index (IPI) is the predominant method utilized to assess prognosis and guide treatment decisions for patients with DLBCL. However, IPI relies only on clinical factors and may not provide a comprehensive forecast of patient outcomes. In recent years, with the advancements in high-throughput sequencing technology, an increasing number of novel indicators with potential predictive value for DLBCL progression have been identified. Studies suggest that incorporating molecular features and tumor microenvironment (TME) into the IPI may be helpful to characterize the signatures of recurrent and refractory lymphoma and select more appropriate treatment⁴. Therefore, there is an urgent need to develop more comprehensive risk models for DLBCL patient.

Copper is a vital nutrient, however, an excess of copper can lead to oxidative stress and cytotoxicity, which is found to be closely related to tumor initiation, development and metastasis^5–7. Higher levels of copper has been found in malignant tumors compared with normal tissues, indicating its potential role in tumor advancement⁸. Similar results were found in lymphoma. Higher levels of copper was found in serum and lymphoma tissue compared with normal tissue ⁹. Besides, serum copper levels have been identified as an independent prognostic factor for lymphoma patients, and are closely related to tumor activity^10,11. Copper ion carrier and copper chelator exhibit cancer-resistant properties. Studies have shown that copper compounds can induce apoptosis in lymphoma cell lines in vitro and reduce the growth of lymphoma in vivo^12–14. The copper chelating agent ATN-224 has demonstrated the ability to induce caspase-independent cell death in DLBCL, which is expected to be a new treatment for relapsed and refractory DLBCL¹⁵. Cuproptosis, a new type of programmed cell death, differs from other cell death pathways such as apoptosis, ferroptosis, and necroptosis¹⁶. It is demonstrated that cuproptosis is initiated by the direct interaction of copper with lipoylated components of the tricarboxylic acid (TCA) cycle, which leads to the aggregation of lipid acylated proteins and subsequent depletion of iron-sulfur cluster proteins. This cascade of events results in proteotoxic stress and cell death ultimately¹⁶. Cuproptosis is believed to play a crucial role in tumor suppression, highlighting its potential for targeted anti-cancer therapy. A recent study has shown that cupreous nanomaterials can induce cuproptosis in bladder cancer¹⁷. Combining nanomedicine that can induce cuproptosis with Programmed Cell Death-Ligand 1 (PD-L1) antibody can enhance bladder cancer therapy¹⁸. These findings provide a novel strategy for future cancer therapy. Furthermore, the expression of cuproptosis related genes in lymphoma has also been detected¹⁹. Therefore, further research on cuproptosis-related pathways and their regulatory molecular mechanisms is warranted and of great significance.

Long noncoding RNAs (lncRNAs), a group of non-coding RNAs longer than 200 nucleotides, play an important role in immune response, including immune cells infiltration, antigen recognition, antigen exposure and tumor suppression²⁰. Extensive research has demonstrated the association between IncRNAs and tumor proliferation, invasion, metastasis and prognosis²¹. Moreover, studies have showed the role of lncRNAs in the pathogenesis and progression of DLBCL. For example, it has been demonstrated that the ALKBH5-mediated N6-methyladenosine modification of TRERNA1 promotes proliferation of DLBCL cells via p21 downregulation²². LINC00461 was shown to inhibit apoptosis and promoting recurrence in DLBCL through miR-411-5p/BNIP3 pathway²³.Through meta-analysis, Xu et al. found that lncRNA expression profile could aid in the diagnosis and classification of DLBCL, and abnormal lncRNA expression level was associated with poor prognosis of DLBCL patients, indicating that lncRNAs can be used as candidate prognostic biomarkers for DLBCL²⁴.

At present, the pathogenesis of DLBCL remains incompletely understood. Studies indicates the important role of lncRNA in DLBCL. Cuproptosis-related genes expression levels are associated with the prognosis of DLBCL patients, but their function has not been fully elucidated. It is important to identify cuproptosis-related lncRNAs with prognostic value in DLBCL patients. In this study, we investigated the relationship between cuproptosis-related lncRNAs and DLBCL using bioinformatics analysis. Our findings may provide novel insights into clinical individual treatment of DLBCL.

The detailed flow chart of the study is displayed in Supplementary Fig. 1

Due to the high heterogeneity of DLBCL in both biological and clinical features, there is significant variation in the prognosis of patients with DLBCL. At present, the IPI is the predominant method utilized to assess prognosis and guide treatment decisions for patients with DLBCL. Age and stage are the components of the IPI. Older age and later stage are associated with a larger IPI score and poorer prognosis. However, IPI relies only on clinical factors and may not provide a comprehensive forecast of DLBCL patient outcomes. The prognosis of DLBCL is affected by multiple factors including clinical characteristics, molecular subtype and the tumor microenvironment. No single biomarker can accurately identify the prognosis of DLBCL patients. Our study suggests that age, stage and gender do not impact the prognosis of DLBCL independently. Research shown that the effect of age on prognosis varies not only by NHL subtype, but also by gender within certain subtypes²⁶. In treated DLBCL patients, efficacy and PFS were not affected by age²⁷. The heterogeneity of NHL, the refinement of histopathological categorization, and the high incidence of advanced stage of lymphoma make the Ann Arbor classification of NHL insufficiently²⁸. Only the advanced Ann Arbor stage and age over 60 years are two major factors predicting poor prognosis in patients with DLBCL subtype, but not as an independent prognostic factors of the OS in DLBCL patients²⁹. IPI relies only on clinical factors and fails to fully capture the molecular biological heterogeneity involved in the occurrence and progression of DLBCL. Consequently, it cannot accurately stratify the risk and predict the prognosis of DLBCL. Therefore, it is urgent to develop novel prognostic evaluation models. Previous research has demonstrated that copper plays an anti-tumor role by regulating cell death¹⁶. Copper have been confirmed involved in the occurrence and development of malignant tumors, but few studies focused on cuproptosis-related lncRNAs. Therefore, our study aims to elucidate the role of cuproptosis-related lncRNAs in DLBCL progression, and develop a prognostic model which can indicate the prognosis of DLBCL patients more accurately.

Homologous lncRNAs can play different roles in different tumors. For example, LncRNA NEAT1 regulates pyroptosis in glioma cells and colorectal cancer cells by targeting miR-296-5p or miR-448; while its high expression promotes ferroptosis in non-small cell lung cancer³⁰. Studies on the relationship between lncRNA and cuproptosis have been reported in various diseases. LncRNA MIR31HG can inhibit cuproptosis and promote the proliferation, migration, and invasion of lung adenocarcinoma cells by down-regulating miR-193a-3p and increasing downstream TNFRSF21 expression³¹. LncRNA XIST can sponge miR-92b-3p and regulate the cuproptosis-related gene MTF1 to influence the progression of breast cancer³². LncRNAs are valuable prognostic indicators for patients with tumor, and play important roles in initiation, development, and progression of DLBCL^33–35. Our research suggests that a prognostic risk model based on cuproptosis-related lncRNAs can effectively predict the prognosis of DLBCL patients, offering practical implications for clinical use. Among the seven lncRNAs included in the risk model, LINC00654 has been identified as the hub lncRNA in DLBCL patients, and LncRNA00654-NINL mRNA regulatory axis could be involved in DLBCL progression³⁶. The rapid onset of radiation-induced lymphoma observed in NINL transgenic mice confirms an oncogenic role for NINL gene³⁷. Our data indicates that LINC00654 is a high-risk lncRNA in DLBCL, and decreasing its expression may inhibitor tumor growth. We hypothesize that increased levels of LINC00654 in DLBCL result in elevated expression of the NINL gene, which negatively regulates cuproptosis through modulation of cell cycle changes, thus promoting the progression of DLBCL. LINC00294 has been discovered as an oncogene in various tumors. For example, LINC00294 inhibits mitochondrial function and promotes glioma cell apoptosis via miR-21-5p/CASKIN1/cAMP axis³⁸. Additionally, LINC00294 can promote cervical cancer development by promoting cell cycle transition³⁹. Further investigation is needed to understand the involvement of LINC00294 in regulating cuproptosis. Significantly, we observed that LINC00294 expression was lower in the high-risk group than that in the low-risk group. WWC2-AS2, LINC00661 and RNF139-AS1 were identified as prognostic indicators in lung adenocarcinoma, cholangiocarcinoma and bladder cancer, respectively^40–42. In our study, novel lncRNAs including LINC00294, WWC2-AS2, LINC00661, RNF139-AS1, LINC01165 and LINC01398 were identified in DLBCL for the first time. However, the regulatory connection between lncRNAs and cuproptosis has primarily been examined through database analysis, with limited experimental investigations conducted on these associations. The expression pattern, clinical relevance and underlying mechanisms of these lncRNAs in DLBCL patients is still poorly understood. Therefore, more studies are needed to elucidate the function of these lncRNAs in the pathogenesis of DLBCL.

The tumor microenvironment consists of tumor cells, infiltrating immune cells, bone marrow-derived inflammatory cells, fibroblasts, signaling molecules, peripheral blood vessels and extracellular matrix. Immune cell infiltration is a immunological feature of the tumor microenvironment and is essential for the development of inflammatory environment and immune escape of tumor cells. Previous studies on lymphoma suggested that all TME cells exhibit varying survival associations, which demonstrated context-dependent heterogeneity in clinical outcomes⁴³. In this study, a notable increase in the proportion of immune cells, including regulatory T (Treg) cells, neutrophils, mast cells, eosinophils, γδ T cells, and type 2 helper T cells was observed in high-risk DLBCL group. The imbalance between immune effector cells and immune suppressive cells may lead to a disturbed immune microenvironment, leaving an immunosuppressed state in DLBCL. Treg cells has been identified as major contributors to a suppressive immune microenvironment, and the increased proportion of Treg cells are associated with worse outcomes in DLBCL^44,45. The proportion of Treg cells in peripheral blood may be good prognostic markers for OS after 2 years in relapsed refractory DLBCL patients⁴⁶. The neutrophil/lymphocyte (N/L) ratio at diagnosis has been proved to be a prognostic factor for survival in DLBCL, and patients with an N/L ratio < 3.5 at diagnosis experienced a superior OS compared with those with an N/L ratio ≥ 3.5 at diagnosis⁴⁷. Higher neutrophils and N/L ratio may indicate a poorer prognosis for DLBCL patients at diagnosis⁴⁸. These findings are highly consistent with our results. In summary, the cuproptosis-related lncRNA-based risk model may play an important role in indicating immune cell infiltration of DLBCL. The immune regulatory mechanisms by which the above cells infiltration contributes to tumor invasion and progression in DLBCL need to be further investigated.

Through functional enrichment analysis, we found that differentially expressed genes between the low-risk and high-risk groups were mainly enriched in cell metabolic pathways, including phospholipid metabolic pathways, cellular carbohydrate metabolic pathways, regulation of carbohydrate biosynthetic process, and primary bile acid biosynthesis pathways. Mitochondrial metabolism plays a central role in cell metabolism, and many metabolic pathways such as the tricarboxylic acid cycle (TCA), oxidative phosphorylation, fatty acid oxidation, nucleotide synthesis and amino acid metabolism occur in mitochondria. Research shows that disruptions in copper homeostasis can lead to aberrant metabolic process^49,50.Mitochondrial respiration has been considered as vital process in cuproptosis¹⁶. This suggests that there may be differences in mitochondrial metabolism between the high-risk and low-risk groups, which may be one of the potential reasons for the different prognoses between the two groups. Furthermore, differentially expressed genes were also enriched in signal transduction, inflammation pathways, such as response to ROS, MAPK signaling pathway, HIF-1 signaling pathway, Ras signaling pathway. These pathways have been found to be involved in the progression and therapeutic response of DLBCL. For example, TEOA inhibits tumor proliferation and induces DNA damage of DLBCL cells through activation of the ROS-dependent p38 MAPK signaling pathway⁵¹. The activation of HIF-1α results in suppression of translation under hypoxic stress in DLBCL⁵². HIF-1 expression predicts superior survival in patients with DLBCL treated with R-CHOP⁵³. Apatinib exerts anti-tumor activity by inhibition of the Ras pathway in DLBCL⁵⁴. These may be potential targets for prevention and treatment of DLBCL. The underlying mechanism how cuproptosis-related lncRNA induces cuproptosis in DLBCL by the above signaling pathways still needs further investigation.

We found that the IC50 value of most drugs increased with the increase of risk score, which suggested that patients in high-risk group may develop resistance to most anticancer drugs. Our study also indicated that high-risk patients may be sensitive to vinorelbine and pyrimethamine. R-CHOP chemotherapy is the standard treatment for patients with DLBCL, but vincristine induced peripheral neuropathy, which occurs in more than a third of the patients, might require earlier treatment discontinuation⁵⁵. Vinorelbine induces cell cycle arrest in the G2-M phase, its inhibition leads to premature mitotic entry and cell death. Studies have shown that replacement of vincristine by vinorelbine due to neuropathy is effective and safe, which significantly improve neuropathy in patients compared to treatment with R-CHOP⁵⁶. The regimen including rituximab, vinorelbine, ifosfamide, mitoxantrone and prednisone displays significant activity and acceptable toxicity in relapsed DLBCL⁵⁷. The combination of prednisolone, vinorelbine, etoposide, cyclophosphamide and rituximab dramatically increases the 24-months disease free survival (74%) in vulnerable elderly NHL patients as compared to treatment with mini R-CHOP (60%)⁵⁸. So far, the application of pyrimidine in DLBCL has not been reported. In conclusion, vinorelbine and pyrimidine may be potential therapeutic targets for DLBCL, which provides the basis for precise individualized treatment for DLBCL patients.

However, there are still limitations in this study. Firstly, the number of DLBCL samples in TCGA and GSE10846↗ data is not enough, and we need additional data from different databases for external validation of our model. Secondly, the cuproptosis-related lncRNAs that can guide DLBCL prognosis and the immune microenvironment obtained in this study require further research into the biological function.

In summary, we have developed a risk model incorporating a signature of cuproptosis-related lncRNA that demonstrates independent prognostic value for DLBCL.In addition, our preliminary analysis has indicated a relationship between the risk model and immunological characteristics, which offers insights into the underlying mechanism of cuproptosis and suggests individual and precise therapeutic strategies in DLBCL. The cuproptosis-related lncRNA-based risk model integrates the clinical characteristics, molecular biomarkers, immune microenvironment on the prognosis of DLBCL patients, which provides a new perspective for the stratified diagnosis of DLBCL. However, this model does not explicitly consider the effect of gene mutation factors on the prognosis of patients. In addition, it is important to acknowledge the limitations of this model, such as sample size, potential confounders, and the external validity. Future studies will therefore be necessary to validate our findings in independent cohorts and through experimental validation.