Autophagy-related genes affect the survival of multiple myeloma patients depending on chromosomal abnormality

Ethics committee approval was not necessary for this study because publicly open information from the Gene Expression Omnibus (GEO) database (ncbi.nlm.nih.gov/geo/) was used.

The present study undertakes an investigation into the role of ABN in the survival analysis of MM patients. Our findings address 2 major conclusions. First, it is clearly shown that ABN is the most severe factor causing mortality (among other factors such as sex, age, treatment protocol, and race). Second, it is evident that the patients with ABN have radically different prognosis-related novel ARGs (mostly hazardous ones) compared with the patients without ABN.

The clinical effect of ABN on poor patient outcome has been noted in various cancers including MM [13,14,15,16,17]. To develop more effective cancer treatments, it is extremely important to determine the stage of cancer as a pathological staging based on the tumor-node-metastasis (TNM) classification system [18]. However, this system does not show the biological background and molecular basis of cancers. Therefore, it provides insufficient information about the genetic basis of malignancy and the prediction of prognosis of the disease. Recently, it has become a tradition to trace individual cancer-related genes to enable the targeting of molecular mechanisms and the detection of strong biomarkers at the gene level. In this context, genes related to autophagy have been screened using high-throughput expression data and valuable statistical tools in recent years. In this way, identified candidate ARGs that can affect the prognosis of different cancers, including cancers such as MM, were targeted [18,19,20,21,22,23]. Zhu et al. [24] demonstrated the prognostic value of 16 ARGs in 559 patients with MM and developed a model based on the risk score. However, the dataset used in the study conducted by Zhu et al. [24] included all patients regardless of their CA. The role of ABN in a survival analysis of MM patients was investigated in our study. Prognostic ARGs (prognostic ARG signature) were attempted to be determined for patient groups with and without chromosomal anomalies. As a result of the analyses performed, it was clearly shown in our study that ABN was the most serious factor that causes death (among other factors such as gender, age, treatment protocol, and race). Second, it was clear that patients with ABN (41 different ARGs) had different prognosis-related ARGs (mostly dangerous ones) than patients without ABN (13 different ARGs). These hazardous and survival-triggering ARGs (corresponding to MM patients with and without ABN, respectively), which differ according to the genetic background of the patients, can be reliable and promising targets to eradicate MM cancer and increase the survival of patients.

These results provide very important implications for cancer treatment outcomes and pharmacological research and applications. The results of the studies in the literature showed that the presence of ABN may lead to therapeutic vulnerability in cancers [25, 26]. According to the results of these studies, it can be concluded that differently designed cancer treatments can change the fate of cancer prognosis. Therefore, when starting a treatment strategy, investigating the presence or absence of ABN in the primary stage can increase the success of the treatment. Similarly, in addition to classical cancer staging procedures, the European Myeloma Network recommends subgrouping patients with MM based on their cytogenetic history and ABN prior to optimization of anticancer drug combinations [27]. It is promising to subgroup MM patients using a combination of the International Staging System (ISS) and ABN to have higher survival rates, according to the results of an international myeloma working group [28]. Therefore, in our study, 548 MM patients from the MAQC-II project, whose gene intensity data with GEO GSE24080 accession number are available, were divided into 2 groups according to their genetic history (MM patients with and without ABN). This strategy will differ significantly in 2 different situations. On the one hand, if there is a ABN, most prognosis-related ARGs can be downregulated at the gene level, as they are often dangerous, and can contribute positively to treatment. On the other hand, in patients without ABN, cancer treatment agents can be selected in such a way that survival-triggering ARGs can be upregulated, and those with hazardous ones can be designed to be downregulated. These applications should be tested with laboratory-based clinical studies and advanced bioinformatics analyses, further studies should be carried out on drug interactions and gene interactions with each other, and gene therapies should be designed according to these studies. However, in our study, the effects of specific types of ABN (such as mutations, cytogenetic changes, translocations, etc.) on survival times and rates of MM patients have not been searched since the data with the accession number GSE24080 do not include these detailed elements of information.

Although different research groups have tried to focus on the chromosome abnormalities of MM patients to develop better therapeutic strategies targeting cells based on their genetic background, this has not been emphasized enough in the literature [29, 30]. First, there is a limited data set based on genetic background and ABN including cancer patient gene densities. For instance, to our knowledge, MM patient gene intensity data on specific types of ABN and mutations have also not been available. Therefore, a purposeful designing of the data mining and data collection stages can predominantly ensure the reliability of the results obtained from bioinformatics analysis. Otherwise, current survival analysis and laboratory studies can lead to misleading results. Additionally, it can be very important to be aware of the diversity of cancer-related genes (e.g., ARGs) in pharmaceutical industry applications and drug development steps to avoid wasting time and investment. This can be achieved by using reliable patient gene density data for bioinformatics analysis.

In our study, the role of autophagy-dependent genes in cancer treatment, and therefore, the biological processes associated with autophagy, were shown to play a key role in cancer treatment, at least in MM cancer. The literature findings also support our studies. Ongoing lab-based research has shown that gene-level targeting with anticancer drugs in MM is a promising strategy for suppressing autophagy and related pathways as well as eradicating MM cancer [31, 32].

In our study, due to the lack of data of patients with other ABN, our results were confirmed only by the data of 1576 MM patients with 1q21 amplification. Despite the lack of data, the biological significance of our verification was high. In the literature, 1q21 amplification was associated with poor prognosis and shorter survival of MM patients [33]. In parallel with these results, it was shown in our study that 29 of 41 ARGs found to affect the prognosis of patients with ABN were associated with prognosis. It has also been ascertained in the literature that the combination of 1q21 amplification with other ABN would lead to an even shorter survival time [33]. A greater number of ARGs (more than 29) could have been confirmed in our study if data pertaining to other chromosomal abnormalities had been available.

In parallel with the results of functional GO enrichment analysis, in patients without ABN, general “biological processes” such as “protein localization” and “peptide and amide transport” came to the fore. However, in cases of ABN, enriched ARGs were mainly related to specific pathways such as programmed cell death, positive regulation of stress conditions (such as starvation, reactive oxygen species (ROS), organonitrogen compounds), negative regulation of transferase activity, phosphate metabolic process, and cellular protein metabolic process. In other words, GOrilla highlights the enrichment in ARGs related to cell death and stress response pathways in patients with ABN. Accordingly, according to the results of GOrilla clustering, targeting specific ARGs related to programmed cell death by autophagy by triggering stress conditions may be an effective way to combat MM.

Despite recent therapeutic advances, MM cancer is not yet effectively treatable. For example, the IL-3 cytokine is required for B cells to survive, and in our previous in vitro and in vivo studies, IL-3 withdrawal was shown to induce autophagic cell death and subsequent apoptosis in pro-B cells. Following IL-3 withdrawal, cancer cells could be removed after phagocytosis by resident macrophages [34]. There are other studies targeting autophagic cell death in MM cells. For example, Lamy et al. [35] demonstrated that caspase-10 is essential for the survival of all MM cell lines and that the vital balance between survival and cell death can be disturbed and driven in favor of autophagic cell death. Another study concluded that iron deprivation and hence higher cellular and mitochondrial ROS levels could lead to autophagic cell death in MM cells [36]. These results are consistent with our current findings that it may be possible to eradicate MM as a clonal B cell malignancy by inducing excessive starvation or other stress conditions and thus manipulating specific ARGs and thereby inducing autophagic cell death. Similarly, in another study, another type of cancer cells, human breast cancer cells (MCF-7), were induced to die by autophagy through steroid hormone depletion and tamoxifen therapy. These autophagic dying cells were shown to be phagocytosed by human macrophages, and clearance of these cells was achieved by inflammasome activation [37]. As a result, we believe that further research into cancer treatment can focus on cancer treatment from this perspective and increase the chances of success in treatment.

To sum up, ARGs can be involved in clinical practice and treatment strategies in MM patients with ABN. Based on the results we obtained with gene ontology analysis (GOrilla analysis), it may be possible to use ARGs detected in MM patients with ABN as target genes in anticancer treatments. For instance, autophagy is involved in cancer treatment according to the stage of the cancer. Therefore, autophagy can be either triggered or blocked to combat MM cancer cells with ABN according to their stages (early or late stage). Additionally, autophagic cell death can even be triggered by targeting related ARGs in MM patients with ABN.

Our study has some limitations. First, there is a lack of data including gene intensity values of patients with ABN as well as genes linked to autophagy. The results were validated with this dataset, since only data from 1q21 amplified MM patients were available. Second, the prognostic value and clinical significance of these ARGs must be tested using further laboratory-based research. Third, the interaction between the genes identified for autophagy and each ABN should be investigated. In addition to our gene enrichment results, the question of why some genes affect survival in the presence of ABN should be answered by using clinical samples with laboratory-based research.

Consequently, in this study, the prognostic model was constructed in such a way that the status of ARG genes changed because of the presence or absence of ABN. Classification of MM patients according to their ABN can provide us with a more personalized and efficient cancer treatment.