Enrichment of circulating myeloma cells by immunomagnetic beads combined with flow cytometry for monitoring minimal residual disease and relapse in patients with multiple myeloma

Circulating tumor plasma cells and peripheral blood measurable residual disease assessment in multiple myeloma patients not planned for upfront transplant

Circulating tumor plasma cells (CTPCs) provide a noninvasive alternative for measuring tumor burden in newly diagnosed multiple myeloma (NDMM). Moreover, measurable residual disease (MRD) assessment in peripheral blood (PBMRD) can provide an ideal alternative to bone marrow MRD, which is limited by its painful nature and technical challenges. However, the clinical significance of PBMRD in NDMM still remains uncertain. Additionally, data on CTPC in NDMM patients not treated with transplant are scarce. We prospectively studied CTPC and PBMRD in 141 NDMM patients using highly sensitive multicolor flow cytometry (HS-MFC). PBMRD was monitored at the end of three cycles (PBMRD1) and six cycles (PBMRD2) of chemotherapy in patients with detectable baseline CTPC. Patients received bortezomib-based triplet therapy and were not planned for an upfront transplant. Among baseline risk factors, CTPC ≥ 0.01% was independently associated with poor progression-free survival (PFS) (hazard ratio [HR] = 2.77; p = 0.0047) and overall survival (OS) (HR = 2.9; p = 0.023) on multivariate analysis. In patients with detectable baseline CTPC, undetectable PBMRD at both subsequent time points was associated with longer PFS (HR = 0.46; p = 0.0037), whereas detectable PBMRD at any time point was associated with short OS (HR = 3.25; p = 0.004). Undetectable combined PBMRD (PBMRD1 and PBMRD2) outperformed the serum-immunofixation-based response. On multivariate analysis, detectable PBMRD at any time point was independently associated with poor PFS (HR = 2.0; p = 0.025) and OS (HR = 3.97; p = 0.013). Thus, our findings showed that CTPC and PBMRD assessment using HS-MFC provides a robust, noninvasive biomarker for NDMM patients not planned for an upfront transplant. Sequential PBMRD monitoring has great potential to improve the impact of the existing risk stratification and response assessment models.

Liquid biopsy by analysis of circulating myeloma cells and cell-free nucleic acids: a novel noninvasive approach of disease evaluation in multiple myeloma

Multiple myeloma (MM) is an incurable hematological cancer with high spatial- and temporal-heterogeneity. Invasive single-point bone marrow sampling cannot capture the tumor heterogeneity and is difficult to repeat for serial assessments. Liquid biopsy is a technique for identifying and analyzing circulating MM cells and cell products produced by tumors and released into the circulation, allowing for the minimally invasive and comprehensive detection of disease burden and molecular alterations in MM and monitoring treatment response and disease progression. Furthermore, liquid biopsy can provide complementary information to conventional detection approaches and improve their prognostic values. This article reviewed the technologies and applications of liquid biopsy in MM.

Monitoring multiple myeloma in the peripheral blood based on cell-free DNA and circulating plasma cells

With the advent of novel, highly effective therapies for multiple myeloma (MM), classical serologic monitoring appears insufficient for response assessment and prediction of relapse. Moreover, serologic studies in MM are hampered by interference of therapeutic antibodies. The detection of malignant plasma cell clones by next generation sequencing (NGS) or multiparameter flow cytometry (MFC) circumvents these difficulties and can be performed in the peripheral blood (pB) by targeting circulating cell-free DNA (cfDNA) or circulating plasma cells (CPCs), thus also avoiding an invasive sampling procedure. Here, we applied NGS of VJ light chain (LC) rearrangements in cfDNA and MFC of magnetically-enriched CD138-positive CPCs (me-MFC) to investigate disease burden in unselected MM patients. Sequencing was successful for 114/130 (87.7%) cfDNA samples and me-MFC results were analyzable for 196/205 (95.6%) samples. MM clones were detectable in 38.9% of samples taken at initial diagnosis or relapse (ID/RD), but only in 11.8% of samples taken during complete remission (CR). Circulating MM plasma cells were present in 83.3% of ID/RD samples and 9.9% of CR samples. Residual disease assessment by NGS or me-MFC in samples taken during very good partial remission or CR was 80% concordant. Notably, 4/4 (NGS) and 5/8 (me-MFC) positive CR samples were from patients with oligo- or non-secretory myeloma. The time to progression was shorter if there was evidence of residual myeloma in the pB. Together, our findings indicate that our two novel analytical approaches accurately indicate the course of MM and may be particularly valuable for monitoring patients with serologically non-trackable disease.

Deep Learning-Based CT Imaging in Diagnosing Myeloma and Its Prognosis Evaluation

Imaging examination plays an important role in the early diagnosis of myeloma. The study focused on the segmentation effects of deep learning-based models on CT images for myeloma, and the influence of different chemotherapy treatments on the prognosis of patients. Specifically, 186 patients with suspected myeloma were the research subjects. The U-Net model was adjusted to segment the CT images, and then, the Faster region convolutional neural network (RCNN) model was used to label the lesions. Patients were divided into bortezomib group (group 1, n = 128) and non-bortezomib group (group 2, n = 58). The biochemical indexes, blood routine indexes, and skeletal muscle of the two groups were compared before and after chemotherapy. The results showed that the improved U-Net model demonstrated good segmentation results, the Faster RCNN model can realize the labeling of the lesion area in the CT image, and the classification accuracy rate was as high as 99%. Compared with group 1, group 2 showed enlarged psoas major and erector spinae muscle after treatment and decreased bone marrow plasma cells content, blood M protein, urine 24 h light chain, pBNP, ß-2 microglobulin (β2MG), ALP, and white blood cell (WBC) levels (P < 0.05). In conclusion, deep learning is suggested in the segmentation and classification of CT images for myeloma, which can lift the detection accuracy. Two different chemotherapy regimens both improve the prognosis of patients, but the effects of non-bortezomib chemotherapy are better.

Minimal Residual Disease in Multiple Myeloma: Potential for Blood-Based Methods to Monitor Disease

In recent years, the life expectancy of Multiple Myeloma (MM) patients has substantially improved, but this cancer remains incurable with increasing incidence in the developed world. Most MM patients will eventually relapse due to residual drug-resistant cancerous cells that survive treatment, commonly referred to as minimal residual disease (MRD). Methods to improve MRD detection in MM patients are generating considerable interest as a means of monitoring patients' response to treatment. In clinical laboratories, these methods currently require bone marrow aspirates which are invasive and frequently miss detection of localised disease due to the spatial heterogeneity of disease infiltration. By simplifying serial sampling and allowing for the detection of extramedullary disease, a blood-based method could significantly impact treatment duration and intensity and minimise chemotherapy-induced toxicity. This review will describe the current blood-based techniques available to detect MRD in MM and compare their potential to evaluate patient prognosis and drive therapeutic decisions.

The Role of Proteoglycans in Cancer Metastasis and Circulating Tumor Cell Analysis

Circulating tumor cells (CTCs) are accessible by liquid biopsies via an easy blood draw. They represent not only the primary tumor site, but also potential metastatic lesions, and could thus be an attractive supplement for cancer diagnostics. However, the analysis of rare CTCs in billions of normal blood cells is still technically challenging and novel specific CTC markers are needed. The formation of metastasis is a complex process supported by numerous molecular alterations, and thus novel CTC markers might be found by focusing on this process. One example of this is specific changes in the cancer cell glycocalyx, which is a network on the cell surface composed of carbohydrate structures. Proteoglycans are important glycocalyx components and consist of a protein core and covalently attached long glycosaminoglycan chains. A few CTC assays have already utilized proteoglycans for both enrichment and analysis of CTCs. Nonetheless, the biological function of proteoglycans on clinical CTCs has not been studied in detail so far. Therefore, the present review describes proteoglycan functions during the metastatic cascade to highlight their importance to CTCs. We also outline current approaches for CTC assays based on targeting proteoglycans by their protein cores or their glycosaminoglycan chains. Lastly, we briefly discuss important technical aspects, which should be considered for studying proteoglycans.