Analytical Challenges in Development of Chemoresistance Predictors for Precision Oncology

Chemoresistance, i.e., tumor insensitivity to chemotherapy, shortens life expectancy of cancer patients. Despite the availability of new treatment options, initial systemic regimens for solid tumors are dominated by a set of standard chemotherapy drugs, and alternative therapies are used only when a patient has demonstrated chemoresistance clinically. Chemoresistance predictors use laboratory parameters measured on tissue samples to predict the patient's response to chemotherapy and help to avoid application of chemotherapy to chemoresistant patients. Despite thousands of publications on putative chemoresistance predictors, there are only about a dozen predictors that are sufficiently accurate for precision oncology. One of the major reasons for inaccuracy of predictors is inaccuracy of analytical methods utilized to measure their laboratory parameters: an inaccurate method leads to an inaccurate predictor. The goal of this study was to identify analytical challenges in chemoresistance-predictor development and suggest ways to overcome them. Here we describe principles of chemoresistance predictor development via correlating a clinical parameter, which manifests disease state, with a laboratory parameter. We further classify predictors based on the nature of laboratory parameters and analyze advantages and limitations of different predictors using the reliability of analytical methods utilized for measuring laboratory parameters as a criterion. Our eventual focus is on predictors with known mechanisms of reactions involved in drug resistance (drug extrusion, drug degradation, and DNA damage repair) and using rate constants of these reactions to establish accurate and robust laboratory parameters. Many aspects and conclusions of our analysis are applicable to all types of disease biomarkers built upon the correlation of clinical and laboratory parameters.

Spheroid-Based Approach to Assess the Tissue Relevance of Analysis of Dispersed-Settled Tissue Cells by Cytometry of the Reaction Rate Constant

Cytometry of Reaction Rate Constant (CRRC) uses time-lapse fluorescence microscopy to measure a rate constant of a catalytic reaction in individual cells and, thus, facilitate accurate size determination for cell subpopulations with distinct efficiencies of this reaction. Reliable CRRC requires uniform exposure of cells to the reaction substrate followed by their uniform imaging, which in turn, requires that a tissue sample be disintegrated into a suspension of dispersed cells, and these cells settle on the support surface before being analyzed by CRRC. We call such cells "dispersed-settled" to distinguish them from cells cultured as a monolayer. Studies of the dispersed-settled cells can be tissue-relevant only if the cells maintain their 3D tissue state during the multi-hour CRRC procedure. Here, we propose an approach for assessing tissue relevance of the CRRC-based analysis of the dispersed-settled cells. Our approach utilizes cultured multicellular spheroids as a 3D cell model and cultured cell monolayers as a 2D cell model. The CRRC results of the dispersed-settled cells derived from spheroids are compared to those of spheroids and monolayers in order to find if the dispersed-settled cells are representative of the spheroids. To demonstrate its practical use, we applied this approach to a cellular reaction of multidrug resistance (MDR) transport, which was followed by extrusion of a fluorescent substrate from the cells. The approach proved to be reliable and revealed long-term maintenance of MDR transport in the dispersed-settled cells obtained from cultured ovarian cancer spheroids. Accordingly, CRRC can be used to determine accurately the size of a cell subpopulation with an elevated level of MDR transport in tumor samples, which makes CRRC a suitable method for the development of MDR-based predictors of chemoresistance. The proposed spheroid-based approach for validation of CRRC is applicable to other types of cellular reactions and, thus, will be an indispensable tool for transforming CRRC from an experimental technique into a practical analytical tool.

Transcriptome Analysis of Mesenchymal Stem Cells from Multiple Myeloma Patients Reveals Downregulation of Genes Involved in Cell Cycle Progression, Immune Response, and Bone Metabolism

A growing body of evidence suggests a key role of tumor microenvironment, especially for bone marrow mesenchymal stem cells (MSC), in the maintenance and progression of multiple myeloma (MM), through direct and indirect interactions with tumor plasma cells. Thus, this study aimed to investigate the gene expression and functional alterations of MSC from MM patients (MM-MSC) in comparison with their normal counterparts from normal donors (ND-MSC). Gene expression analysis (Affymetrix) was performed in MM-MSC and ND-MSC after in vitro expansion. To validate these findings, some genes were selected to be evaluated by quantitative real time PCR (RT-qPCR), and also functional in vitro analyses were performed. We demonstrated that MM-MSC have a distinct gene expression profile than ND-MSC, with 485 differentially expressed genes (DEG) - 280 upregulated and 205 downregulated. Bioinformatics analyses revealed that the main enriched functions among downregulated DEG were related to cell cycle progression, immune response activation and bone metabolism. Four genes were validated by qPCR - ZNF521 and SEMA3A, which are involved in bone metabolism, and HLA-DRA and CHIRL1, which are implicated in the activation of immune response. Taken together, our results suggest that MM-MSC have constitutive abnormalities that remain present even in the absence of tumors cells. The alterations found in cell cycle progression, immune system activation, and osteoblastogenesis suggest, respectively, that MM-MSC are permanently dependent of tumor cells, might contribute to immune evasion and play an essential role in bone lesions frequently found in MM patients.

Proteasome and heat shock protein 70 (HSP70) inhibitors as therapeutic alternative in multiple myeloma

HSP70 connects multiple signaling pathways that work synergistically to protect tumor cells from death by proteotoxic stress and represents a possible target to establish a new approach for multiple myeloma treatment. Therefore, bioluminescent cell lines RPMI8226-LUC-PURO and U266-LUC-PURO were treated with HSP70 (VER155008) and/or proteasome (bortezomib) inhibitors and immunodeficient mice were used for subcutaneous xenograft models to evaluate tumor growth reduction and tumor growth inhibition after treatment. Bioluminescence imaging was used to follow tumor response. Treatment with bortezomib showed ∼60% of late apoptosis in RPMI8226-LUC-PURO (without additional benefit of VER155008 in this cell line). However, U266-LUC-PURO showed ∼60% of cell death after treatment with VER155008 (alone or with bortezomib). RPMI8226-LUC-PURO xenograft presented tumor reduction by bioluminescence imaging after treatment with bortezomib, VER155008 or drug combination compared to controls. Treatment with bortezomib, alone or combined with VER155008, showed inhibition of tumor growth assessed by bioluminescence imaging after one week in both RPMI8226-LUC-PURO and U266-LUC-PURO cell lines when compared to controls. In conclusion, our study shows that the combination of proteasome and HSP70 inhibitors induced cell death in tumor cells in vitro (late apoptosis induction) and in vivo (inhibition of tumor growth) with special benefit in U266-LUC-PURO, bearing 17p deletion.

Activation of the Janus kinase/signal transducer and activator of transcription pathway in multiple myeloma is not related to point mutations in kinase and pseudokinase domains of JAK1

Abstract Considering the recent impact of tyrosine kinase inhibitors in the treatment of myeloproliferative disorders carrying a recurrent JAK2 mutation not identified in multiple myeloma (MM), this study aimed to search for mutations in kinase and pseudokinase domains of the JAK1 gene in an attempt to define any critical and recurring change that can be used as a therapeutic target. We obtained CD138 + purified cells from 27 bone marrow aspirates of untreated MM, four normal controls and four MM cell lines. After amplification of kinase and pseudokinase domains of JAK1 in cDNA samples, the fragments were automatically sequenced. Seventy-eight percent of MM cases showed at least one polymorphism, all being synonymous single nucleotide polymorphisms (SNPs), with allele frequencies consistent with previous studies in normal European, African American and Asian populations. The four cell lines also showed only synonymous SNPs. Mutations in the kinase and pseudokinase domains of the JAK1 gene do not seem to be important for activation of the Janus kinase/signal transducer and activator of transcription (JAK/STAT) pathway because we were not able to find any recurrent mutation in a case series of 27 patients and four MM cell lines.