ABSTRACT
Proteasome inhibitors are among the most potent classes of drugs in multiple myeloma treatment. One of the main challenges in myeloma therapy is acquired resistance to drugs. Several theories have been proposed to describe the mechanisms responsible for resistance to the most commonly used proteasome inhibitors bortezomib and carfilzomib. This study aimed to describe functional differences between sensitive myeloma cells (MM1S WT) and their daughter cell lines resistant to either bortezomib (MM1S/R BTZ) or carfilzomib (MM1S/R CFZ), as well as between both resistant cell lines. Bortezomib- and carfilzomib-resistant cell lines were successfully generated by continuous exposure to the drugs. When exposed to different drugs than during the resistance generation period, MM1S/R BTZ cells showed cross-resistance to carfilzomib, whereas MM1S/R CFZ cells were similarly sensitive to bortezomib as MM1S WT cells. Following proteomic profiling, unsupervised principal component analysis revealed that the MM1S/R BTZ and MM1S/R CFZ cell lines differed significantly from the MM1S WT cell line and from each other. Canonical pathway analysis showed similar pathways enriched in both comparisons - MM1S WT vs. MM1S/R CFZ and MM1S WT vs. MM1S/R BTZ. However, important differences were present in the statistical significance of particular pathways. Key alterations included the ubiquitin-proteasome system, metabolic pathways responsible for redox homeostasis and the unfolded protein response. In functional studies, both drugs continued to reduce chymotrypsin-like proteasome activity in resistant cells. However, the baseline activity of all three catalytic domains of the proteasome was higher in the resistant cells. Differences in generation of reactive oxygen species were identified in MM1S/R BTZ (decreased) and MM1S/CFZ cells (increased) in comparison to MM1S WT cells. Both baseline and drug-induced activity of the unfolded protein response were higher in resistant cells than in MM1S WT cells and included all three arms of this pathway: IRE1α/XBP1s, ATF6 and EIF2α/ATF4 (downstream effectors of PERK). In conclusion, contrary to some previous reports, resistant MM1S cells show upregulation of unfolded protein response activity, reflecting the heterogeneity of multiple myeloma and prompting further studies on the role of this pathway in resistance to proteasome inhibitors.
ABSTRACT
Influenza is a major global public health threat as a result of its highly pathogenic variants, large zoonotic reservoir, and pandemic potential. Metagenomic viral sequencing offers the potential for a diagnostic test for influenza virus which also provides insights on transmission, evolution, and drug resistance and simultaneously detects other viruses. We therefore set out to apply the Oxford Nanopore Technologies sequencing method to metagenomic sequencing of respiratory samples. We generated influenza virus reads down to a limit of detection of 102 to 103 genome copies/ml in pooled samples, observing a strong relationship between the viral titer and the proportion of influenza virus reads (P=4.7×10-5). Applying our methods to clinical throat swabs, we generated influenza virus reads for 27/27 samples with mid-to-high viral titers (cycle threshold [CT] values, <30) and 6/13 samples with low viral titers (CT values, 30 to 40). No false-positive reads were generated from 10 influenza virus-negative samples. Thus, Nanopore sequencing operated with 83% sensitivity (95% confidence interval [CI], 67 to 93%) and 100% specificity (95% CI, 69 to 100%) compared to the current diagnostic standard. Coverage of full-length virus was dependent on sample composition, being negatively influenced by increased host and bacterial reads. However, at high influenza virus titers, we were able to reconstruct >99% complete sequences for all eight gene segments. We also detected a human coronavirus coinfection in one clinical sample. While further optimization is required to improve sensitivity, this approach shows promise for the Nanopore platform to be used in the diagnosis and genetic analysis of influenza virus and other respiratory viruses.