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Abstract Computational pharmacogenomics can potentially identify new indications for already approved drugs and pinpoint compounds with similar mechanism-of-action. Here, we used an integrated drug repositioning approach based on transcriptomics data and structure-based virtual screening to identify compounds with gene signatures similar to three known proteasome inhibitors (PIs; bortezomib, MG-132, and MLN-2238). In vitro validation of candidate compounds was then performed to assess proteasomal proteolytic activity, accumulation of ubiquitinated proteins, cell viability, and drug-induced expression in A375 melanoma and MCF7 breast cancer cells. Using this approach, we identified six compounds with PI properties ((-)-kinetin-riboside, manumycin-A, puromycin dihydrochloride, resistomycin, tegaserod maleate, and thapsigargin). Although the docking scores pinpointed their ability to bind to the β5 subunit, our in vitro study revealed that these compounds inhibited the β1, β2, and β5 catalytic sites to some extent. As shown with bortezomib, only manumycin-A, puromycin dihydrochloride, and tegaserod maleate resulted in excessive accumulation of ubiquitinated proteins and elevated HMOX1 expression. Taken together, our integrated drug repositioning approach and subsequent in vitro validation studies identified six compounds demonstrating properties similar to proteasome inhibitors.

Abstract Repurposing of FDA-approved drugs is a quick and cost-effective alternative to de novo drug development. Here, we identify genes involved in bortezomib sensitivity, predict cancer types that may benefit from treatment with bortezomib, and evaluate the mechanism-of-action of bortezomib in breast cancer (BT-474 and ZR-75–30), melanoma (A-375), and glioblastoma (A-172) cells in vitro. Cancer cell lines derived from cancers of the blood, kidney, nervous system, and skin were found to be significantly more sensitive to bortezomib than other organ systems. The in vitro studies confirmed that although bortezomib effectively inhibited the β5 catalytic site in all four cell lines, cell cycle arrest was only induced in G2/M phase and apoptosis in A-375 and A-172 after 24h. The genomic and transcriptomic analyses identified 33 genes (e.g. ALDH18A1, ATAD2) associated with bortezomib resistance. Taken together, we identified biomarkers predictive of bortezomib sensitivity and cancer types that might benefit from treatment with bortezomib.

Abstract Recombinant α1-microglobulin (A1M) is a proposed radioprotector during 177Lu-octreotate therapy of neuroendocrine tumors (NETs). To ensure a maintained therapeutic effect, we previously demonstrated that A1M does not affect the 177Lu-octreotate induced decrease in GOT1 tumor volume. However, the underlying biological events of these findings are still unknown. The aim of this work was to examine the regulation of apoptosis-related genes in GOT1 tumors short-time after i.v. administration of 177Lu-octreotate with and without A1M or A1M alone. Human GOT1 tumor-bearing mice received 30 MBq 177Lu-octreotate or 5 mg/kg A1M or co-treatment with both. Animals were sacrificed after 1 or 7 days. Gene expression analysis of apoptosis-related genes in GOT1 tissue was performed with RT-PCR. In general, similar expression patterns of pro- and anti-apoptotic genes were found after 177Lu-octreotate exposure with or without co-administration of A1M. The highest regulated genes in both irradiated groups compared to untreated controls were FAS and TNFSFRS10B. Administration of A1M alone only resulted in significantly regulated genes after 7 days. Co-administration of A1M did not negatively affect the transcriptional apoptotic response of 177Lu-octreotate in GOT1 tumors.

Abstract There is limited knowledge of the biology of breast cancer (BC) brain metastasis (BM). We primarily aimed to determine the mutations in BCBM and to compare the mutational pattern with the matched primary breast cancer (BC). Secondary aims were to determine mutations in each subgroup (Luminal A-/B-like, HER2+ and TNBC) of BCBM, and to determine survival according to specific mutations. We investigated 57 BCBMs, including 46 cases with matched primary tumors (PT) by targeted Next Generation Sequencing (NGS) using the Cancer Hotspot Panel v2 (ThermoFisher Scientific) covering 207 targeted regions in 50 cancer related genes. Subtype according to immunohistochemistry was re-evaluated. NGS results fulfilling sequencing quality criteria were obtained from 52 BM and 41 PT, out of which 37 were matched pairs. Pathogenic mutations were detected in 66% of PTs (27/41), and 62% of BMs (32/52). TP53 mutations were most frequent; 49% (20/41) of PTs and 48% (25/52) in BMs, followed by PIK3CA mutations; 22% (9/42) in PTs and 25% (13/52) in BMs. Mutations in CDH1, EGFR, HRAS, RB1 CDKN2A and PTEN were detected in single pairs or single samples. Mutational pattern was discordant in 24% of matched pairs. We show a discordance of PIK3CA and TP53 mutations of roughly 25% indicating the need to develop methods to assess mutational status in brain metastasis where analysis of cell-free DNA from cerebrospinal fluid (CSF) has shown promising results.

Abstract Oral leukoplakia (OL), a potentially malignant disorder, recurs in 40% of cases after surgical removal. Recurrence is a risk factor for malignant transformation. We aimed to examine the prognostic significance of four biomarkers related to cell proliferation: p53, p63, podoplanin (PDPN) and Ki-67 in predicting recurrence. Formalin-fixed-paraffin-embedded specimens from excised OL (n = 73, 33 recurrent; 40 non-recurrent) were collected in a prospective study. Immunohistochemistry was used to visualise expression of p53, p63, PDPN and Ki-67. Image analysis software was used for quantification of p53-, p63- and Ki-67-expressing cells, while PDPN was analysed visually. The expression of all four proteins were higher in recurrent compared with non-recurrent OL, only expression of p53 was statistically significant. In uni- and multivariable Cox regression analyses of individual markers, expression of p63 was significantly associated with higher recurrence risk (p = 0.047). OL with a combined high expression of both p53 and p63 had a significantly higher risk to recur [Log Rank, p = 0.036; multivariate Cox, HR: 2.48 (1.13–5.44; p = 0.024)]. Combination of p53 and p63 expression may be used as a prognostic biomarker for recurrence of OL.