Chronic hypoxia favours adoption to a castration-resistant cell state in prostate cancer

doi:10.21203/rs.3.rs-1758175/v1

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Chronic hypoxia favours adoption to a castration-resistant cell state in prostate cancer

https://doi.org/10.21203/rs.3.rs-1758175/v1

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Predicting and treating recurrence in intermediate-risk prostate cancer patients remains a challenge despite having identified genomic instability (1) and hypoxia (2,3) as risk factors. This underlies challenges in assigning the functional impact of these risk factors to mechanisms promoting prostate cancer progression. Here we show chronic hypoxia (CH), as observed in prostate tumours (4), leads to the adoption of an androgen-independent state in prostate cancer cells. Specifically, CH results in prostate cancer cells adopting transcriptional and metabolic alterations typical of castration-resistant prostate cancer cells. These changes include increased expression of transmembrane transporters for the methionine cycle and related pathways leading to increased abundance of metabolites and expression of enzymes related to glycolysis. Targeting the Glucose Transporter 1 (GLUT1) identified a dependency on glycolysis in androgen-independent cells. Overall, we identified a therapeutically targetable weakness in chronic hypoxia and androgen-independent prostate cancer. These findings may offer additional strategies for treatment development against hypoxic prostate cancer.

Prostate cancer

hypoxia

castrate resistance

metabolism

glycolysis

Prostate cancer is the second most common cancer diagnosed in men, affecting 1 in 5 men on average with a 5-year survival of 98% (5,6). Although the 5-year survival rate is high, progression still occurs in approximately 20-34% of prostate cancer patients (7,8). Biochemical recurrence (BCR) and the subsequent progression to castration-resistant prostate cancer (CRPC) are the main drivers of prostate cancer-specific mortality (9,10). Gleason score, tumour grade, and prostate specific antigen (PSA) levels in the sera are some of the primary means of progression risk stratification for prostate cancer patients (11,12). Using these grading systems, patients fall into three main categories: low, intermediate and high risk (12,13). The risk of prostate cancer-specific mortality in high-risk patients is approximately 40% and 4% in low-risk when patient follow-up is extended to 10 years or more (14). The intermediate-risk patients present the greatest difficulty in predicting cancer progression (6,15), with a risk of prostate cancer-specific mortality ranging between 6.5% and 11% (14). Intermediate-risk prostate cancer patients can be subdivided into low-intermediate (Gleason score 3+4) and high-intermediate (Gleason score 4+3) (5,6). While this separation serves to guide treatment selection within intermediate-risk patients, disease progression in the form of biochemical and locoregional recurrence can still occur (15). These findings reflect the intra-tumour heterogeneity of prostate cancer and the difficulty in predicting disease progression. Therefore, there is a need to identify those patients more likely to develop recurrence and intervene earlier to prevent biochemical recurrence and disease progression.

Beyond Gleason scores and PSA levels, hypoxia (2,16,17), genomic instability (1) and the MRI imaging feature anisotropy are recent predictors of prostate cancer progression (18). While hypoxia is associated with PTEN loss (19) and genomic instability in prostate cancer (1,17,20), it is also an environmental stressor that can induce non-genetic changes. Hypoxia prevents the degradation of the Hypoxia Inducible Factor 1ɑ (HIF1ɑ) protein, which activates a HIF1ɑ-dependent transcriptional response (21,22), driving angiogenesis, proliferation, apoptosis and a number of metabolic pathways (23,24). These pathways promote survival in a hypoxic environment and are associated with cancer progression (23,25). For example, glucose-6-phosphate isomerase (GPI) expression is increased in prostate cancer cells exposed to acute cycles of hypoxia (1% oxygen) in an androgen-depleted environment (26). GPI encodes an enzyme important in glycolysis allowing cells to decrease their dependence on oxygen for energy (26,27). Hypoxia can also alter the epigenetic landscape of prostate cancer cells by promoting the expression of histone demethylases (28,29). For example the expression of lysine demethylase 3A (KDM3A), a coactivator of AR, is increased under hypoxia, resulting in the decreased methylation of H3K9 and increased expressed of CTH and PFKP (30–32). These genes are involved in metabolic pathways, specifically CTH in cysteine and methionine metabolism and PFKP in glycolysis (30,33). Subsequently, hypoxia can alter the epigenetic landscape and give rise to chromatin variants (34) in prostate cancer cells by favouring the expression of KDM3A (28,29)(31,32)(28,29). Thus, hypoxia represents a potent environmental pressure to promote progression through chromatin variants that impact gene expression and altered metabolic pathways.

Therapeutic interventions designed against hypoxia have become increasingly attractive in solid tumours including prostate tumours (35,36). Many hypoxia-based therapies focus on HIF1ɑ (35,36). However, HIF1ɑ is primarily involved in acute hypoxia responses, up to 24 hours, with a different HIF isoform mediating a longer term response (24,37). The HIF isoforms have different target genes, leading to changes in the transcriptional program (37). This indicates longer exposure to hypoxia causes further changes in gene expression. Therefore, targeting HIF1ɑ may not necessarily reverse changes mediated by hypoxia. Here we show how chronic, as opposed to acute hypoxia, leads to androgen insensitivity in prostate cancer cells by mimicking transcriptional and metabolic changes seen in CRPC cells. These changes reflect vulnerabilities for targeted intervention using chemical inhibitors of glycolysis to prevent the development of aggressive prostate cancer.

Cell lines - media, 1% oxygen chamber, Incucyte, compound/drug testing

Cell lines: LNCaP clone FGC (ATCCⓇ, CRL-1740^TM), VCaP (ATCCⓇ, CRL-2876™) RWPE-1 (ATCCⓇ, CRL-11609^TM), PWR-1E (ATCCⓇ, CRL-11611^TM) and the V16A cell line (gifted from Hansen He, originally from Amina Zoubeidi) were used in the subsequent experiments.

Cell culture maintenance conditions: LNCaP cells were cultured in RPMI (ThermoFisher, #11875093) with 10% fetal bovine serum (FBS) (ThermoFisher Scientific, #12483020) and Penicillin/Streptomycin (10,000U/ml, ThermoFisher Scientific, #15140122) at 21% oxygen or Penicillin/Streptomycin/Amphotericin B (100x, ThermoFisher Scientific, #15240062) at 1% oxygen. VCaP cells were maintained in DMEM (ThermoFisher Scientific 11995065) with 10% FBS (ThermoFisher) and Penicillin/Streptomycin (ThermoFisher Scientific) at 21% oxygen or Penicillin/Streptomycin/Amphotericin B (ThermoFisher Scientific) at 1% oxygen. The V16A cell line (derived from LNCaPs, and subsequently referred to as LNCaP-V16A) was cultured in RPMI-phenol red media (ThermoFisher Scientific, #11835030) with 10% charcoal depleted FBS (Wisent Cat: 080750, Lot: 912070), Penicillin/Streptomycin and were maintained at 21% oxygen. The RWPE-1 and PWR-1E cell lines were cultured in keratinocyte serum-free media (KSF, Thermofisher Scientific, #17005042) supplemented with recombinant epidermal growth factor (EGF) and bovine pituitary extract (BPE). Cells were counted using the Countess™ cell counter (Invitrogen, #C10281).

Generation of the CH cells: LNCaP/VCaP cells were plated at a density of 30-50% and maintained in 1% oxygen (Whitley H35 hypoxystation). During IncucyteⓇ S3 (Sartorius) experiments, cells were briefly removed from hypoxia for imaging. Cells were maintained in 1% oxygen for a minimum of 144 hours to be considered chronically hypoxic (CH).

Cell culture experimental conditions: Cells cultured in RPMI media (ThermoFisher) with 10% FBS (ThermoFisher Scientific) and Penicillin/Streptomycin (10,000U/ml, ThermoFisher Scientific) hereby referred to as Androgen + media. Cells were cultured in RPMI-phenol red media (ThermoFisher Scientific) with 10% Charcoal depleted FBS (Wisent) and Penicillin/Streptomycin (ThermoFisher Scientific) hereby referred to as Androgen - media. Enzalutamide (final concentration 10µM, Axom, #1613) was added to the Androgen - media, making Androgen - with ENZA.

Conditional medium experimental conditions: For medium testing LNCaP, LNCaP-CH and LNCaP-V16A cells were plated in 96-well plates (Millipore Sigma, CorningⓇ CLS3596-50EA). RPMI media depleted of metabolites for the methionine pathway and glycolysis was synthesised by Wisent (350-055-CL, custom order). A base media was made with the RPMI metabolite depleted media, charcoal depleted FBS and Penicillin/Streptomycin to be consistent with the RPMI - steroid base media. Each of the metabolites required was supplied at 100x concentration, except for D-Glucose which was supplied at 75x concentration (Wisent, custom order).

Chemical compound treatment: LNCaP, LNCaP-CH and LNCaP-V16A cells were plated in 96-well plates (Millipore Sigma, CorningⓇ CLS3596-50EA). The chemical compounds BAY-876 (SGC, Toronto), BAY-588 (SGC, Toronto), V-9302 (Aobious, #AOB33597) and MAT2A Inhibitor II (FIDAS-5, Calbiochem, Millipore Sigma 5041730001) were diluted in DMSO (Bioshop DMS666.100) to 10mM stock solutions. The chemical compounds were added at 2x concentration in 100µl of media to each well. An equal volume of the control DMSO (Bioshop DMS666.100) was added to the 100µl of media for MAT2A and V-9302 control. Cells were continuously monitored at 21% oxygen using the IncucyteⓇ S3 (Sartorius).

Western blotting

Cells were incubated in 1% oxygen for varying lengths of time, from 8 to 144 hours, and collected in ice-cold DPBS (ThermoFisher Scientific, #14190144) immediately prior to subcellular fractionation, performed using the NE-PER Nuclear and Cytoplasmic Extract Kit (ThermoFisher Scientific, #0078833). Protein was quantified using the Pierce™ BCA protein assay kit (ThermoFisher Scientific, #23227) and 20µg of the nuclear fraction (NF) was prepared by adding loading dye (5x concentration, 250mM Tris-HCl ph 6.8, 10% SDS, 50% Glycerol, 500mM DTT, 0.05% Bromophenol Blue) to a final concentration of 1x. Protein samples were boiled for 10 minutes at 95^oC then run on an Any kD^TMMin-iPROTEANⓇ TGX^TM precast gel (Bio-rad, 10 well, #4569034) and transferred using a Trans-Blot Turbo Midi 0.2µm PVDF (Transfer packs, Bio-Rad #1704157) system to PVDF membrane. The antibodies used were HIF1ɑ (1:500, Abcam, #ab2185) and nuclear protein control TBP (1:1000, Cell Signalling, #44059S) with an anti-Rabbit (1:2500, Li-Core, #926-32213) secondary antibody. Membranes were imaged using ODYSSEY™ CLx (Li-Cor) and images analysed using Image Studio™ (Li-Cor).

RT-qPCR

Cells were plated in 6-well plates (Cellstar, #657160) and either incubated at 21% oxygen or 1% oxygen. RNA was collected and purified using the Allprep DNA/RNA mini kit (Qiagen, #80204), as per manufacturer's instructions. RNA was quantified via NanoDrop (NanoDrop 2000, ThermoFisher Scientific, ND2000CLAPTOP). After quantification 1µg of RNA was used for cDNA synthesis, performed using the SensiFAST™ kit (Meridian Bioscience, #BIO-65054). HIF1ɑ specific gene set selected from Semeza GL., (23) and Beyer et al. (31). DNA oligonucleotide primers were synthesised by Integrated DNA Technologies Canada, Inc. (IDT, Toronto, Canada) (Supplementary Table 1). Quantitative PCR (qPCR) was performed using SensiFAST™ SYBR® No-ROX Kit (Meridiant Bioscience, #BIO-98050) on a BIORAD c1000 touch thermocycler with the CFX96 touch^TM Real-time detection system (BioRad). All results were analysed in excel as the log 2 fold change of the ΔΔCt (2^-(ΔΔCt)) (Microsoft).

RNA Sequencing and Data Processing

Sample preparation: Biological replicates of each cell line were plated in 6-well plates and cultured in RPMI - steroid + DHT or RPMI - steroids, depending on the cell type, for 72 hours. The cells were washed 2 times in DPBS and then placed on ice. The RNeasy plus mini kit (Qiagen, #74136) was used to collect RNA from cells as per manufacturer's instructions. RNA was then quantified using the Nanodrop and 1µg of RNA was delivered to the Princess Margaret Genomics Centre (PMGC, Toronto, Canada). The PMGC performed ribosomal RNA depletion using Ribo-Zero Gold rRNA Removal kit (Illumina).

Sequencing: The RNA libraries were sent for 75 bp paired-end sequencing on an Illumina NextSeq 550 at a target depth of 60M read pairs per sample. Sequence quality was assessed with FastQC (v0.11.8) (38), and FASTQ files from multiple lanes corresponding to the same samples were merged. Reads were trimmed for quality with TrimGalore! (v0.6.2) (39) using Cutadapt (v2.3) (40). Trimmed read pairs were used to quantify transcripts with Kallisto (v0.45.1) (41) against the GRCh38 transcriptome reference index (Ensembl v94) with the following command: kallisto quant -b 100 -t 8 --pseudobam -i {index} {sample_R1} {sample_R2}. One of the three V16A replicates was removed at this point, due to more than 75% of transcripts having 0 compatible reads assigned to them.

Differential gene expression analysis: To remove sequencing batch effects between samples, the SVA model (Bioconductor R package v3.36.0 (42)) was used to calculate one surrogate variable in R (v3.5.1) (43). Transcript counts were modelled with Sleuth (v0.30.0) (44), using a contrast model consisting of the cell type, sequencing batch, and surrogate variable calculated from SVA. Only transcripts where >= 60% of samples contained >= 10 reads were considered. The Wald test was performed to calculate significantly differentially expressed transcripts, and results were aggregated on a gene-level basis. Multiple p-values were adjusted using the Benjamini-Hochberg FDR method. Differentially expressed transcripts or genes were considered significant if the FDR values were < 0.05.

Gene score analysis: Gene Ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed using the clusterProfiler R package (45) using the “fdr” pAdjustMethod with a minimum gene size of 1 as the only modification to default settings.

Metabolite extraction

Sample preparation: Biological replicates of each cell line were plated in 6 well plates and cultured in respective media for 72 hours. The LNCaP and LNCaP-CH were cultured in RPMI - Steroid + DHT and the V16A were cultured in RPMI - Steroid. The cells were collected at approximately 70% confluence and counted to ensure there were between 5x10⁵ and 1x10⁶ cells (Supplementary Table 2). For conditioned media collection, 1mL of media was removed from each biological replicate. Naive media, in technical replicates, were collected in parallel with conditioned media. Cells were washed 2 times in 0.9% sodium chloride in HPLC grade H₂O (Caledon, #8801-7-40) solution and placed on ice. 1mL of 80% HPLC grade Methanol (Caledon, #6701-7-40), previously stored at -80^oC, was added to each well with plates then placed at -80^oC for 15 minutes. Once removed from -80^oC the plates were placed on dry ice and cells were scraped into 1.5mL tubes. The cell suspension was then centrifuged at 20,000g for 10 minutes at 4^oC. The supernatant was then divided into 2 separate 1.5mL tubes with approximately 450µl of extract in each and either stored at -80^oC or dried with Vacufuge® plus (Eppendorf). Samples dried via Vacufuge® plus were stored at -80^oC prior to shipping. Liquid chromatography-mass spectrometry (LC-MS) of metabolite extracts and media samples was performed by Juan Liu with supervision from Jason Locasale (Duke University, NC, USA) as published (46).

Analysis: The peak intensity of the LC-MS was used for all analysis and reading were excluded if the value read 1000 as this indicated lack of detection. The intracellular metabolites were normalised first by quantile normalisation, then log2 transformed and mean centred. For the media (extracellular) metabolites the samples were quantile normalised. The LNCaP cell line samples were used as the control condition for all subsequent analyses. The intracellular metabolites for the LNCaP-CH and LNCaP-V16As were compared to the LNCaPs using an unpaired t-test. The cut-off for significantly different was set at 1.5 fold change with a false discovery rate (FDR) of 0.05. For the media (extracellular) analysis the naive media replicates were combined to set the naive media peak intensity level. The conditioned media for all samples were compared to the naive media for unpaired t-test analysis.

CH and V16A shared transcript profile in patient samples

The 199 genes identified as shared between the LNCaP-CH and LNCaP-V16A cells were used to score the Porto transcriptional data set (47) as having a positive or negative score. This was achieved by taking the mean of the expression score of each gene of the 166 identified out of the 199 gene set. The gene was then given either a positive 1 or negative 1 in each patient sample if the log2 normalised value of the gene was either above or below the mean. The gene scores for each patient sample were added together. The gene score was considered positive if above 0 and negative if below 0. The data was then separated into the top and bottom 50th percentile before use in a box plot and statistical analysis in R (v1.4.1717). A t-test with FDR correction was performed on the case and control group scores to determine any statistical differences.

Chronic hypoxia promotes insensitivity to androgen depletion

To study the effect of chronic hypoxia in prostate cancer, the LNCaP cell line, an androgen-sensitive prostate cancer cell line, was continuously cultured in 1% oxygen. To determine whether hypoxia was detrimental to proliferation cells were monitored in 1% oxygen. With no prior exposure to hypoxia, the growth of LNCaP cells was measured for up to 144 hours in 21% (ambient) or 1% (hypoxia) oxygen. LNCaP cells showed no significant difference in growth when maintained in 21% or 1% oxygen (Figure 1A). The ability to grow in 1% oxygen was also demonstrated with VCaP cells, another androgen-sensitive prostate cancer cell line (Supplementary Figure 1A). In contrast, hypoxia was detrimental to the growth of normal prostate epithelial RWPE-1 and PWR-1E cell lines within 70 hours of incubation (Supplementary Figure 1B). In parallel, we measured HIF1ɑ protein levels in the nuclear fraction (NF) of LNCaP cells to assess the response to hypoxia. In agreement with previous reports (24), HIF1ɑ protein levels increased in LNCaP cells within the first 8 hours of incubation in 1% oxygen levels (Figure 1B). HIF1ɑ levels then decreased but remained present in cells maintained in hypoxic conditions for up to 144 hours (Figure 1B). Expression of HIF1ɑ target genes, such as Solute Carrier Family 2 Member 1 (SLC2A1) (23), Carbonic Anhydrase 9 (CA9) (48) and Histone demethylase 3A (KDM3A) (31), showed a marked increase within the first 8-24 hours under hypoxia (Figure 1C). SLC2A1 and KDM3A expression was also demonstrated to increase between 8 and 24 hours in VCaP cells (Supplementary Figure 1C). Although expression decreased over time under hypoxia, mRNA levels for these HIF1a target genes remained above normoxia baseline. Collectively, these results suggest that prostate cancer cells respond to and proliferate unimpeded in hypoxic conditions.

To study the impact of chronic hypoxia on the biological features of prostate cancer cells, we first established LNCaP cells from long-term maintenance (>144 hours) in 1% oxygen levels (Figure 1D). We labelled these models of chronic hypoxia (CH). No significant differences were noted in the growth properties of LNCaP-CH (Figure 1E) when maintained in 1% oxygen versus when reoxygenated and maintained in 21% oxygen. In accordance with the LNCaP-CH cells, the chronically hypoxic VCaP (VCaP-CH) cells showed no difference in growth when reoxygenated (Supplementary Figure 1D). As hypoxia is associated with progression in prostate cancer (2,17), we next assessed the response of our chronic hypoxia models to standard-of-care therapies. Specifically, we tested the growth response of LNCaP-CH to androgen depletion and enzalutamide treatment. Androgen depletion mimics surgical and chemical castration (26). Enzalutamide is an androgen receptor antagonist commonly used to treat prostate tumours that progress following castration (49,50). For comparison, we included the LNCaP and castration-resistant LNCaP-V16A cell lines (51,52). Androgen depletion alone (Androgen -) or in combination with enzalutamide treatment (Androgen - with ENZA) abrogated the growth of LNCaP cells compared to control conditions (Androgen +, Figure 1F). In contrast, LNCaP-CH cells were insensitive to androgen depletion (Figure 1F). Their growth was reduced only upon combining androgen depletion with enzalutamide treatment. The response of LNCaP-V16A castration-resistant cells to androgen depletion and enzalutamide treatment mimicked the response of LNCaP-CH cells. Collectively, these results argue that chronic hypoxia favours a castration-resistant-like cell state in prostate cancer cells by conferring androgen insensitivity.

Chronic hypoxia and castration resistance converge on metabolic pathway disruption

To better understand how chronic hypoxia could promote castration resistance, we first investigated and compared the expression profile of all three models i.e. LNCaP (androgen sensitive) LNCaP-CH (chronic hypoxia model) and LNCaP-V16A cells (castration resistant) by RNA-seq and identified differentially expressed transcripts, based on a q-value less than 0.05 and the 50th percentile, in both LNCaP-CH and LNCaP-V16A compared to LNCaP. In comparison to LNCaP cells, we identified 913 transcripts upregulated and 1252 transcripts down-regulated in LNCaP-CH cells (Figure 2A). We next compared LNCaP-V16A to LNCaP cells, identifying 310 transcripts upregulated and 671 transcripts downregulated in castration-resistant prostate cancer cells (Figure 2B). To assess similarities and differences amongst transcripts and related pathways in castration-resistant and chronic hypoxic cells we compared the differential expression from LNCaP-CH to that of the LNCaP-V16A cells. We found a total of 532 differentially expressed transcripts shared between LNCaP-CH and LNCaP-V16A when compared to LNCaP cells (Supplementary Figure 2A). In total, 199 transcripts were upregulated and 310 downregulated in both LNCaP-CH and LNCaP-V16A compared to LNCaP cells, leaving 23 genes with divergent expression (Figure 2C, E and Supplementary Figure 2A). While pathway analysis from the 310 downregulated transcripts identified only protein heterodimerization in the GO term analysis (Figure 2F) pathway analysis from the 199 upregulated transcripts, common to both chronic hypoxia and castration-resistant prostate cancer cells, identified enrichment of glycolysis related and metabolite transporter activity including fructose-bisphosphate activity and amino acid transports, glutamine and serine transporters (Figure 2D). Further investigation of these pathways using metabolism-specific KEGG analysis identifies hypoxia, glycolysis and the one-carbon metabolism (Supplementary Figure 2B). To determine the relevance of the transcriptional profiling in patient samples transcriptional data from the Porto Cohort, patients that did and did not develop BCR, was investigated (47). The shared 199 transcriptional profile was investigated in the Porto Cohort, containing patients with BCR termed “Cases” and without BCR termed “Control” (47). Separating the samples into Cases versus Controls showed a higher average gene score in the Cases with a q-value of 0.072 (Supplementary Figure 2C). These findings implicate the transcriptional changes identified in hypoxia are important for prostate cancer progression but require further interrogation to determine which have the greatest impact. Overall, our results argue that chronic hypoxia and castration resistance commonly show alteration in the expression of metabolism-related genes part of the one-carbon and glycolysis-related pathways.

We next directly assessed the impact of chronic hypoxia and castration resistance on metabolism by quantifying 301 metabolites in LNCaP-CH, LNCaP-V16A and LNCaP cells through LC-MS. In comparison to LNCaP cells, 95 intracellular metabolites were significantly different in LNCaP-CH cells (fold change ≥ 1.5, FDR of ≤0.05) (Supplementary Figure 3A). In agreement with the gene expression analysis, these metabolites are enriched in glycolysis-related pathways, including pentose phosphate, pyruvate metabolism and the Citrate cycle (Supplementary Figure 3B). This analysis also revealed increased levels of metabolites related to the methionine and glutathione pathways (Supplementary Figure 3B). Similarly, 88 intracellular metabolites were significantly different in LNCaP-V16A compared to LNCaP cells (fold change ≥ 1.5, FDR ≤0.05) (Supplementary Figure 3C). Across LNCaP-CH and LNCaP-V16A cells, 40 significantly altered intracellular metabolites were consistently altered with the exception of Indole-3-acetate, L-xylonate and Adrenochrome, in both models (Figure 3A). Focusing on the 37 shared metabolites identified metabolic disruptions to glutamate and fatty acid metabolism (Figure 3B). It also revealed enrichment within the methionine, glutathione, purine and pyrimidine pathways (Figure 3B). The comprehensive characterization of changes in the levels of metabolites and gene expression relevant to the methionine pathway revealed commonalities between LNCaP-CH and LNCaP-V16A cells versus LNCaP cells that extend to the folate cycle and the glutathione pathway (Figure 3C). These data suggest methionine usage in the LNCaP-CH and LNCaP-V16A cells has been altered. Assessing the extracellular metabolites for changes in the availability of methionine pathway metabolites showed no difference in L-Methionine and L-Cystine, variable changes in L-Serine with only Glycine significantly decreased in the LNCaP-V16A cell culture media when comparing the media of the LNCaP-CH, and LNCaP cells (Supplementary Figure 4A). To determine whether LNCaP-CH and LNCaP-V16A cells share an increased dependence on these metabolites we assessed their growth in methionine pathway depleted metabolite culture media. Unexpectedly, no differences in growth responses were observed across LNCaP-CH, LNCaP-V16A and LNCaP cells in low-methionine (10%) or no-methionine (0%) conditions. All cells were intolerant to methionine depletion and tolerant to low-methionine conditions (Figure 3D). As cells can recycle methionine through the methionine and folate cycle an inhibitor of MAT2A was tested (53). MAT2A is one of the enzyme of the complex that is responsible for the conversion of L-Methionine into S-adenosylmethionine (SAM), the universal methyl donor employed for DNA and protein methylation (54). Only LNCaP-CH cells demonstrated some sensitivity to the MAT2A inhibitor FIDAS-5, in contrast to LNCaP-V16A and LNCaP cells which were insensitive to this inhibitor (Figure 3E). These results argue that prostate cancer cells exposed to chronic hypoxia may rely more heavily than castration sensitive and resistant prostate cancer cells on SAM production for their growth.

Chronic hypoxia and castration resistance underlies Increased dependency on glucose uptake

Further interrogation of the disrupted metabolic pathways identified glycolysis related pathways in both the LNCaP-CH and LNCaP-V16A cells compared to LNCaP cells. Increased expression of genes related to these pathways was also observed at the transcriptional level. This argues for dependencies on glycolysis related pathways for castration resistance (Figure 4A). To assess these dependencies, we first measured the abundance of glycolysis related metabolites in the cell culture media. Our results show reduced glucose and glutamine levels and increased glutamate levels in the media of all cells compared to the naive culture media (Supplementary Figure 4B). While lower levels of glucose were observed in the media of the LNCaP-CH and LNCaP-V16A cells compared to LNCaP cells, this difference only reached significance in LNCaP-V16A cells (Supplementary Figure 4B). We next assessed for dependencies on glucose uptake for growth across our prostate cancer models using glucose pathway depleted culture media. Our results showed how LNCaP-CH and LNCaP-V16A cells are more sensitive to low-glucose (10%) as well as no-glucose (0%) conditions than the LNCaP cells (Figure 4B). We further tested the sensitivity of our prostate cancer models to the GLUT1 inhibitor, BAY-876. While LNCaP cells were intrinsically resistant to GLUT1 inhibition, LNCaP-CH and LNCaP-V16A cells showed a dose-dependent significant growth inhibition upon treatment with the GLUT1 inhibitor BAY-876, in contrast to the inactive compound BAY-588 (Figure 4C). Collectively, our results argue for a shared dependency on glucose dependency in prostate cancer cells chronically exposed to hypoxia and independently established models of castration resistance. Furthermore, these results support the inclusion of GLUT1 chemical inhibitors in the development of treatment strategies to limit prostate cancer progression.

Here, we demonstrated how chronic hypoxia favours androgen insensitivity in prostate cancer cells, a feature central to the progression to lethal castration resistant prostate cancer. Our results expand on previous studies reporting the role for hypoxia to increase migration and invasion properties in prostate cancers (55, 56), features typical of the response to hypoxia across various cancer types (25). Furthermore, these results parallel the impact reported from cycles of acute hypoxia toward androgen insensitivity in prostate cancer (26, 57). Although acute hypoxia has been implicated in prostate cancer progression (58), in vivo evidence suggests chronic hypoxia increases prostate tumour growth (4). Moreover, longer exposure to hypoxia (> 24 hours) progressively decreased the expression of RAD51, required for homologous recombination (HR) during double strand break repair, in prostate cancer (59). A loss of HR in the cells leads to increased genomic instability (59). Therefore, the longer cells are exposed to hypoxia the more likely they are to become genetically unstable, promoting tumour genetic heterogeneity, observed in hypoxic prostate cancer samples (20) and an attribute of metastatic CRPC (60). Collectively, our work proposes a contribution of chronic hypoxia towards increased risk of progression by favouring androgen insensitivity in prostate cancer.

We further demonstrate how chronic hypoxia alters transcriptional and metabolic pathways, mimicking changes observed in castration-resistant prostate cancer cells. We specifically identify transcriptional and metabolic changes affecting the methionine pathway. The methionine pathway accounts for the production of S-adenosylmethionine (SAM), the universal methyl donor for protein and DNA methylation (54). Our results show a decrease in the abundance of S-adenosylhomocysteine (SAH), a potent inhibitor of methylation formed from the donation of the SAM methyl group to a methyltransferase, implying a change in the usage of SAM (54, 61). However, we could not detect increased sensitivity to short term methionine depletion in prostate cancer cells following chronic exposure to hypoxia. This may be, in part, due to histone methylation acting as a sink for the methyl group, indicating short-term depletion may have little effect on the cells (62). However, the subsequent investigation of the MAT2A inhibitor, the enzyme responsible for the conversion of L-methionine to SAM (54), only identified a susceptibility in prostate cancer cells maintained under chronic hypoxia. These findings suggest the hypoxic cells have a greater dependence on the production of SAM from L-methionine, which may reflect a greater dependence of glutathione production for reactive oxygen detoxification (63). Collectively, these results suggest that chronic hypoxia induces changes in the methionine cycle typical of those observed in castration-resistant prostate cancer. Furthermore, altering this pathway may lead to changes in methionine reservoirs within the hypoxic and castration-resistant cells that could be further investigated and therapeutically exploited.

Beyond the methionine pathway, we observed significant differences in glycolysis related pathways that suggest an increased dependency on glucose under chronic hypoxia exposure and castration-resistant prostate cancer cells. Work by Geng et al. demonstrated cycles of acute hypoxia promoted the transcription of GPI, which promoted a metabolic shift to glycolysis (26). The changes in these metabolic pathways reduced the sensitivity of these cells to enzalutamide, an AR inhibitor. The silencing of GPI resensitized the cells to enzalutamide (26). The transcriptional analysis with LNCaP-CH cells also identified GPI expression as increased during chronic hypoxia. However, GPI was not differentially expressed in the LNCaP-V16A cells (Fig. 4A). Indicating therapeutically targeting or using increased expression of GPI alone does not identify androgen insensitive cells. However, the shared transcriptional changes in the hypoxic and castration-resistant cells identified enzymes involved in the early stages of the glycolysis pathway, with the hypoxic cells showing changes in glucose membrane transporter GLUT1, a marker of hypoxia (64), and a known prognostic factor for recurrence in prostate cancer (65). Moreover, the preferential expression of the hypoxic and castration resistance gene set within the Cases group of the Porto cohort implicates a role of glycolysis dependence during prostate cancer progression (47). However, the data presented here implies both the transcriptional and metabolic analysis were required to fully identify the dependency on glycolysis. The metabolic analysis further implicated a dependency onglucose uptake in androgen insensitivity. In agreement, we report a vulnerability to the GLUT1 inhibitor BAY-876 in both chronic hypoxia and castration-resistant prostate cancer cells, revealing a therapeutically targetable weakness arising under chronic hypoxia.

Acknowledgements

The authors thank the Princess Margaret Genomics Centre and the Princess Margaret Bioinformatics group for providing support and infrastructure for the computational analysis of this work as well as high-throughput sequencing support. We thank members of the M.L. lab for their fruitful discussions and feedback. This work is supported by the Canadian Institute of Health Research (CIHR) (FRN-153234 & 168933 to M.L.), the Ontario Institute for Cancer Research (OICR) Investigator Award through funding provided by the Government of Ontario (M.L.) and the Princess Margaret Cancer Foundation.

Author Disclosures

At the time of publication, James Hawley was an employee of Hoffman-La Roche Limited (Roche Canada). All contributions to the conception, design, analysis, and interpretation of results for this project were completed prior to this employment. James Hawley declares no conflicts of interest. At the time of publication, Aditi Qamra was an employee of Hoffman-La Roche Limited (Roche Canada). All contributions to the conception, design, analysis, and interpretation of results for this project were completed prior to this employment. Aditi Qamra declares no conflicts of interest.

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supplementary table 2 is not available with this version

There is NO conflict of interest to disclose.

SuppFig1.pdf
Supplementary Figure 1A) VCaP cells were cultured in either 21% (blue) or 1% oxygen (red), with N.S representing not significant. B) Proliferation in 21% and 1% oxygen of two immortalised prostate derived cell lines, the RWPE-1 and PWR-1E (* p value=0.05 – 10^-3, ** p value=10^-3 - 10^-6, *** p value=>10^-6). C) The expression of HIF1ɑ target genes SLC2A1 and KDM3A, normalised to TBP, in the VCaP cells. D) Proliferation of the VCaP-CH cells when reoxygenated was compared to cells continuously grown in 1% oxygen.
SuppFig2.pdf
Supplemental Figure 2A) An upset plot represents the differentially expressed transcripts identified in the LNCaP-CH and LNCaP-V16A cells when compared to the LNCaP cells. B) A KEGG pathway analysis of the shared up-regulated transcripts in the LNCaP-CH and LNCaP-V16A cells. C) The box plot represents the expression of 166 identified out of the 199 LNCaP-CH and LNCaP-V16A gene set identified in the Porto cohort. Samples were separated based on whether they were in the case (BCR) or control (Non-BCR) group. Unpaired one-tailed t-tests with FDR correction were performed on the case and control groups to generate a q-value of 0.0729.
SuppFig3.pdf
Supplementary Figure 3A) A heat map of the significantly different (q value <0.05, log2 fold change ≥1.5) metabolites in the LNCaP-CHs compared to the LNCaP cells. B) Metaboanalyst pathway impact analysis of all significantly altered metabolites. Purple text highlights pathways related to methionine and one carbon while the red text highlights glycolysis related pathways. C) Heat map of the significantly altered metabolites (q value <0.05, fold change ≥1.5) in the LNCaP-V16A as compared to the LNCaP cells. D) A Metaboanalyst pathway impact analysis of the significantly altered metabolites in the LNCaP-V16A cells. With pathways colour coded as previously indicated.
SuppFig4.pdf
Supplementary Figure 4.A) Bar graphs representing the quantile normalised peak intensity of the methionine related metabolites profiled in the media during the metabolic analysis (n = 3 for LNCaP-CH and 4 for LNCaP, LNCaP-V16A). The red dotted line indicates the naive media concentration of the metabolite with statistical significance determined by unpaired t-tests (* p value=0.05 – 10^-3, ** p value=10^-3 - 10^-6, *** p value=>10^-6). B) Bar graphs representing the quantile normalised peak intensity of the glycolysis related metabolites profiled in the media during the metabolic analysis (n = 3 for LNCaP-CH and 4 for LNCaP, LNCaP-V16A).
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Chronic hypoxia favours adoption to a castration-resistant cell state in prostate cancer

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