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Page 4 of 16 Tu et al. J Cancer Metastasis Treat 2018;4:58 I http://dx.doi.org/10.20517/2394-4722.2018.67

Extracellular flux assay
The extracellular acidification rate (ECAR)and oxygen consumption rate (OCR) were measured in real-
time using the XF24 extracellular flux bioanalyzer (Seahorse Bioscience, Agilent Technologies Australia,
[27]
Mulgrave, Vic, Australia), as described previously . Briefly, MDA-MB-231 or MDA-MB-231HM.LNm5 cells
were seeded at a concentration of 100,000 cells/well in RPMI medium the day before the assay. One hour
before the start of the metabolic profiling assay the medium was changed to XF Base medium (Seahorse
Bioscience) supplemented with sodium pyruvate (1 mmol/L), D-glucose (25 mmol/L) and adjusted to pH7.4.
To determine glycolytic parameters, ECAR was measured at baseline and after injection of oligomycin
(5 μmol/L) [Supplementary Figure 1A]. To determine respiration parameters, OCR was measured at baseline
and after injection of Oligomycin (5 μmol/L), [carbonyl cyanide-4 (trifluoromethoxy) phenylhydrazone
(FCCP), 1 μmol/L] and a combination of antimycin A and rotenone (2.5 μmol/L each). Parameters of mitochondrial
respiration were measured according to the XF cell Mito Stress test user manual [Supplementary Figure 2A].

RT-qPCR
RNA samples were isolated from 3 or more independent experiments. Total RNA was isolated using TRIzol®
reagent (Life technologies). RNA (100 ng) was reverse-transcribed using the High Capacity cDNA Reverse
Transcription Kit (Invitrogen, Mulgrave, Vic, Australia). Reactions of 5 µL total volume were performed us-
ing a Mastercycler® Pro (Eppendorf, Hamburg, Germany). cDNA (1 ng) was used for real-time PCR using
iTaq™ universal SYBR® Green Supermix (Bio-Rad, Gladesville, NSW, Australia) and an ABI Prism 7900HT
[22]
sequence detection system (Applied Biosystems), as described previously . Gene expression was normalized
-ΔCt
[28]
to 18S ribosomal RNA using the 2 method . Specificity of the primer sets was confirmed by dissociation
curve analysis. Primer sequences are listed in Supplementary Table 1.
RNA-seq library preparation and sequencing
RNA was pooled from 9 individual cultures of independent culture passage of MDA-MB-231HM.LNm5
cell line and the parental MDA-MB-231 cell line. Total RNA was isolated using TRIzol® (as above). RNA-seq
libraries were constructed from 500 ng total RNA using NEBNext Ultra RNA library prep kit for Illumina
(#E7530) with NEBNext Poly(A)mRNA Magnetic Isolation Module (#E7490). Prior to library preparation,
RNA was confirmed to be of high quality (RNA integrity number > 8) by Agilent Bioanalyzer 2100 analysis.
Paired end 2 × 50 bp rapid sequencing was performed on an Illumina HiSeq 2500 (Melbourne Transla-
tional Genomic Platform, University of Melbourne). Raw data was filtered by removing reads with adaptor
sequences, reads where the percentage of unknown bases is greater than 10%, and reads considered to be of
low quality (where bases with quality ≤ 5 constitute greater than 50% of base reads) to obtain “clean reads”.
All subsequent analyses are based on “clean reads” only.

RNA-Seq data analysis
FASTQ files were first analysed using FASTQC software (http://www.bioinformatics.babraham.ac.uk/proj-
ects/download.html) before proceeding with an integrated sequence trimming and alignment step against
the UCSC hg19 human reference genome downloaded from Illumina’s iGenomes (https://support.illumina.
[29]
com/sequencing/sequencing_software/igenome.html) using Rsubread package (v 1.20) . Reads that were
aligned to annotated coding regions of the genome were counted using the “featureCounts” feature from
[30]
[31]
Rsubread . These counts were subsequently normalized using the trimmed mean of M-value method
and transformed into counts per million (CPM) to describe gene expression level. As a single replicate per
condition was used, we assigned a biological coefficient of variation of 0.3 to proceed with the pairwise com-
[32]
parison analyses for the detection of differentially expressed genes using EdgeR software .
Gene Ontology analysis and gene list extraction
A list of all 1,158 nuclear-encoded mitochondrial genes was obtained from the MitoCarta2.0 human inven-
[33]
tory . Genes associated with the processes of glycolysis (canonical glycolysis GO:0061621; glycolytic process
GO:0006096; positive regulation of glycolytic process GO:0045821; negative regulation of glycolytic process