Metabolic vulnerability of breast cancer based on shifts in the expression of metabolic enzyme isoforms 1 Yale Cancer Center, New Haven, CT, USA; 2 JiangSu University, …….China; 3 University of Paris-East, Paris, France Weiwei Shi 1 , Sophia Ononye 1 , Aihua Gong 2 , Tingting Jiang 1 , Rene Natowicz 3 , Lajos Pusztai 1 Background Most cells express multiple different isoforms of the same metabolic enzyme. The expression levels of these isoenzymes vary by tissue differentiation stage and may also be altered during neoplastic transformation. Our goal was to identify isoenzymes that show reduced expression in one isoform while the other isoform has unchanged expression in breast cancer compared to normal breast. Since isoenzymes share similar catalytic activity, we hypothesize that the loss of isoenzyme diversity in cancer cells (i.e. reliance on only one or few isoforms rather than the full spectrum of isoforms) can render these cells selectively sensitive to isoenzyme-specif i c inhibitors that target the remaining isoform. Conclusions We demonstrate pronounced shifts in isoenzyme expression in breast cancers compared to normal breast tissues. These shifts suggest adaptation to hypoxic environment, rapid metabolism and point to potential metabolic vulnerabilities of cancer. Our siRNA experiments with anti-ME2 siRNA provide proof of concept that loss of isoenzyme diversity and primary reliance on a single or few isoenzymes that provide a particular metabolic function in neoplastic cells may be exploited therapeutically for cancer treatment. References 1. Vander Heiden, M.G., Cantley, L.C., Thompson, C.B. Understanding the Warburg Effect: The Metabolic Requirements of Cell Proliferation. Science 324: 1029-1033 (2009). 2. Vander Heiden, M.G. Targeting cancer metabolism: a therapeutic window opens. Nature Rev Drug Discov 10: 671-84 (2011). 3. Muller FL, Colla S, Aquilanti E, Manzo VE, Genovese G, Lee J, Eisenson D, Narurkar R, Deng P, Nezi L, Lee MA, Hu B, Hu J, Sahin E, Ong D, Fletcher-Sananikone E, Ho D, Kwong L, Brennan C, Wang YA, Chin L, DePinho RA. Passenger deletions generate therapeutic vulnerabilities in cancer Nature. 488(7411):337-42 (2012). Acknowledgements This work was supported in part by The Breast Cancer Research Foundation. 7A1_N 7A1_C 7A1_CL 7A2_N 7A2_C 7A2_CL 2 4 6 8 10 12 14 COX7A1 vs. 7A2 on N(normal), C(MDA103 Cancer), CL(cellLine) g1 g2 g1.names g2.names freqIn6Data aveOccur PPAP2B PPAP2C phosphatidic acid phosphatase type 2B phosphatidic acid phosphatase type 2C 6 83.7 PPAP2A PPAP2C phosphatidic acid phosphatase type 2A phosphatidic acid phosphatase type 2C 6 66.5 LDHB LDHC lactate dehydrogenase B lactate dehydrogenase C 6 49.6 LDHB LDHA lactate dehydrogenase B lactate dehydrogenase A 6 49.4 COX7A1 COX7A2 cytochrome c oxidase subunit VIIa polypeptide 1 (muscle) cytochrome c oxidase subunit VIIa polypeptide 2 (liver) 6 48.2 ME3 ME1 malic enzyme 3, NADP(+)-dependent, mitochondrial malic enzyme 1, NADP(+)-dependent, cytosolic 6 46.9 ALDOC ALDOA aldolase C, fructose-bisphosphate aldolase A, fructose-bisphosphate 6 33 ME3 ME2 malic enzyme 3, NADP(+)-dependent, mitochondrial malic enzyme 2, NAD(+)-dependent, mitochondrial 6 24.9 ALDOC ALDOB aldolase C, fructose-bisphosphate aldolase B, fructose-bisphosphate 6 24.8 CHKB CHKA choline kinase beta choline kinase alpha 6 20.9 Results 98 pairs of isoenzymes showed reduced expression (< 3 standard deviations below the mean expression in normal tissues) in one isoform in at least 20% of cancers compared to normal tissue with preserved or over-expression of the second isoform. An example of differential isoenzyme expression for the isoforms of phosphatidic acid phosphatase, PPAP2B and PPAP2C, is shown in Figure 1C. The most commonly altered isoenzyme pairs are shown in Table 1. The f i rst member in each isoenzyme pair including PPAP2B/PPAP2C, COX7A1/COX7A2, ALDOC/ALDOA, LDHB/LDHA, and ME3/ME2 show reduced expression in 84%, 48%, 33.0%, 49%, and 47% of cancers, respectively. Overall cancers shifted towards expressing isoforms that are normally highly expressed in muscle for many energy metabolism related enzymes. Oxidative phosphorylation and electron transfer related enzymes such as COX7A1/COX7A2 also frequently showed differences in expression pattern among cancerous, normal tissues, and cell line samples (Figure 2) . As proof of concept, we examined the effect of knocking down ME2 in MDA-MB-435 cells that lost ME1 and ME3 expression (Figure 3). Anti-ME2 siRNA produced a 51.0% growth inhibition compared to the scrambled siRNA control. ME2 knockdown had no growth inhibitory effect (0% growth inhibition) in the two control cell lines, MDAMB231 and MDAMB468, that show preserved expression of ME3 and ME2 expression. Additional in vitro experiments are underway to conf i rm the specif i city of the inhibitory effect. Methods 1,267 genes involved in 84 metabolic pathways were collected from the KEGG database and were matched to 2,212 isoenzyme gene pairs. 6 breast cancer gene expression datasets (N = 1,081 samples) and one normal tissue dataset (n = 40 samples) were used to establish pair-wise isoenzyme expression distributions. Within each data cohort, we searched isoenzyme pairs that showed loss of expression in one isoform in cancers compared to normal breast tissues while the other isoform was preserved or overexpressed (Figures 1A and 1B). Functional experiments were performed using isoform-specif i c siRNA constructs (Dharmacon, USA) and cell lines purchased from ATCC. Selection of isoenzyme pairs and cell lines was based on cell line availability and gene expression distribution of isoenzymes in at least some cell lines that mimicked the isoform distribution in human cancers. For study, we selected cell lines that show loss of expression in one isoform and control cell lines included cells that express all isoforms. Our initial siRNA experiments focused on malic enzyme (ME) via ME2 knockdown using MDA-MB-435 as the experimental cell line whereas MDA-MB-231 and MDA-MB-468 served as control cell lines. Figure 1: Comparative analysis of isoenzyme expression in cancer versus normal breast tissues: (A) PPAP2B expression is lower in cancers (red) versus normal breast tissues (blue); (B) PPAP2C expression is similar in both cancers and normal breast tissues; (C) Distinctive expression patterns of PPAP2B and PPAP2C in normal tissues (green) and cancers (red). Figure 2. Average expression levels of COX7A1 and COX7A2 in normal breast, breast cancer and cell lines. Expression of COX7A1 in normal cells (7A1_N); cancer (7A1_C); and in cell lines (7A1_CL). Expression of COX7A2 in normal cells (7A2_N); cancer (7A2_C); and in cell lines (7A2_CL). Table 1. Isoenzyme pairs signif i cantly display reduced expression in the f i rst isoform (g1) and normal or increased expression in the second (g2) isoform in breast cancer compared to normal tissues. Figure 3. Expression of malic enzyme isoforms (ME1, 2, 3) in the cell lines selected for siRNA experiments: g1,g2 and g3 correspond to ME3, ME2 and ME1 and p1, p2 and p3 are the probesets. MDA-MB-435 and SUM44PE were used as experimental cell lines and the other cell lines served as controls. 4 6 8 10 12 4 6 8 10 12 Cancer(red) vs. Normal(green) MDA233 vs. 40 Normal PPAP2B@209355_s_at PPAP2C@209529_at Cancer (red) vs. Normal (blue) Samples Expression Rank of PPAP2B@209355_s_at Frequency 0 5000 10000 15000 20000 0 2 4 6 8 10 Cancer (red) vs. Normal (blue) Samples Expression Rank of PPAP2C@209529_at Frequency 0 5000 10000 15000 20000 0 10 20 30 40 A B C