Supplemental Data. Proteome-Scale Investigation of Protein. Allosteric Regulation Perturbed. by Somatic Mutations in 7,000 Cancer Genomes

Transcription

1 The American Journal of Human Genetics, Volume 100 Supplemental Data Proteome-Scale Investigation of Protein Allosteric Regulation Perturbed by Somatic Mutations in 7,000 Cancer Genomes Qiancheng Shen, Feixiong Cheng, Huili Song, Weiqiang Lu, Junfei Zhao, Xiaoli An, Mingyao Liu, Guoqiang Chen, Zhongming Zhao, and Jian Zhang

2 Supplemental Data Figure S1. Patterns of the relationship between variants at allosteric sites and cancer types. D A and D B represent different diseases (cancer types) A and B, and V A and V B represent different variants A and B, respectively. Figure S2. Root mean-square fluctuation (RMSF) of backbone atoms relative to the initial structure for PDE10A-WT and PDE10A p.pro360ala in the Molecular dynamics (MD)

3 simulations. The wild-type crystal structure of PDE10A (GAF-B domain) was retrieved (PDB ID: 2ZMF) from the PDB database. 1 The p.pro360ala mutant form was obtained by changing proline to alanine in PDE10A using PyMOL. Before the MD simulations, a geometric optimization and electrostatic potential calculations were performed at the HF/6-31G level by the Gaussian 09 program. 2 After that, the partial atomic charges of camp were calculated by the restrained electrostatic potential (RESP) protocol with the Antechamber module of AMBER. The force field parameters for camp were found using the General AMBER Force Field (GAFF). 3 The standard AMBER force field for bio-organic systems (ff99sb) 4 was used to describe the protein parameters. The LEaP module in the AMBER software package (version 11) was used to add the missing hydrogen atoms of the proteins. Each complex was neutralized by adding 4 sodium counterions and solvated in a rectangular pre-equilibrated box of TIP3P water with at least a 10 Å distance around the complex. All MD simulations were performed using AMBER11. Firstly, minimizations were carried out for both solvated complexes. Each minimization was performed using the steepest decent method, switched to the conjugate gradient method every 3000 steps. The first minimization using a harmonic restraints weight of kcal/(mol Å 2 ) was applied to all of the protein atoms. Following this step, all atoms were released. Then, each system was warmed up from 0 to 300 K with 50 ps in the NVT ensemble. Next, each system was equilibrated for 300 ps to adjust the solvent density under 1 atm of pressure in the NPT ensemble. In the heating and equilibrium, all atoms of the protein were restrained by a harmonic restraint weight of 10.0 kcal/(mol.å 2 ). Finally, the MD simulation was run by releasing all of the restrains on each system for a total of 100 ns in the NPT ensemble, keeping the temperature at K and the pressure at 1 atm. During the simulations, a time step of 2 fs was used for the equations of motion, and periodic boundary conditions were employed to avoid edge effects in the calculation. The electrostatic interactions were calculated by the particle-mesh Ewald (PME) method 5 with a cutoff of 10.0 Å. The SHAKE algorithm was used to constrain the bond lengths involving hydrogens. 6,7 The motion and equilibration of the MD trajectories were monitored using the root-mean-square displacement

4 (RMSD) values of the backbone atoms by respecting the starting structure. Both of the complexes were stable during the last 20 ns. Principle component analysis (PCA) was performed using the stable trajectory (last equalized 20 ns trajectory) of the simulation to identify the change in the conformation space of PDE10A p.pro360ala. Table S1. All 574 allosteric protein-coding genes. See the attached excel file Table_S1.xlsx. Table S2. All 74 allosteric protein coding genes annotated with released crystal structures. See the attached excel file Table_S2.xlsx. Table S3. The gene sequence used for the construction of pcmv-pde10a2. See the attached excel file Table_S3.xlsx. Table S4. Predicted mutated allosteric proteins for each individual cancer. Cancer type Predicted allosteric proteins* COAD BRAF a,8, GRIA2 b, MAPK8 b,9, HK1 b,10, AR b,11, SAMHD1 b SKCM GCK a, BRAF a,12, SERPINC1 b, PPARG b,13, ALB b, CYP3A4 b, HRAS b,14 LUAD BRAF a,15, CHRM2 a,16, MALT1 b,17, HRAS b,18, IGF1R b,19, PANK3 b, ESR2 b,20, ME2 b,21, CHEK1 b,22, ITGAL b,23, PDE10A b UCEC CNSK2A1 a, SERPINC1 a, CYP3A4 a,24, PDE10A a, GRIA2 a, CDK2 a,25, PRKAA2 a, ME2 a, ITGAL a, AR b,26, SAMHD1 b, PTK2 b,27 STAD GNPDA1 b, F7 b, MAPK8 b, BRAF b,28, PDE5A b, AKT1 b,29, TTR b, NT5C2 b BRCA AKT1 a,30, PTK2 b,31, BRAF b, SERPINE1 b,32, MAPK14 b,33 HNSC HRAS a,34, PDE10A b, UGDH b LUSC CHRM2 a, HRAS a,35, BRAF b,36 GBM BRAF a,37 KIRC CYP3A4 a, LTA4H a OV BRAF b,38, ALB b,39 BLCA HRAS a,40 a : Significantly mutated allosteric proteins predicted with q < 0.1 b : Mutated allosteric proteins predicted with P < 0.05 as well as at least two variants at allosteric sites. *: Gene with underline means that it has been reported to involve in individual cancer type in the literature labeled at the top right-hand corner. References 1. Handa, N., Mizohata, E., Kishishita, S., Toyama, M., Morita, S., Uchikubo-Kamo, T., Akasaka, R., Omori, K., Kotera, J., Terada, T., et al. (2008). Crystal structure of the GAF-B

5 domain from human phosphodiesterase 10A complexed with its ligand, camp. J. Biol. Chem. 283, Gaussian 09, R.E., Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Mennucci, B.; Petersson, G. A.; Nakatsuji, H.; Caricato, M.; Li, X.; Hratchian, H. P.; Izmaylov, A. F.; Bloino, J.; Zheng, G.; Sonnenberg, J. L.; Hada, M.; Ehara, M.; Toyota, K.; Fukuda, R.; Hasegawa, J.; Ishida, M.; Nakajima, T.; Honda, Y.; Kitao, O.; Nakai, H.; Vreven, T.; Montgomery, J. A., Jr.; Peralta, J. E.; Ogliaro, F.; Bearpark, M.; Heyd, J. J.; Brothers, E.; Kudin, K. N.; Staroverov, V. N.; Kobayashi, R.; Normand, J.; Raghavachari, K.; Rendell, A.; Burant, J. C.; Iyengar, S. S.; Tomasi, J.; Cossi, M.; Rega, N.; Millam, J. M.; Klene, M.; Knox, J. E.; Cross, J. B.; Bakken, V.; Adamo, C.; Jaramillo, J.; Gomperts, R.; Stratmann, R. E.; Yazyev, O.; Austin, A. J.; Cammi, R.; Pomelli, C.; Ochterski, J. W.; Martin, R. L.; Morokuma, K.; Zakrzewski, V. G.; Voth, G. A.; Salvador, P.; Dannenberg, J. J.; Dapprich, S.; Daniels, A. D.; Farkas, Ö.; Foresman, J. B.; Ortiz, J. V.; Cioslowski, J.; Fox, D. J. Gaussian, Inc., Wallingford CT, Wang, J., Wolf, R.M., Caldwell, J.W., Kollman, P.A., and Case, D.A. (2004). Development and testing of a general amber force field. J. Comput. Chem. 25, Wickstrom, L., Okur, A., and Simmerling, C. (2009). Evaluating the performance of the ff99sb force field based on NMR scalar coupling data. Biophys. J. 97, Darden, T.A., and Pedersen, L.G. (1993). Molecular modeling: an experimental tool. Environ. Health. Perspect. 101, Jonkman, J.G., Wijsbeek, J., Hollenbeek, S., de Boer, S.H., de Zeeuw, R.A., Van Bork, L.E., and Orie, N.G. (1975). Determination of low cencentrations of the quaternary ammonium compound thiazinamium methylsulphate in plasma and urine. J. Pharm. Pharmacol. 27, Ryckaert, J.P., Ciccotti, G., and Berendsen, J.C. (1977). Numerical integration of the cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes. J. Comput. Phys. 23, Kawazoe, A., Shitara, K., Fukuoka, S., Kuboki, Y., Bando, H., Okamoto, W., Kojima, T., Fuse, N., Yamanaka, T., Doi, T., et al. (2015). A retrospective observational study of clinicopathological features of KRAS, NRAS, BRAF and PIK3CA mutations in Japanese patients with metastatic colorectal cancer. BMC Cancer 15, Slattery, M.L., Lundgreen, A., Bondurant, K.L., and Wolff, R.K. (2011). Tumor necrosis factor-related genes and colon and rectal cancer. Int. J. Mol. Epidemiol. Genet. 2, Graziano, F., Ruzzo, A., Giacomini, E., Ricciardi, T., Aprile, G., Loupakis, F., Lorenzini, P., Ongaro, E., Zoratto, F., Catalano, V., et al. (2016). Glycolysis gene expression analysis

6 and selective metabolic advantage in the clinical progression of colorectal cancer. Pharmacogenomics J. published online March 01, doi: /tpj Gu, S., Papadopoulou, N., Gehring, E.M., Nasir, O., Dimas, K., Bhavsar, S.K., Foller, M., Alevizopoulos, K., Lang, F., and Stournaras, C. (2009). Functional membrane androgen receptors in colon tumors trigger pro-apoptotic responses in vitro and reduce drastically tumor incidence in vivo. Mol. Cancer 8, Yaman, B., Akalin, T., and Kandiloglu, G. (2015). Clinicopathological characteristics and mutation profiling in primary cutaneous melanoma. Am. J. Dermatopathol. 37, Schadendorf, D. (2009). Peroxisome proliferator-activating receptors: a new way to treat melanoma? J. Invest. Dermatol. 129, Hassel, J.C., Groesser, L., Herschberger, E., Weichert, W., and Hafner, C. (2015). RAS mutations in benign epithelial tumors associated with BRAF inhibitor treatment of melanoma. J. Invest. Dermatol. 135, Caparica, R., de Castro, G., Jr., Gil-Bazo, I., Caglevic, C., Calogero, R., Giallombardo, M., Santos, E.S., Raez, L.E., and Rolfo, C. (2016). BRAF mutations in non-small cell lung cancer: has finally Janus opened the door? Crit. Rev. Oncol. Hematol. 101, Zhao, Q., Gu, X., Zhang, C., Lu, Q., Chen, H., and Xu, L. (2015). Blocking M2 muscarinic receptor signaling inhibits tumor growth and reverses epithelial-mesenchymal transition (EMT) in non-small cell lung cancer (NSCLC). Cancer Biol. Ther. 16, Pan, D., Jiang, C., Ma, Z., Blonska, M., You, M.J., and Lin, X. (2016). MALT1 is required for EGFR-induced NF-kappaB activation and contributes to EGFR-driven lung cancer progression. Oncogene 35, Wen, Y.S., Cai, L., Zhang, X.W., Zhu, J.F., Zhang, Z.C., Shao, J.Y., and Zhang, L.J. (2014). Concurrent oncogene mutation profile in Chinese patients with stage Ib lung adenocarcinoma. Medicine (Baltimore) 93, e Lin, J.C., Wu, Y.Y., Wu, J.Y., Lin, T.C., Wu, C.T., Chang, Y.L., Jou, Y.S., Hong, T.M., and Yang, P.C. (2012). TROP2 is epigenetically inactivated and modulates IGF-1R signalling in lung adenocarcinoma. EMBO Mol. Med. 4, Tanaka, K., Shimizu, K., Kakegawa, S., Ohtaki, Y., Nagashima, T., Kaira, K., Horiguchi, J., Oyama, T., and Takeyoshi, I. (2016). Prognostic significance of aromatase and estrogen receptor beta expression in EGFR wild-type lung adenocarcinoma. Am. J. Transl. Res. 8, Ren, J.G., Seth, P., Clish, C.B., Lorkiewicz, P.K., Higashi, R.M., Lane, A.N., Fan, T.W., and Sukhatme, V.P. (2014). Knockdown of malic enzyme 2 suppresses lung tumor growth, induces differentiation and impacts PI3K/AKT signaling. Sci. Rep. 4,

7 22. Bartucci, M., Svensson, S., Romania, P., Dattilo, R., Patrizii, M., Signore, M., Navarra, S., Lotti, F., Biffoni, M., Pilozzi, E., et al. (2012). Therapeutic targeting of Chk1 in NSCLC stem cells during chemotherapy. Cell Death Differ. 19, Chen, C., Fu, X., Zhang, D., Li, Y., Xie, Y., Li, Y., and Huang, Y. (2011). Varied pathways of stage IA lung adenocarcinomas discovered by integrated gene expression analysis. Int. J. Biol. Sci. 7, Chu, W., Fyles, A., Sellers, E.M., McCready, D.R., Murphy, J., Pal, T., and Narod, S.A. (2007). Association between CYP3A4 genotype and risk of endometrial cancer following tamoxifen use. Carcinogenesis 28, Di Cristofano, A., and Ellenson, L.H. (2007). Endometrial carcinoma. Annu. Rev. Pathol. 2, Matysiak, Z.E., Ochedalski, T., and Piastowska-Ciesielska, A.W. (2015). The evaluation of involvement of angiotensin II, its receptors, and androgen receptor in endometrial cancer. Gynecol. Endocrinol. 31, Thanapprapasr, D., Previs, R.A., Hu, W., Ivan, C., Armaiz-Pena, G.N., Dorniak, P.L., Hansen, J.M., Rupaimoole, R., Huang, J., Dalton, H.J., et al. (2015). PTEN Expression as a Predictor of Response to Focal Adhesion Kinase Inhibition in Uterine Cancer. Mol. Cancer Ther. 14, Lee, S.H., Lee, J.W., Soung, Y.H., Kim, H.S., Park, W.S., Kim, S.Y., Lee, J.H., Park, J.Y., Cho, Y.G., Kim, C.J., et al. (2003). BRAF and KRAS mutations in stomach cancer. Oncogene 22, Guo, S.L., Ye, H., Teng, Y., Wang, Y.L., Yang, G., Li, X.B., Zhang, C., Yang, X., Yang, Z.Z., and Yang, X. (2013). Akt-p53-miR-365-cyclin D1/cdc25A axis contributes to gastric tumorigenesis induced by PTEN deficiency. Nat. Commun. 4, Cotrim, C.Z., Fabris, V., Doria, M.L., Lindberg, K., Gustafsson, J.A., Amado, F., Lanari, C., and Helguero, L.A. (2013). Estrogen receptor beta growth-inhibitory effects are repressed through activation of MAPK and PI3K signalling in mammary epithelial and breast cancer cells. Oncogene 32, Lightfoot, H.M., Jr., Lark, A., Livasy, C.A., Moore, D.T., Cowan, D., Dressler, L., Craven, R.J., and Cance, W.G. (2004). Upregulation of focal adhesion kinase (FAK) expression in ductal carcinoma in situ (DCIS) is an early event in breast tumorigenesis. Breast Cancer Res. Treat. 88, Costantini, V., Sidoni, A., Deveglia, R., Cazzato, O.A., Bellezza, G., Ferri, I., Bucciarelli, E., and Nenci, G.G. (1996). Combined overexpression of urokinase, urokinase receptor, and plasminogen activator inhibitor-1 is associated with breast cancer progression: an immunohistochemical comparison of normal, benign, and malignant breast tissues. Cancer 77,

8 33. Slattery, M.L., Lundgreen, A., John, E.M., Torres-Mejia, G., Hines, L., Giuliano, A.R., Baumgartner, K.B., Stern, M.C., and Wolff, R.K. (2015). MAPK genes interact with diet and lifestyle factors to alter risk of breast cancer: the Breast Cancer Health Disparities Study. Nutr. Cancer 67, Rampias, T., Giagini, A., Siolos, S., Matsuzaki, H., Sasaki, C., Scorilas, A., and Psyrri, A. (2014). RAS/PI3K crosstalk and cetuximab resistance in head and neck squamous cell carcinoma. Clin. Cancer Res. 20, To, M.D., Rosario, R.D., Westcott, P.M., Banta, K.L., and Balmain, A. (2013). Interactions between wild-type and mutant Ras genes in lung and skin carcinogenesis. Oncogene 32, Yashima, H., Shimizu, K., Araki, T., Aomori, T., Ohtaki, Y., Nagashima, T., Enokida, Y., Atsumi, J., Nakamura, T., Takeyoshi, I., et al. (2014). Assessment of DDR2, BRAF, EGFR and KRAS mutations as therapeutic targets in non-adenocarcinoma lung cancer patients. Mol. Clin. Oncol. 2, Kuroda, J.I., Nobusawa, S., Nakamura, H., Yokoo, H., Ueda, R., Makino, K., Yano, S., and Kuratsu, J.I. (2016). A case of an epithelioid glioblastoma with the BRAF V600E mutation colocalized with BRAF intact low-grade diffuse astrocytoma. Neuropathology 36, Zeppernick, F., Ardighieri, L., Hannibal, C.G., Vang, R., Junge, J., Kjaer, S.K., Zhang, R., Kurman, R.J., and Shih Ie, M. (2014). BRAF mutation is associated with a specific cell type with features suggestive of senescence in ovarian serous borderline (atypical proliferative) tumors. Am. J. Surg. Pathol. 38, Asher, V., Lee, J., and Bali, A. (2012). Preoperative serum albumin is an independent prognostic predictor of survival in ovarian cancer. Med. Oncol. 29, McDaniel, A.S., Zhai, Y., Cho, K.R., Dhanasekaran, S.M., Montgomery, J.S., Palapattu, G., Siddiqui, J., Morgan, T., Alva, A., Weizer, A., et al. (2014). HRAS mutations are frequent in inverted urothelial neoplasms. Hum. Pathol. 45,