Circulating Tumor and Invasive Cell Gene Expression Profile Predicts Treatment Response and Survival in Pancreatic Adenocarcinoma

Kenneth H Yu, Mark Ricigliano, Brian McCarthy, Joanne F Chou, Marinela Capanu, Brandon Cooper, Andrew Bartlett, Christina Covington, Maeve A Lowery, Eileen M O'Reilly, Kenneth H Yu, Mark Ricigliano, Brian McCarthy, Joanne F Chou, Marinela Capanu, Brandon Cooper, Andrew Bartlett, Christina Covington, Maeve A Lowery, Eileen M O'Reilly

Abstract

Previous studies have shown that pharmacogenomic modeling of circulating tumor and invasive cells (CTICs) can predict response of pancreatic ductal adenocarcinoma (PDAC) to combination chemotherapy, predominantly 5-fluorouracil-based. We hypothesized that a similar approach could be developed to predict treatment response to standard frontline gemcitabine with nab-paclitaxel (G/nab-P) chemotherapy. Gene expression profiles for responsiveness to G/nab-P were determined in cell lines and a test set of patient samples. A prospective clinical trial was conducted, enrolling 37 patients with advanced PDAC who received G/nab-P. Peripheral blood was collected prior to treatment, after two months of treatment, and at progression. The CTICs were isolated based on a phenotype of collagen invasion. The RNA was isolated, cDNA synthesized, and qPCR gene expression analyzed. Patients were most closely matched to one of three chemotherapy response templates. Circulating tumor and invasive cells' SMAD4 expression was measured serially. The CTICs were reliably isolated and profiled from peripheral blood prior to and during chemotherapy treatment. Individual patients could be matched to distinct response templates predicting differential responses to G/nab-P treatment. Progression free survival was significantly correlated to response prediction and ΔSMAD4 was significantly associated with disease progression. These findings support phenotypic profiling and ΔSMAD4 of CTICs as promising clinical tools for choosing effective therapy in advanced PDAC, and for anticipating disease progression.

Keywords: 5-fluorouracil; FOLFIRINOX; SMAD4; circulating tumor and invasive cells; gemcitabine; nab-paclitaxel; pancreatic cancer.

Conflict of interest statement

The following authors report no conflicts of interest: Joanne F. Chou, Marinela Capanu, Christina Covington, Maeve A. Lowery and Eileen M. O’Reilly. Kenneth H. Yu serves as an advisor to Adera Biolabs. Yu has no financial interest in and has not received compensation from Adera Biolabs. Brandon Cooper, Andrew Bartlett, Mark Ricigliano, and Brian McCarthy are employees of Adera Biolabs.

Figures

Figure 1
Figure 1
Kaplan–Meier analysis of progression-free survival (PFS) of patients treated with G/nab-P based on classification into one of three PGx profiles (A), and based on predicted G/nab-P sensitivity (B).
Figure 2
Figure 2
Performance of PGx profiling (A), G/nab-P sensitivity (B), ΔSMAD4 (C), and a combined analysis (D) to predict treatment response. Six-month PFS was used as a cut-off for predicting sensitivity and response (>6 months) or resistance and lack of response (<6 months).
Figure 3
Figure 3
Kaplan–Meier analysis of PFS based on ΔSMAD4 (A), ΔSMAD4 (S4), and G/nab-P sensitivity (GN+) or resistance (GN-); (B) decrease in carbohydrate antigen (CA) 19-9 by 50% (C) or 90% (D) after 2 months of treatment with G/nab-P.
Figure 4
Figure 4
Consort diagram.

References

    1. Matrisian L.M., Aizenberg R., Rosenzweig A. The Alarming Rise of Pancreatic Cancer Deaths in the United States: Why We Need to Stem the Tide Today. [(accessed on 10 September 2018)]; Pancreatic Cancer Action Network, 2012. Available online: .
    1. Conroy T., Desseigne F., Ychou M., Bouche O., Guimbaud R., Becouarn Y., Adenis A., Raoul J.L., Gourgou-Bourgade S., De la Fouchardiere C., et al. FOLFIRINOX versus gemcitabine for metastatic pancreatic cancer. N. Engl. J. Med. 2011;364:1817–1825. doi: 10.1056/NEJMoa1011923.
    1. Von Hoff D.D., Ervin T., Arena F.P., Chiorean E.G., Infante J., Moore M., Seay T., Tjulandin S.A., Ma W.W., Saleh M.N., et al. Increased survival in pancreatic cancer with nab-paclitaxel plus gemcitabine. N. Engl. J. Med. 2013;369:1691–1703. doi: 10.1056/NEJMoa1304369.
    1. Poplin E., Wasan H., Rolfe L., Raponi M., Ikdahl T., Bondarenko I., Davidenko I., Bondar V., Garin A., Boeck S., et al. Randomized, Multicenter, Phase II Study of CO-101 Versus Gemcitabine in Patients With Metastatic Pancreatic Ductal Adenocarcinoma: Including a Prospective Evaluation of the Role of hENT1 in Gemcitabine or CO-101 Sensitivity. J. Clin. Oncol. 2013;31:4453–4461. doi: 10.1200/JCO.2013.51.0826.
    1. Lamb J., Crawford E.D., Peck D., Modell J.W., Blat I.C., Wrobel M.J., Lerner J., Brunet J.P., Subramanian A., Ross K.N., et al. The Connectivity Map: Using gene-expression signatures to connect small molecules, genes, and disease. Science. 2006;313:1929–1935. doi: 10.1126/science.1132939.
    1. Wei G., Twomey D., Lamb J., Schlis K., Agarwal J., Stam R.W., Opferman J.T., Sallan S.E., Den Boer M.L., Pieters R., et al. Gene expression-based chemical genomics identifies rapamycin as a modulator of MCL1 and glucocorticoid resistance. Cancer Cell. 2006;10:331–342. doi: 10.1016/j.ccr.2006.09.006.
    1. Lu J., Fan T., Zhao Q., Zeng W., Zaslavsky E., Chen J.J., Frohman M.A., Golightly M.G., Madajewicz S., Chen W.T. Isolation of circulating epithelial and tumor progenitor cells with an invasive phenotype from breast cancer patients. Int. J. Cancer. 2010;126:669–683. doi: 10.1002/ijc.24814.
    1. Paris P.L., Kobayashi Y., Zhao Q., Zeng W., Sridharan S., Fan T., Adler H.L., Yera E.R., Zarrabi M.H., Zucker S., et al. Functional phenotyping and genotyping of circulating tumor cells from patients with castration resistant prostate cancer. Cancer Lett. 2009;277:164–173. doi: 10.1016/j.canlet.2008.12.007.
    1. Fan T., Zhao Q., Chen J.J., Chen W.T., Pearl M.L. Clinical significance of circulating tumor cells detected by an invasion assay in peripheral blood of patients with ovarian cancer. Gynecol. Oncol. 2009;112:185–191. doi: 10.1016/j.ygyno.2008.09.021.
    1. Premasekharan G., Gilbert E., Okimoto R.A., Hamirani A., Lindquist K.J., Ngo V.T., Roy R., Hough J., Edwards M., Paz R., et al. An improved CTC isolation scheme for pairing with downstream genomics: Demonstrating clinical utility in metastatic prostate, lung and pancreatic cancer. Cancer Lett. 2016;380:144–152. doi: 10.1016/j.canlet.2016.06.017.
    1. Pearl M.L., Dong H., Zhao Q., Tulley S., Dombroff M.K., Chen W.T. iCTC drug resistance (CDR) Testing ex vivo for evaluation of available therapies to treat patients with epithelial ovarian cancer. Gynecol. Oncol. 2017;147:426–432. doi: 10.1016/j.ygyno.2017.08.018.
    1. Pearl M.L., Zhao Q., Yang J., Dong H., Tulley S., Zhang Q., Golightly M., Zucker S., Chen W.T. Prognostic analysis of invasive circulating tumor cells (iCTCs) in epithelial ovarian cancer. Gynecol. Oncol. 2014;134:581–590. doi: 10.1016/j.ygyno.2014.06.013.
    1. Pearl M.L., Dong H., Tulley S., Zhao Q., Golightly M., Zucker S., Chen W.T. Treatment monitoring of patients with epithelial ovarian cancer using invasive circulating tumor cells (iCTCs) Gynecol. Oncol. 2015;137:229–238. doi: 10.1016/j.ygyno.2015.03.002.
    1. Tulley S., Zhao Q., Dong H., Pearl M.L., Chen W.T. Vita-Assay Method of Enrichment and Identification of Circulating Cancer Cells/Circulating Tumor Cells (CTCs) Methods Mol. Biol. 2016;1406:107–119.
    1. Yu K.H., Ricigliano M., Hidalgo M., Abou-Alfa G.K., Lowery M.A., Saltz L.B., Crotty J.F., Gary K., Cooper B., Lapidus R., et al. Pharmacogenomic modeling of circulating tumor and invasive cells for prediction of chemotherapy response and resistance in pancreatic cancer. Clin. Cancer Res. 2014;20:5281–5289. doi: 10.1158/1078-0432.CCR-14-0531.
    1. Ferrone C.R., Finkelstein D.M., Thayer S.P., Muzikansky A., Fernandez-delCastillo C., Warshaw A.L. Perioperative CA19-9 levels can predict stage and survival in patients with resectable pancreatic adenocarcinoma. J. Clin. Oncol. 2006;24:2897–2902. doi: 10.1200/JCO.2005.05.3934.
    1. Berger A.C., Garcia M., Jr., Hoffman J.P., Regine W.F., Abrams R.A., Safran H., Konski A., Benson A.B., 3rd, MacDonald J., Willett C.G. Postresection CA 19-9 predicts overall survival in patients with pancreatic cancer treated with adjuvant chemoradiation: A prospective validation by RTOG 9704. J. Clin. Oncol. 2008;26:5918–5922. doi: 10.1200/JCO.2008.18.6288.
    1. Yang G.Y., Malik N.K., Chandrasekhar R., Ma W.W., Flaherty L., Iyer R., Kuvshinoff B., Gibbs J., Wilding G., Warren G., et al. Change in CA 19-9 levels after chemoradiotherapy predicts survival in patients with locally advanced unresectable pancreatic cancer. J. Gastrointest. Oncol. 2013;4:361–369. doi: 10.1016/j.ijrobp.2010.07.709.
    1. Hess V., Glimelius B., Grawe P., Dietrich D., Bodoky G., Ruhstaller T., Bajetta E., Saletti P., Figer A., Scheithauer W., et al. CA 19-9 tumour-marker response to chemotherapy in patients with advanced pancreatic cancer enrolled in a randomised controlled trial. Lancet Oncol. 2008;9:132–138. doi: 10.1016/S1470-2045(08)70001-9.
    1. Ballehaninna U.K., Chamberlain R.S., Serum C.A. 19-9 as a Biomarker for Pancreatic Cancer-A Comprehensive Review. Indian J. Surg. Oncol. 2011;2:88–100. doi: 10.1007/s13193-011-0042-1.
    1. Waddell N., Pajic M., Patch A.M., Chang D.K., Kassahn K.S., Bailey P., Johns A.L., Miller D., Nones K., Quek K., et al. Whole genomes redefine the mutational landscape of pancreatic cancer. Nature. 2015;518:495–501. doi: 10.1038/nature14169.
    1. Kang Y., Ling J., Suzuki R., Roife D., Chopin-Laly X., Truty M.J., Chatterjee D., Wang H., Thomas R.M., Katz M.H., et al. SMAD4 regulates cell motility through transcription of N-cadherin in human pancreatic ductal epithelium. PLoS ONE. 2014;9:e107948. doi: 10.1371/journal.pone.0107948.
    1. Polley M.Y., Lamborn K.R., Chang S.M., Butowski N., Clarke J.L., Prados M. Six-month progression-free survival as an alternative primary efficacy endpoint to overall survival in newly diagnosed glioblastoma patients receiving temozolomide. Neuro Oncol. 2010;12:274–282. doi: 10.1093/neuonc/nop034.
    1. Philip P.A., Chansky K., LeBlanc M., Rubinstein L., Seymour L., Ivy S.P., Alberts S.R., Catalano P.J., Crowley J. Historical controls for metastatic pancreatic cancer: Benchmarks for planning and analyzing single-arm phase II trials. Clin. Cancer Res. 2014;20:4176–4185. doi: 10.1158/1078-0432.CCR-13-2024.
    1. Krempley B.D., Yu K.H. Preclinical models of pancreatic ductal adenocarcinoma. Chin. Clin. Oncol. 2017;6:25. doi: 10.21037/cco.2017.06.15.
    1. Ponz-Sarvise M., Tuveson D.A., Yu K.H. Mouse Models of Pancreatic Ductal Adenocarcinoma. Hematol. Oncol. Clin. N. Am. 2015;29:609–617. doi: 10.1016/j.hoc.2015.04.010.
    1. Boj S.F., Hwang C.-I., Baker L.A., Chio II.C., Engle D.D., Corbo V., Jager M., Ponz-Sarvise M., Tiriac H., Spector M.S., et al. Organoid Models of Human and Mouse Ductal Pancreatic Cancer. Cell. 2015;160:1–15. doi: 10.1016/j.cell.2014.12.021.
    1. Scherf U., Ross D.T., Waltham M., Smith L.H., Lee J.K., Tanabe L., Kohn K.W., Reinhold W.C., Myers T.G., Andrews D.T., et al. A gene expression database for the molecular pharmacology of cancer. Nat. Genet. 2000;24:236–244. doi: 10.1038/73439.
    1. Staunton J.E., Slonim D.K., Coller H.A., Tamayo P., Angelo M.J., Park J., Scherf U., Lee J.K., Reinhold W.O., Weinstein J.N., et al. Chemosensitivity prediction by transcriptional profiling. Proc. Natl. Acad. Sci. USA. 2001;98:10787–10792. doi: 10.1073/pnas.191368598.
    1. Lee J.K., Havaleshko D.M., Cho H., Weinstein J.N., Kaldjian E.P., Karpovich J., Grimshaw A., Theodorescu D. A strategy for predicting the chemosensitivity of human cancers and its application to drug discovery. Proc. Natl. Acad. Sci. USA. 2007;104:13086–13091. doi: 10.1073/pnas.0610292104.
    1. Adamski M.G., Gumann P., Baird A.E. A method for quantitative analysis of standard and high-throughput qPCR expression data based on input sample quantity. PLoS ONE. 2014;9:e103917. doi: 10.1371/journal.pone.0103917.
    1. Costa C., Gimenez-Capitan A., Karachaliou N., Rosell R. Comprehensive molecular screening: From the RT-PCR to the RNA-seq. Transl. Lung Cancer Res. 2013;2:87–91.
    1. Deeley R.G., Westlake C., Cole S.P. Transmembrane transport of endo- and xenobiotics by mammalian ATP-binding cassette multidrug resistance proteins. Physiol. Rev. 2006;86:849–899. doi: 10.1152/physrev.00035.2005.
    1. Gottesman M.M., Ling V. The molecular basis of multidrug resistance in cancer: The early years of P-glycoprotein research. FEBS Lett. 2006;580:998–1009. doi: 10.1016/j.febslet.2005.12.060.
    1. Ross D.D., Nakanishi T. Impact of breast cancer resistance protein on cancer treatment outcomes. Methods Mol. Biol. 2010;596:251–290.
    1. Li Q., Shu Y. Role of solute carriers in response to anticancer drugs. Mol. Cell. Ther. 2014;2:15. doi: 10.1186/2052-8426-2-15.
    1. He L., Vasiliou K., Nebert D.W. Analysis and update of the human solute carrier (SLC) gene superfamily. Hum. Genom. 2009;3:195–206. doi: 10.1186/1479-7364-3-2-195.
    1. De Mattia E., Cecchin E., Toffoli G. Pharmacogenomics of intrinsic and acquired pharmacoresistance in colorectal cancer: Toward targeted personalized therapy. Drug Resist. Updat. 2015;20:39–70. doi: 10.1016/j.drup.2015.05.003.
    1. Lemstrova R., Soucek P., Melichar B., Mohelnikova-Duchonova B. Role of solute carrier transporters in pancreatic cancer: A review. Pharmacogenomics. 2014;15:1133–1145. doi: 10.2217/pgs.14.80.
    1. Iacobuzio-Donahue C.A., Fu B., Yachida S., Luo M., Abe H., Henderson C.M., Vilardell F., Wang Z., Keller J.W., Banerjee P., et al. DPC4 gene status of the primary carcinoma correlates with patterns of failure in patients with pancreatic cancer. J. Clin. Oncol. 2009;27:1806–1813. doi: 10.1200/JCO.2008.17.7188.
    1. Shugang X., Hongfa Y., Jianpeng L., Xu Z., Jingqi F., Xiangxiang L., Wei L. Prognostic Value of SMAD4 in Pancreatic Cancer: A Meta-Analysis. Transl. Oncol. 2016;9:1–7. doi: 10.1016/j.tranon.2015.11.007.
    1. Whittle M.C., Hingorani S.R. RUNX3 defines disease behavior in pancreatic ductal adenocarcinoma. Mol. Cell. Oncol. 2016;3:e1076588. doi: 10.1080/23723556.2015.1076588.
    1. Gu A.D., Zhang S., Wang Y., Xiong H., Curtis T.A., Wan Y.Y. A critical role for transcription factor Smad4 in T cell function that is independent of transforming growth factor beta receptor signaling. Immunity. 2015;42:68–79. doi: 10.1016/j.immuni.2014.12.019.
    1. Cortez V.S., Ulland T.K., Cervantes-Barragan L., Bando J.K., Robinette M.L., Wang Q., White A.J., Gilfillan S., Cella M., Colonna M. SMAD4 impedes the conversion of NK cells into ILC1-like cells by curtailing non-canonical TGF-beta signaling. Nat. Immunol. 2017;18:995–1003.
    1. Schultz N.A., Dehlendorff C., Jensen B.V., Bjerregaard J.K., Nielsen K.R., Bojesen S.E., Calatayud D., Nielsen S.E., Yilmaz M., Hollander N.H., et al. MicroRNA biomarkers in whole blood for detection of pancreatic cancer. JAMA. 2014;311:392–404. doi: 10.1001/jama.2013.284664.
    1. Kim J., Bamlet W.R., Oberg A.L., Chaffee K.G., Donahue G., Cao X.J., Chari S., Garcia B.A., Petersen G.M., Zaret K.S. Detection of early pancreatic ductal adenocarcinoma with thrombospondin-2 and CA19-9 blood markers. Sci. Transl. Med. 2017;9 doi: 10.1126/scitranslmed.aah5583.
    1. Hoshida Y., Villanueva A., Kobayashi M., Peix J., Chiang D.Y., Camargo A., Gupta S., Moore J., Wrobel M.J., Lerner J., et al. Gene expression in fixed tissues and outcome in hepatocellular carcinoma. N. Engl. J. Med. 2008;359:1995–2004. doi: 10.1056/NEJMoa0804525.
    1. Xu L., Shen S.S., Hoshida Y., Subramanian A., Ross K., Brunet J.P., Wagner S.N., Ramaswamy S., Mesirov J.P., Hynes R.O. Gene expression changes in an animal melanoma model correlate with aggressiveness of human melanoma metastases. Mol. Cancer Res. 2008;6:760–769. doi: 10.1158/1541-7786.MCR-07-0344.
    1. Reiner A., Yekutieli D., Benjamini Y. Identifying differentially expressed genes using false discovery rate controlling procedures. Bioinformatics. 2003;19:368–375. doi: 10.1093/bioinformatics/btf877.

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