Pyxis Oncology, Inc. · NASDAQ:PYXS
Pyxis Oncology — ASCO 2022
14 slides from Pyxis Oncology's conference presentation, June 2022
Slide 1: Distinct biosignatures associate with survival after chemoimmunotherapy in phase II pancreatic cancer study
Distinct biosignatures associate with survival after chemoimmunotherapy in a randomized, three-arm phase II study in patients with metastatic pancreatic cancer Lacey J. Padrón, PhD – Vice President, Informatics – Parker Institute for Cancer Immunotherapy Lacey J. Padrón1*, Deena M. Maurer1, Mark H.
Slide 2: PRINCE clinical trial of chemoimmunotherapy combinations in mPDAC
PRINCE clinical trial of chemoimmunotherapy combinations in mPDAC Gemcitabine + nab-Paclitaxel +/- CD40 agonist (sotigalimab) +/- PD-1 blockade (nivolumab) CD40 4 Antibody (sotigalimab) Trafficking of T-cells to tumors (CTLs) 5 Infiltration of T-cells into tumors (CTLs, endothelial cells) 3 Pancreat
Slide 3: PRINCE trial design
PRINCE trial design Ph2 Randomization nivo/chemo (n=34): gem/nab-P* + nivolumab 240 mg q2w 1L Metastatic Follow up for PDAC sotiga/chemo (n=30 + n=6 ph1b): gem/nab-P* + sotigalimab 0.3 mg/kg q4w (D3 of each cycle) Progression and N=105 Survival sotiga/nivo/chemo (n=29 + n=6 ph1b): gem/nab-P* + sotig
Slide 4: Clinical results
4 Clinical results Overall Survival 1.00 + + Overall Survival Probability ++ + ++ Percent Change in Sum of Target Lesions 0.75 + + 100 * = confirmed CR/PR nivo/chemo sotiga/chemo 0.50 + 80 sotiga/nivo/chemo +++ Maximum Change from Baseline (%) + ++ + 60 0.25 + + + ++ + ++ + 40 0.00 20 0 6 12 18 24 3
Slide 5: PRINCE translational profiling
5 PRINCE translational profiling Adaptive panel Clinical Vectra Imaging Data Innate panel Tumor Tissue RNA Seq Sequencing Whole Exome Seq Cell free DNA TCR Seq mutant KRAS Blood Serum Proteomics O-link targeted protein panels CANDEL Database PBMC profiling Shotgun & glycoprotein mass spec CyTOF: Bro
Slide 6: CANDEL: Our software platform for multi-omic data analysis
CANDEL: Our software platform for multi-omic data analysis Molecular data Tumor sequencing CANDEL Gene expression Immune profiling High-dimensional imaging Cell Free DNA Clinical data Treatment information Efficacy data Informatics and Translational Teams Safety data § Biomarkers of response § Machi
Slide 7: Pharmacodynamic effects of immunotherapies
7 Pharmacodynamic effects of immunotherapies Increases in activated and Increases in soluble proteins Blood proliferating T cells indicating immune activation n = 19-26 n = 18-28 n = 14-32 n = 23-32 n = 25-36 n = 25-35 PRESENTED BY: Lacey J. Padròn, PhD Vice President, Informatics – Parker Institute
Slide 8: Circulating biomarkers of survival following nivo/chemo
8 Circulating biomarkers of survival following nivo/chemo Blood § Baseline levels of T cell populations in circulation predict survival following nivo/chemo § Many predictive T cell populations show n = 14/12 n = 13/15 n = 17/15 an activated, antigen-experienced phenotype § Biomarkers predict surviv
Slide 9: Tumor biomarkers of survival following nivo/chemo
9 Tumor biomarkers of OS Status Oxidative Phosphorylation survival following Cogaulation Fatty Acid Metabolism Adipogenesis nivo/chemo Peroxisome Bile Acid Metabolism Tumor Xenobiotic Metabolism Pancreas Beta Cells Cholesterol Homeostasis Apical Surface TNF-α Signaling Via NFκB TGF-β Signaling § Sev
Slide 10: Circulating biomarkers of survival following sotiga/chemo
10 Circulating biomarkers of survival following sotiga/chemo Blood § Pretreatment levels of CD4 T cell, B cell, and dendritic cell subsets predict survival benefit n = 13/13 n = 16/12 n = 15/17 § Predictive cell populations reflect the mechanism of action of agonistic CD40 therapy § Biomarkers predi
Slide 11: Tumoral biomarkers of survival following sotiga/chemo
11 Tumoral biomarkers of survival following OS Status sotiga/chemo OS Status < 1 yr. TH2 Response > 1 yr. OS Association Tumor TH1 Response better (pval < 0.05) worse (pval < 0.05) IFN-γ Response worse (0.05 > pval < 0.01) TGF-β Signaling normalized log2 expression −2 −1 0 1 2 Glycolysis § Pretreatm
Slide 12: Biomarkers of survival following sotiga/nivo/chemo
12 Biomarkers of survival following sotiga/nivo/chemo § Few factors in the tumor or circulation predicted survival benefit § Relevant biomarkers from other arms were not predictive of survival benefit § Hyperactivation may be leading to a dysfunctional immune state PRESENTED BY: Lacey J. Padròn, PhD
Slide 13: Conclusions
13 Conclusions § Immuno-pharmacodynamic effects were observed in each arm § Novel circulating and tumoral biomarkers predict overall survival following treatment with nivo/chemo or sotiga/chemo § Prospective studies are warranted to test the validity of blood-based predictive biomarkers of response
Slide 14: Acknowledgments
14 Acknowledgments Patients & their families PICI Central: Sultan Nawabi, Justin Fairchild, Jingying Xu, Joyson Karakunnel, Lisa Butterfield, Ramy Ibrahim, Ute Dugan, Christine Sean Parker Spencer, Mike Travers, Robin Kageyama, Diane Da Silva Lead Study PI: Robert H. Vonderheide Sites: Rosemarie Mic