Abstract CT183: Phase (Ph) I/II study of MBG453± spartalizumab (PDR001) in patients (pts) with advanced malignancies
Bibliographic record
Abstract
Abstract Background: MBG453 and spartalizumab, humanized IgG4 mAbs, block binding of TIM-3 to PtdSer and PD-1 to PD-L1/2, respectively. Preclinical studies show synergistic anti-tumor activity of TIM-3 and PD-1 co-blockade. Here we report the dose escalation results from a Ph I-Ib/II study of MBG453 ± spartalizumab in metastatic solid tumors (NCT02608268). Methods: Metastatic cancer pts received intravenous MBG453 alone at 80-1200 mg Q2W or Q4W, or combination therapy (Q2W/Q4W) with MBG453 (20-800/80-1200 mg) + spartalizumab (80-240 mg/80-400 mg). The recommended Ph II dose (RP2D) was determined using an adaptive Bayesian logistic regression model guided by escalation with overdose control together with Ph I-Ib endpoints (dose-limiting toxicity [DLT] at 8 weeks). Results: As of July 26, 2018, 87 pts received MBG453 alone (14% were anti-PD-1/PD-L1 pre-treated; common tumors [≥9%]: pancreatic cancer [11%], sarcoma [10%], and colorectal cancer [CRC; 9%]) and 86 pts received MBG453 + spartalizumab (27% were anti-PD-1/PD-L1 pre-treated; common tumors [≥6%]: melanoma [8%], NSCLC [7%], CRC [7%], and ovarian cancer [6%]). One DLT (myasthenia gravis grade [G] 4) was reported in a pt with thymoma treated with MBG453 (240 mg Q4W) + spartalizumab (80 mg Q4W). Treatment-related adverse events (AEs) were reported in 40% and 59% of pts treated with MBG453 and MBG453 + spartalizumab, and G3/4 AEs in 0% and 11% of pts; the most common AE (≥10%) was fatigue in 10% and 15% of pts, respectively. MBG453 exposure generally increased in a dose-proportional manner. Maximum tolerated doses were not identified with the tested dose/schedule. MBG453 800 mg Q4W (n=9 pts treated) and MBG453 800 mg + spartalizumab 400 mg Q4W (n=6 pts treated) were declared as RP2Ds. Stable disease (SD) was seen in 25/87 (29%) pts treated with MBG453 alone (common tumors [≥2 pts]: sarcoma [n=5], and breast cancer, CRC, ovarian cancer, cholangiocarcinoma, and NSCLC [n=2 pts each]); 4 of 25 pts with SD were anti-PD-1/PD-L1 pre-treated. Of 86 MBG453 + spartalizumab pts, partial responses were seen in 4 pts (5%); 1 anti-PD-1/PD-L1 pre-treated pt (out of 6 with NSCLC; DOR: 392 d), 3 anti-PD-1/PD-L1 naïve pts (CRC [n=2 out of 6, DOR: 223 d, 109 d]; SCLC [n=1 out of 3; DOR: 112 d]). SD was seen in 34/86 (40%) MBG453 + spartalizumab pts (common tumors [≥3 pts]: melanoma [n=5; 2 cutaneous, 2 uveal, and 1 non-cutaneous], ovarian cancer [n=3], and urothelial carcinoma [n=3]); 10 of 34 pts with SD were anti-PD-1/PD-L1 pre-treated. RNAseq analysis of screening and on-treatment biopsies revealed a pharmacodynamic trend of increased IFN-γ-associated gene signatures following MBG453 + spartalizumab treatment. Conclusions: MBG453 + spartalizumab was well tolerated with preliminary signs of anti-tumor activity. MBG453 800 mg Q4W and MBG453 800 mg + spartalizumab 400 mg Q4W were selected as the RP2Ds; dose expansion is ongoing in pts with melanoma or NSCLC resistant to anti-PD-1/PD-L1. Citation Format: Giuseppe Curigliano, Hans Gelderblom, Nicolas Mach, Toshihiko Doi, Wai Meng David Tai, Patrick Forde, John Sarantopoulos, Philippe L. Bedard, Chia-Chi Lin, Stephen Hodi, Sofie Wilgenhof, Armando Santoro, Catherine Sabatos-Peyton, Tyler Longmire, Kitty Wan, Panagiotis Nikolopoulos, Luigi Manenti, Aung Naing. Phase (Ph) I/II study of MBG453± spartalizumab (PDR001) in patients (pts) with advanced malignancies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr CT183.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".