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KRAS is the most frequently mutated oncogene in cancer and encodes a key signalling protein in tumours1,2. The KRAS(G12C) mutant has a cysteine residue that has been exploited to design covalent inhibitors that have promising preclinical activity3–5. Here we optimized a series of inhibitors, using novel binding interactions to markedly enhance their potency and selectivity. Our efforts have led to the discovery of AMG 510, which is, to our knowledge, the first KRAS(G12C) inhibitor in clinical development. In preclinical analyses, treatment with AMG 510 led to the regression of KRASG12C tumours and improved the anti-tumour efficacy of chemotherapy and targeted agents. In immune-competent mice, treatment with AMG 510 resulted in a pro-inflammatory tumour microenvironment and produced durable cures alone as well as in combination with immune-checkpoint inhibitors. Cured mice rejected the growth of isogenic KRASG12D tumours, which suggests adaptive immunity against shared antigens. Furthermore, in clinical trials, AMG 510 demonstrated anti-tumour activity in the first dosing cohorts and represents a potentially transformative therapy for patients for whom effective treatments are lacking. Treatment of KRASG12C-mutant cancer cells with the KRAS(G12C) inhibitor AMG 510 leads to durable response in mice, and anti-tumour activity in patients suggests that AMG 510 could be effective in patients for whom treatments are currently lacking.

We propose a framework for integrating optimal power flow (OPF) with state estimation (SE) in the loop for distribution networks. Our approach combines a primal-dual gradient-based OPF solver with a SE feedback loop based on a limited set of sensors for system monitoring, instead of assuming exact knowledge of all states. The estimation algorithm reduces uncertainty on unmeasured grid states based on a few appropriate online state measurements and noisy "pseudo-measurements". We analyze the convergence of the proposed algorithm and quantify the statistical estimation errors based on a weighted least squares (WLS) estimator. The numerical results on a 4521-node network demonstrate that this approach can scale to extremely large networks and provide robustness to both large pseudo measurement variability and inherent sensor measurement noise., Comment: arXiv admin note: text overlap with arXiv:1909.12763

In this paper, we propose a data-based methodology to solve a multi-period stochastic optimal water flow (OWF) problem for water distribution networks (WDNs). The framework explicitly considers the pump schedule and water network head level with limited information of demand forecast errors for an extended period simulation. The objective is to determine the optimal feedback decisions of network-connected components, such as nominal pump schedules and tank head levels and reserve policies, which specify device reactions to forecast errors for accommodation of fluctuating water demand. Instead of assuming the uncertainties across the water network are generated by a prescribed certain distribution, we consider ambiguity sets of distributions centered at an empirical distribution, which is based directly on a finite training data set. We use a distance-based ambiguity set with the Wasserstein metric to quantify the distance between the real unknown data-generating distribution and the empirical distribution. This allows our multi-period OWF framework to trade off system performance and inherent sampling errors in the training dataset. Case studies on a three-tank water distribution network systematically illustrate the tradeoff between pump operational cost, risks of constraint violation, and out-of-sample performance.

KRAS is the most frequently mutated oncogene in cancer and encodes a key signaling protein in tumors. The p.G12C mutation of KRAS is present in approximately 13% of lung adenocarcinoma, 3% of colorectal cancer, and 2% of other solid tumors. Sotorasib (formerly known as AMG 510), the first KRASG12C inhibitor to reach clinical testing in humans, has demonstrated evidence of clinical activity as a single agent in patients with non-small cell lung (NSCLC), colorectal (CRC), endometrial, and appendiceal carcinoma. Preclinically, sotorasib has shown significant tumor growth inhibition as a single agent in multiple CDX and PDX models. The clinically-validated strategy of combining multiple inhibitors in the MAPK pathway suggests that combination strategies could yield even better outcomes for patients. Specifically, the combination of sotorasib and other inhibitors in the MAPK and AKT signaling pathways might further enhance tumor cell killing and overcome potential resistance. To test this hypothesis, in vitro combination experiments were conducted in multiple KRAS p.G12C cell lines with combination matrices of sotorasib and inhibitors of HER kinases, EGFR, SOS1, SHP2, MEK, PI3K, or mTOR, as well as an inhibitor of cyclin-dependent kinases 4 and 6 (CDK4/6). The combination of sotorasib with multiple agents resulted in robust synergistic cell killing of KRAS p.G12C tumor cells in vitro. To understand whether these observations translated in vivo, we assessed combinations of sotorasib with a SHP-2 inhibitor or a HER kinase inhibitor in pharmacodynamic assays and efficacy models in tumor xenografts. Consistent with the synergy observed in vitro, sotorasib in combination with a HER kinase inhibitor (afatinib) or a SHP2 inhibitor (RMC-4550) in vivo resulted in enhanced inhibition of MAPK signaling as measured by p-ERK in NCI-H358 tumors. In efficacy studies using the NCI-H358 xenograft model, significantly enhanced anti-tumor activity was observed with a minimally efficacious dose of sotorasib in combination with afatinib, RMC-4550, or a CDK4/6 inhibitor (palbociclib). Furthermore, enhanced anti-tumor activity was observed with sotorasib in combination with a MEK inhibitor or with the anti-EGFR monoclonal antibody panitumumab in a CRC KRAS p.G12C PDX model. Taken together, these data support the clinical evaluation of combination treatment of sotorasib with analogous agents in patients with KRAS p.G12C tumors. Citation Format: Karen Rex, Anne Y. Saiki, Tyler Holt, Alla Verlinsky, Patricia L. McElroy, Tao Osgood, Ji-Rong Sun, Marwan G. Fakih, Upendra P. Dahal, Bernd Bruenner, Victor J. Cee, Brian A. Lanman, Jude Canon, J. Russell Lipford. Combination of the KRASG12C inhibitor sotorasib with targeted agents improves anti-tumor efficacy in KRAS p.G12C cancer models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1057.

Somatic activating mutations of RAS family members are tumor driver mutations found in an estimated 21% of all cancers. Oncogenic KRAS mutations at residues G12, G13, and Q61 represent the most common RAS mutations found in solid malignancies. The prevalence of KRAS p.G12C tumors is ~13% of lung adenocarcinoma (including NSCLC), 3% of colorectal carcinoma (CRC), and 1% to 2% of numerous other solid tumors, representing an unmet medical need. We have developed AMG 510, an orally bioavailable, covalent inhibitor of KRASG12C with potent biochemical and cellular activity, and robust in vivo efficacy. AMG 510 inhibited SOS-catalyzed nucleotide exchange of recombinant mutant KRASG12C/C118A but had minimal effect on KRASC118A, which is wildtype at position 12. In cellular assays, AMG 510 covalently modified KRASG12C and inhibited KRASG12C signaling as measured by phosphorylation of ERK1/2 (p-ERK) in all KRAS p.G12C-mutant cell lines tested but did not inhibit p-ERK in cell lines with various other KRAS mutations. AMG 510 also selectively impaired viability of KRAS p.G12C mutant cell lines but did not affect cell lines with other KRAS mutations. In vivo pharmacodynamic assays demonstrated dose- and time-dependent inhibition of KRASG12Csignaling in human pancreatic and NSCLC tumor xenografts. Covalent modification of KRASG12C by AMG 510 was measured by mass spectrometry and correlated with p-ERK inhibition in tumors. AMG 510 significantly inhibited the growth of KRAS p.G12C xenografts and resulted in tumor regression. Combination treatment of AMG 510 with standard-of-care and targeted agents demonstrated enhanced tumor growth inhibition compared to either single agent. In a syngeneic model of KRAS p.G12C mutant cancer, AMG 510 treatment significantly inhibited tumor growth and caused regression. AMG 510 is currently in Phase 1, first-in-human clinical trials for patients with advanced solid tumors harboring a KRAS p.G12C mutation. Citation Format: Karen Rex, Anne Y. Saiki, Ji-Rong Sun, Tyler Holt, Neelima Koppada, Brian A. Lanman, Laurie P. Volak, Robert S. Foti, Victor J. Cee, J. Russell Lipford, Jude Canon. In vivo characterization of AMG 510 - a potent and selective KRASG12Ccovalent small molecule inhibitor in preclinical KRASG12Ccancer models [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 3090.