Profiling candidate therapeutics with limited cancer models during preclinical development hinders predictions of clinical efficacy and identifying factors that underlie heterogeneous patient responses for patient-selection strategies. We established ∼1,000 patient-derived tumor xenograft models (PDXs) with a diverse set of driver mutations. With these PDXs, we performed in vivo compound screens using a 1 × 1 × 1 experimental design (PDX clinical trial or PCT) to assess the population responses to 62 treatments across six indications. We demonstrate both the reproducibility and the clinical translatability of this approach by identifying associations between a genotype and drug response, and established mechanisms of resistance. In addition, our results suggest that PCTs may represent a more accurate approach than cell line models for assessing the clinical potential of some therapeutic modalities. We therefore propose that this experimental paradigm could potentially improve preclinical evaluation of treatment modalities and enhance our ability to predict clinical trial responses.

FGFR1 was recently shown to be activated as part of a compensatory response to prolonged treatment with the MEK inhibitor trametinib in several KRAS-mutant lung and pancreatic cancer cell lines. We hypothesize that other receptor tyrosine kinases (RTK) are also feedback-activated in this context. Herein, we profile a large panel of KRAS-mutant cancer cell lines for the contribution of RTKs to the feedback activation of phospho-MEK following MEK inhibition, using an SHP2 inhibitor (SHP099) that blocks RAS activation mediated by multiple RTKs. We find that RTK-driven feedback activation widely exists in KRAS-mutant cancer cells, to a less extent in those harboring the G13D variant, and involves several RTKs, including EGFR, FGFR, and MET. We further demonstrate that this pathway feedback activation is mediated through mutant KRAS, at least for the G12C, G12D, and G12V variants, and wild-type KRAS can also contribute significantly to the feedback activation. Finally, SHP099 and MEK inhibitors exhibit combination benefits inhibiting KRAS-mutant cancer cell proliferation in vitro and in vivo. These findings provide a rationale for exploration of combining SHP2 and MAPK pathway inhibitors for treating KRAS-mutant cancers in the clinic.

SHP2 is a ubiquitous tyrosine phosphatase involved in regulating both tumor and immune cell signaling. In this study, we discovered a novel immune modulatory function of SHP2. Targeting this protein with allosteric SHP2 inhibitors promoted anti-tumor immunity, including enhancing T cell cytotoxic function and immune-mediated tumor regression. Knockout of SHP2 using CRISPR/Cas9 gene editing showed that targeting SHP2 in cancer cells contributes to this immune response. Inhibition of SHP2 activity augmented tumor intrinsic IFNγ signaling resulting in enhanced chemoattractant cytokine release and cytotoxic T cell recruitment, as well as increased expression of MHC Class I and PD-L1 on the cancer cell surface. Furthermore, SHP2 inhibition diminished the differentiation and inhibitory function of immune suppressive myeloid cells in the tumor microenvironment. SHP2 inhibition enhanced responses to anti-PD-1 blockade in syngeneic mouse models. Overall, our study reveals novel functions of SHP2 in tumor immunity and proposes that targeting SHP2 is a promising strategy for cancer immunotherapy.

KRAS, an oncogene mutated in nearly one third of human cancers, remains a pharmacologic challenge for direct inhibition except for recent advances in selective inhibitors targeting the G12C variant. Here, we report that selective inhibition of the protein tyrosine phosphatase, SHP2, can impair the proliferation of KRAS-mutant cancer cells in vitro and in vivo using cell line xenografts and primary human tumors. In vitro, sensitivity of KRAS-mutant cells toward the allosteric SHP2 inhibitor, SHP099, is not apparent when cells are grown on plastic in 2D monolayer, but is revealed when cells are grown as 3D multicellular spheroids. This antitumor activity is also observed in vivo in mouse models. Interrogation of the MAPK pathway in SHP099-treated KRAS-mutant cancer models demonstrated similar modulation of p-ERK and DUSP6 transcripts in 2D, 3D, and in vivo, suggesting a MAPK pathway-dependent mechanism and possible non-MAPK pathway-dependent mechanisms in tumor cells or tumor microenvironment for the in vivo efficacy. For the KRAS G12C MIAPaCa-2 model, we demonstrate that the efficacy is cancer cell intrinsic as there is minimal antiangiogenic activity by SHP099, and the effects of SHP099 is recapitulated by genetic depletion of SHP2 in cancer cells. Furthermore, we demonstrate that SHP099 efficacy in KRAS-mutant models can be recapitulated with RTK inhibitors, suggesting RTK activity is responsible for the SHP2 activation. Taken together, these data reveal that many KRAS-mutant cancers depend on upstream signaling from RTK and SHP2, and provide a new therapeutic framework for treating KRAS-mutant cancers with SHP2 inhibitors.

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The novel coronavirus SARS-CoV-2 that causes the disease COVID-19 has forced us to go into our homes and limit our physical interactions with others. Economies around the world have come to a halt, with non-essential businesses being forced to close in order to prevent further propagation of the virus. Developing countries are having more difficulties due to their lack of access to diagnostic resources. In this study, we present an approach for detecting COVID-19 infections exclusively on the basis of self-reported symptoms. Such an approach is of great interest because it is relatively inexpensive and easy to deploy at either an individual or population scale. Our best model delivers a sensitivity score of 0.752, a specificity score of 0.609, and an area under the curve for the receiver operating characteristic of 0.728. These are promising results that justify continuing research efforts towards a machine learning test for detecting COVID-19.

Advanced ovarian cancers are a leading cause of cancer-related death in women. Such cancers are currently treated with surgery and chemotherapy which is often temporarily successful but exhibits a high rate of relapse after which treatment options are few. Here we assess the responses of a panel of patient-derived ovarian cancer xenografts (PDXs) to 19 mono and combination therapies, including small molecules and antibody-drug conjugates. The PDX panel aimed to mimic the heterogeneity of disease observed in patients, and exhibited a distribution of responsiveness to standard of care chemotherapy similar to human clinical data. Three monotherapies and one drug combination were found to be active in different subsets of PDXs. By analyzing gene expression data we identified gene expression biomarkers predictive of responsiveness to each of three novel targeted therapy regimens.While no single treatment had as high a response rate as chemotherapy, nearly 90% of PDXs were eligible for and responded to at least one biomarker-guided treatment, including tumors resistant to standard chemotherapy. Biomarker frequency was similar in human patients, suggesting the possibility of a new therapeutic approach to ovarian cancer and demonstrating the potential power of PDX-based trials in broadening the reach of precision cancer medicine..