Microenvironment drives cell state, plasticity, and drug response in pancreatic cancer.

Prognostically relevant RNA expression states exist in pancreatic ductal adenocarcinoma (PDAC), but our understanding of their drivers, stability, and relationship to therapeutic response is limited. To examine these attributes systematically, we profiled metastatic biopsies and matched organoid models at single-cell resolution. In vivo, we identify a new intermediate PDAC transcriptional cell state and uncover distinct site- and state-specific tumor microenvironments (TMEs). Benchmarking models against this reference map, we reveal strong culture-specific biases in cancer cell transcriptional state representation driven by altered TME signals. We restore expression state heterogeneity by adding back in vivo-relevant factors and show plasticity in culture models. Further, we prove that non-genetic modulation of cell state can strongly influence drug responses, uncovering state-specific vulnerabilities. This work provides a broadly applicable framework for aligning cell states across in vivo and ex vivo settings, identifying drivers of transcriptional plasticity and manipulating cell state to target associated vulnerabilities.

WRN helicase is a synthetic lethal target in microsatellite unstable cancers.

Synthetic lethality-an interaction between two genetic events through which the co-occurrence of these two genetic events leads to cell death, but each event alone does not-can be exploited for cancer therapeutics1. DNA repair processes represent attractive synthetic lethal targets, because many cancers exhibit an impairment of a DNA repair pathway, which can lead to dependence on specific repair proteins2. The success of poly(ADP-ribose) polymerase 1 (PARP-1) inhibitors in cancers with deficiencies in homologous recombination highlights the potential of this approach3. Hypothesizing that other DNA repair defects would give rise to synthetic lethal relationships, we queried dependencies in cancers with microsatellite instability (MSI), which results from deficient DNA mismatch repair. Here we analysed data from large-scale silencing screens using CRISPR-Cas9-mediated knockout and RNA interference, and found that the RecQ DNA helicase WRN was selectively essential in MSI models in vitro and in vivo, yet dispensable in models of cancers that are microsatellite stable. Depletion of WRN induced double-stranded DNA breaks and promoted apoptosis and cell cycle arrest selectively in MSI models. MSI cancer models required the helicase activity of WRN, but not its exonuclease activity. These findings show that WRN is a synthetic lethal vulnerability and promising drug target for MSI cancers.

DeepComBat: A statistically motivated, hyperparameter-robust, deep learning approach to harmonization of neuroimaging data.

Neuroimaging data acquired using multiple scanners or protocols are increasingly available. However, such data exhibit technical artifacts across batches which introduce confounding and decrease reproducibility. This is especially true when multi-batch data are analyzed using complex downstream models which are more likely to pick up on and implicitly incorporate batch-related information. Previously proposed image harmonization methods have sought to remove these batch effects; however, batch effects remain detectable in the data after applying these methods. We present DeepComBat, a deep learning harmonization method based on a conditional variational autoencoder and the ComBat method. DeepComBat combines the strengths of statistical and deep learning methods in order to account for the multivariate relationships between features while simultaneously relaxing strong assumptions made by previous deep learning harmonization methods. As a result, DeepComBat can perform multivariate harmonization while preserving data structure and avoiding the introduction of synthetic artifacts. We apply this method to cortical thickness measurements from a cognitive-aging cohort and show DeepComBat qualitatively and quantitatively outperforms existing methods in removing batch effects while preserving biological heterogeneity. Additionally, DeepComBat provides a new perspective for statistically motivated deep learning harmonization methods.

Discovery of a selective inhibitor of doublecortin like kinase 1.

Doublecortin like kinase 1 (DCLK1) is an understudied kinase that is upregulated in a wide range of cancers, including pancreatic ductal adenocarcinoma (PDAC). However, little is known about its potential as a therapeutic target. We used chemoproteomic profiling and structure-based design to develop a selective, in vivo-compatible chemical probe of the DCLK1 kinase domain, DCLK1-IN-1. We demonstrate activity of DCLK1-IN-1 against clinically relevant patient-derived PDAC organoid models and use a combination of RNA-sequencing, proteomics and phosphoproteomics analysis to reveal that DCLK1 inhibition modulates proteins and pathways associated with cell motility in this context. DCLK1-IN-1 will serve as a versatile tool to investigate DCLK1 biology and establish its role in cancer.

Isoform-selective inhibitor of histone deacetylase 3 (HDAC3) limits pancreatic islet infiltration and protects female nonobese diabetic mice from diabetes.

Preservation of insulin-secreting ß-cells is an important goal for therapies aimed at restoring normoglycemia in patients with diabetes. One approach, the inhibition of histone deacetylases (HDACs), has been reported to suppress pancreatic islet inflammation and ß-cell apoptosis in vitro In this report, we demonstrate the efficacy of HDAC inhibitors (HDACi) in vivo We show that daily administration of BRD3308, an isoform-selective HDAC3 inhibitor, for 2 weeks to female nonobese diabetic (NOD) mice, beginning at 3 weeks of age, followed by twice-weekly injections until age 25 weeks, protects the animals from diabetes. The preservation of ß-cells was because of a significant decrease in islet infiltration of mononuclear cells. Moreover, the BRD3308 treatment increased basal insulin secretion from islets cultured in vitro All metabolic tissues tested in vehicle- or BRD3308-treated groups showed virtually no sign of immune cell infiltration, except minimal infiltration in white adipose tissue in animals treated with the highest BRD3308 dose (10 mg/kg), providing additional evidence of protection from immune attack in the treated groups. Furthermore, pancreata from animals treated with 10 mg/kg BRD3308 exhibited significantly decreased numbers of apoptotic ß-cells compared with those treated with vehicle or low-dose BRD3308. Finally, animals treated with 1 or 10 mg/kg BRD3308 had enhanced ß-cell proliferation. These in vivo results point to the potential use of selective HDAC3 inhibitors as a therapeutic approach to suppress pancreatic islet infiltration and prevent ß-cell death with the long-term goal of limiting the progression of type 1 diabetes.

DeepComBat: A Statistically Motivated, Hyperparameter-Robust, Deep Learning Approach to Harmonization of Neuroimaging Data.

Neuroimaging data from multiple batches (i.e. acquisition sites, scanner manufacturer, datasets, etc.) are increasingly necessary to gain new insights into the human brain. However, multi-batch data, as well as extracted radiomic features, exhibit pronounced technical artifacts across batches. These batch effects introduce confounding into the data and can obscure biological effects of interest, decreasing the generalizability and reproducibility of findings. This is especially true when multi-batch data is used alongside complex downstream analysis models, such as machine learning methods. Image harmonization methods seeking to remove these batch effects are important for mitigating these issues; however, significant multivariate batch effects remain in the data following harmonization by current state-of-the-art statistical and deep learning methods. We present DeepCombat, a deep learning harmonization method based on a conditional variational autoencoder architecture and the ComBat harmonization model. DeepCombat learns and removes subject-level batch effects by accounting for the multivariate relationships between features. Additionally, DeepComBat relaxes a number of strong assumptions commonly made by previous deep learning harmonization methods and is empirically robust across a wide range of hyperparameter choices. We apply this method to neuroimaging data from a large cognitive-aging cohort and find that DeepCombat outperforms existing methods, as assessed by a battery of machine learning methods, in removing scanner effects from cortical thickness measurements while preserving biological heterogeneity. Additionally, DeepComBat provides a new perspective for statistically-motivated deep learning harmonization methods.

Atypical KRASG12R Mutant Is Impaired in PI3K Signaling and Macropinocytosis in Pancreatic Cancer.

Allele-specific signaling by different KRAS alleles remains poorly understood. The KRAS G12R mutation displays uneven prevalence among cancers that harbor the highest occurrence of KRAS mutations: It is rare (∼1%) in lung and colorectal cancers, yet relatively common (∼20%) in pancreatic ductal adenocarcinoma (PDAC), suggesting context-specific properties. We evaluated whether KRASG12R is functionally distinct from the more common KRASG12D- or KRASG12V-mutant proteins (KRASG12D/V). We found that KRASG12D/V but not KRASG12R drives macropinocytosis and that MYC is essential for macropinocytosis in KRASG12D/V- but not KRASG12R-mutant PDAC. Surprisingly, we found that KRASG12R is defective for interaction with a key effector, p110α PI3K (PI3Kα), due to structural perturbations in switch II. Instead, upregulated KRAS-independent PI3Kγ activity was able to support macropinocytosis in KRASG12R-mutant PDAC. Finally, we determined that KRASG12R-mutant PDAC displayed a distinct drug sensitivity profile compared with KRASG12D-mutant PDAC but is still responsive to the combined inhibition of ERK and autophagy. SIGNIFICANCE: We determined that KRASG12R is impaired in activating a key effector, p110α PI3K. As such, KRASG12R is impaired in driving macropinocytosis. However, overexpression of PI3Kγ in PDAC compensates for this deficiency, providing one basis for the prevalence of this otherwise rare KRAS mutant in pancreatic cancer but not other cancers.See related commentary by Falcomatà et al., p. 23.This article is highlighted in the In This Issue feature, p. 1.

Increased ß-cell proliferation before immune cell invasion prevents progression of type 1 diabetes.

Type 1 diabetes (T1D) is characterized by pancreatic islet infiltration by autoreactive immune cells and a near-total loss of ß-cells1. Restoration of insulin-producing ß-cells coupled with immunomodulation to suppress the autoimmune attack has emerged as a potential approach to counter T1D2-4. Here we report that enhancing ß-cell mass early in life, in two models of female NOD mice, results in immunomodulation of T-cells, reduced islet infiltration and lower ß-cell apoptosis, that together protect them from developing T1D. The animals displayed altered ß-cell antigens, and islet transplantation studies showed prolonged graft survival in the NOD-LIRKO model. Adoptive transfer of splenocytes from the NOD-LIRKOs prevented development of diabetes in pre-diabetic NOD mice. A significant increase in the splenic CD4+CD25+FoxP3+ regulatory T-cell (Treg) population was observed to underlie the protected phenotype since Treg depletion rendered NOD-LIRKO mice diabetic. The increase in Tregs coupled with activation of TGF-ß/SMAD3 signaling pathway in pathogenic T-cells favored reduced ability to kill ß-cells. These data support a previously unidentified observation that initiating ß-cell proliferation, alone, prior to islet infiltration by immune cells alters the identity of ß-cells, decreases pathologic self-reactivity of effector cells and increases Tregs to prevent progression of T1D.

Synthetic Lethal Interaction of SHOC2 Depletion with MEK Inhibition in RAS-Driven Cancers.

The mitogen-activated protein kinase (MAPK) pathway is a critical effector of oncogenic RAS signaling, and MAPK pathway inhibition may be an effective combination treatment strategy. We performed genome-scale loss-of-function CRISPR-Cas9 screens in the presence of a MEK1/2 inhibitor (MEKi) in KRAS-mutant pancreatic and lung cancer cell lines and identified genes that cooperate with MEK inhibition. While we observed heterogeneity in genetic modifiers of MEKi sensitivity across cell lines, several recurrent classes of synthetic lethal vulnerabilities emerged at the pathway level. Multiple members of receptor tyrosine kinase (RTK)-RAS-MAPK pathways scored as sensitizers to MEKi. In particular, we demonstrate that knockout, suppression, or degradation of SHOC2, a positive regulator of MAPK signaling, specifically cooperated with MEK inhibition to impair proliferation in RAS-driven cancer cells. The depletion of SHOC2 disrupted survival pathways triggered by feedback RTK signaling in response to MEK inhibition. Thus, these findings nominate SHOC2 as a potential target for combination therapy.

TAS-120 Overcomes Resistance to ATP-Competitive FGFR Inhibitors in Patients with FGFR2 Fusion-Positive Intrahepatic Cholangiocarcinoma.

ATP-competitive fibroblast growth factor receptor (FGFR) kinase inhibitors, including BGJ398 and Debio 1347, show antitumor activity in patients with intrahepatic cholangiocarcinoma (ICC) harboring activating FGFR2 gene fusions. Unfortunately, acquired resistance develops and is often associated with the emergence of secondary FGFR2 kinase domain mutations. Here, we report that the irreversible pan-FGFR inhibitor TAS-120 demonstrated efficacy in 4 patients with FGFR2 fusion-positive ICC who developed resistance to BGJ398 or Debio 1347. Examination of serial biopsies, circulating tumor DNA (ctDNA), and patient-derived ICC cells revealed that TAS-120 was active against multiple FGFR2 mutations conferring resistance to BGJ398 or Debio 1347. Functional assessment and modeling the clonal outgrowth of individual resistance mutations from polyclonal cell pools mirrored the resistance profiles observed clinically for each inhibitor. Our findings suggest that strategic sequencing of FGFR inhibitors, guided by serial biopsy and ctDNA analysis, may prolong the duration of benefit from FGFR inhibition in patients with FGFR2 fusion-positive ICC. SIGNIFICANCE: ATP-competitive FGFR inhibitors (BGJ398, Debio 1347) show efficacy in FGFR2-altered ICC; however, acquired FGFR2 kinase domain mutations cause drug resistance and tumor progression. We demonstrate that the irreversible FGFR inhibitor TAS-120 provides clinical benefit in patients with resistance to BGJ398 or Debio 1347 and overcomes several FGFR2 mutations in ICC models.This article is highlighted in the In This Issue feature, p. 983.