Large variety in a panel of human colon cancer organoids in response to EZH2 inhibition

EZH2 inhibitors have gained great interest for their use as anti-cancer therapeutics. However, most research has focused on EZH2 mutant cancers and recently adverse effects of EZH2 inactivation have come to light. To determine whether colorectal cancer cells respond to EZH2 inhibition and to explore which factors influence the degree of response, we treated a panel of 20 organoid lines derived from human colon tumors with different concentrations of the EZH2 inhibitor GSK126. The resulting responses were associated with mutation status, gene expression and responses to other drugs. We found that the response to GSK126 treatment greatly varied between organoid lines. Response associated with the mutation status of ATRX and PAX2, and correlated with BIK expression. It also correlated well with response to Nutlin-3a which inhibits MDM2-p53 interaction thereby activating p53 signaling. Sensitivity to EZH2 ablation depended on the presence of wild type p53, as tumor organoids became resistant when p53 was mutated or knocked down. Our exploratory study provides insight into which genetic factors predict sensitivity to EZH2 inhibition. In addition, we show that the response to EZH2 inhibition requires wild type p53. We conclude that a subset of colorectal cancer patients may benefit from EZH2-targeting therapies

Inferring single-cell protein levels and cell cycle behavior in heterogeneous cell populations

Individual cells in a genetically identical population can show highly variable behavior. Single-cell measurements allow us to study this variability, but the available measurement techniques have limitations: live-cell microscopy is typically restricted to one or a few molecular markers, while techniques that simultaneously measure large numbers of molecular markers are destructive and cannot be used to follow cells over time. To help overcome these limitations, we present here scMeMo (single cell Mechanistic Modeler): a mechanistic modeling framework that can leverage diverse sets of measurements in order to infer unobserved variables in heterogeneous single cells. We used this framework to construct a model describing cell cycle progression in human cells, and show that it can predict the levels of several proteins in individual cells, based on live-cell microscopy measurements of only one marker and information learned from other experiments. The framework incorporates an uncertainty calibration step that makes the posterior distributions robust against partial model misspecification. Our modeling framework can be used to integrate information from separate experiments with diverse readouts, and to infer single cell variables that may be difficult to measure directly

Intrinsic Resistance to MEK Inhibition in KRAS Mutant Lung and Colon Cancer through Transcriptional Induction of ERBB3

Summary There are no effective therapies for the ∼30% of human malignancies with mutant RAS oncogenes. Using a kinome-centered synthetic lethality screen, we find that suppression of the ERBB3 receptor tyrosine kinase sensitizes KRAS mutant lung and colon cancer cells to MEK inhibitors. We show that MEK inhibition results in MYC-dependent transcriptional upregulation of ERBB3, which is responsible for intrinsic drug resistance. Drugs targeting both EGFR and ERBB2, each capable of forming heterodimers with ERBB3, can reverse unresponsiveness to MEK inhibition by decreasing inhibitory phosphorylation of the proapoptotic proteins BAD and BIM. Moreover, ERBB3 protein level is a biomarker of response to combinatorial treatment. These data suggest a combination strategy for treating KRAS mutant colon and lung cancers and a way to identify the tumors that are most likely to benefit from such combinatorial treatment

Loss of p53 triggers Wnt-dependent systemic inflammation to drive breast cancer metastasis

Cancer-associated systemic inflammation is strongly linked to poor disease outcome in patients with cancer1,2. For most human epithelial tumour types, high systemic neutrophil-to-lymphocyte ratios are associated with poor overall survival3, and experimental studies have demonstrated a causal relationship between neutrophils and metastasis4,5. However, the cancer-cell-intrinsic mechanisms that dictate the substantial heterogeneity in systemic neutrophilic inflammation between tumour-bearing hosts are largely unresolved. Here, using a panel of 16 distinct genetically engineered mouse models for breast cancer, we uncover a role for cancer-cell-intrinsic p53 as a key regulator of pro-metastatic neutrophils. Mechanistically, loss of p53 in cancer cells induced the secretion of WNT ligands that stimulate tumour-associated macrophages to produce IL-1β, thus driving systemic inflammation. Pharmacological and genetic blockade of WNT secretion in p53-null cancer cells reverses macrophage production of IL-1β and subsequent neutrophilic inflammation, resulting in reduced metastasis formation. Collectively, we demonstrate a mechanistic link between the loss of p53 in cancer cells, secretion of WNT ligands and systemic neutrophilia that potentiates metastatic progression. These insights illustrate the importance of the genetic makeup of breast tumours in dictating pro-metastatic systemic inflammation, and set the stage for personalized immune intervention strategies for patients with cancer

Loss of p53 triggers Wnt-dependent systemic inflammation to drive breast cancer metastasis

Cancer-associated systemic inflammation is strongly linked to poor disease outcome in patients with cancer1,2. For most human epithelial tumour types, high systemic neutrophil-to-lymphocyte ratios are associated with poor overall survival3, and experimental studies have demonstrated a causal relationship between neutrophils and metastasis4,5. However, the cancer-cell-intrinsic mechanisms that dictate the substantial heterogeneity in systemic neutrophilic inflammation between tumour-bearing hosts are largely unresolved. Here, using a panel of 16 distinct genetically engineered mouse models for breast cancer, we uncover a role for cancer-cell-intrinsic p53 as a key regulator of pro-metastatic neutrophils. Mechanistically, loss of p53 in cancer cells induced the secretion of WNT ligands that stimulate tumour-associated macrophages to produce IL-1β, thus driving systemic inflammation. Pharmacological and genetic blockade of WNT secretion in p53-null cancer cells reverses macrophage production of IL-1β and subsequent neutrophilic inflammation, resulting in reduced metastasis formation. Collectively, we demonstrate a mechanistic link between the loss of p53 in cancer cells, secretion of WNT ligands and systemic neutrophilia that potentiates metastatic progression. These insights illustrate the importance of the genetic makeup of breast tumours in dictating pro-metastatic systemic inflammation, and set the stage for personalized immune intervention strategies for patients with cancer

Fanconi anemia and homologous recombination gene variants are associated with functional DNA repair defects in vitro and poor outcome in patients with advanced head and neck squamous cell carcinoma

Mutations in Fanconi Anemia or Homologous Recombination (FA/HR) genes can cause DNA repair defects and could therefore impact cancer treatment response and patient outcome. Their functional impact and clinical relevance in head and neck squamous cell carcinoma (HNSCC) is unknown. We therefore questioned whether functional FA/HR defects occurred in HNSCC and whether they are associated with FA/HR variants. We assayed a panel of 29 patient-derived HNSCC cell lines and found that a considerable fraction is hypersensitive to the crosslinker Mitomycin C and PARP inhibitors, a functional measure of FA/HR defects. DNA sequencing showed that these hypersensitivities are associated with the presence of bi-allelic rare germline and somatic FA/HR gene variants. We next questioned whether such variants are associated with prognosis and treatment response in HNSCC patients. DNA sequencing of 77 advanced stage HNSCC tumors revealed a 19% incidence of such variants. Importantly, these variants were associated with a poor prognosis (p = 0.027; HR = 2.6, 1.1–6.0) but favorable response to high cumulative cisplatin dose. We show how an integrated in vitro functional repair and genomic analysis can improve the prognostic value of genetic biomarkers. We conclude that repair defects are marked and frequent in HNSCC and are associated with clinical outcome.</p

Microcalcification crystallography as a potential marker of DCIS recurrence

Ductal carcinoma in-situ (DCIS) accounts for 20-25% of all new breast cancer diagnoses. DCIS has an uncertain risk of progression to invasive breast cancer and a lack of predictive biomarkers may result in relatively high levels (~ 75%) of overtreatment. To identify unique prognostic biomarkers of invasive progression, crystallographic and chemical features of DCIS microcalcifications have been explored. Samples from patients with at least 5-years of follow up and no known recurrence (174 calcifications in 67 patients) or ipsilateral invasive breast cancer recurrence (179 microcalcifications in 57 patients) were studied. Significant differences were noted between the two groups including whitlockite relative mass, hydroxyapatite and whitlockite crystal maturity and, elementally, sodium to calcium ion ratio. A preliminary predictive model for DCIS to invasive cancer progression was developed from these parameters with an AUC of 0.797. These results provide insights into the differing DCIS tissue microenvironments, and how these impact microcalcification formation. [Abstract copyright: © 2023. The Author(s).

Identifying mutant-specific multi-drug combinations using comparative network reconstruction

Targeted inhibition of aberrant signaling is an important treatment strategy in cancer, but responses are often short-lived. Multi-drug combinations have the potential to mitigate this, but to avoid toxicity such combinations must be selective and given at low dosages. Here, we present a pipeline to identify promising multi-drug combinations. We perturbed an isogenic PI3K mutant and wild-type cell line pair with a limited set of drugs and recorded their signaling state and cell viability. We then reconstructed their signaling networks and mapped the signaling response to changes in cell viability. The resulting models, which allowed us to predict the effect of unseen combinations, indicated that no combination selectively reduces the viability of the PI3K mutant cells. However, we were able to validate 25 of the 30 combinations that we predicted to be anti-selective. Our pipeline enables efficient prioritization of multi-drug combinations from the enormous search space of possible combinations