Traditional in vitro human liver cell culture models lose key hepatic functions such as metabolic activity during short-term culture. Advanced three-dimensional (3D) liver coculture platforms offer the potential for extended hepatocyte functionality and allow for the study of more complex biologic interactions, which can improve and refine human drug safety evaluations. Here, we use a perfusion flow 3D microreactor platform for the coculture of cryopreserved primary human hepatocytes and Kupffer cells to study the regulation of cytochrome P450 3A4 isoform (CYP3A4) activity by chronic interleukin 6 (IL-6)-mediated inflammation over 2 weeks. Hepatocyte cultures remained stable over 2 weeks, with consistent albumin production and basal IL-6 levels. Direct IL-6 stimulation that mimics an inflammatory state induced a dose-dependent suppression of CYP3A4 activity, an increase in C-reactive protein (CRP) secretion, and a decrease in shed soluble interleukin-6 receptor (IL-6R) levels, indicating expected hepatic IL-6 bioactivity. Tocilizumab, an anti-IL-6R monoclonal antibody used to treat rheumatoid arthritis, has been demonstrated clinically to impact small molecule drug pharmacokinetics by modulating cytochrome P450 enzyme activities, an effect not observed in traditional hepatic cultures. We have now recapitulated the clinical observation in a 3D bioreactor system. Tocilizumab was shown to desuppress CYP3A4 activity while reducing the CRP concentration after 72 hours in the continued presence of IL-6. This change in CYP3A4 activity decreased the half-life and area under the curve up to the last measurable concentration (AUC last ) of the small molecule CYP3A4 substrate simvastatin hydroxy acid, measured before and after tocilizumab treatment. We conclude that next-generation in vitro liver culture platforms are well suited for these types of long-term treatment studies and show promise for improved drug safety assessment.

The extent to which immune cell phenotypes in the peripheral blood reflect within-tumor immune activity prior to and early in cancer therapy is unclear. To address this question, we studied the population dynamics of tumor and immune cells, and immune phenotypic changes, using clinical tumor and immune cell measurements and single-cell genomic analyses. These samples were serially obtained from a cohort of advanced gastrointestinal cancer patients enrolled in a trial with chemotherapy and immunotherapy. Using an ecological population model, fitted to clinical tumor burden and immune cell abundance data from each patient, we find evidence of a strong tumor-circulating immune cell interaction in responder patients but not in those patients that progress on treatment. Upon initiation of therapy, immune cell abundance increased rapidly in responsive patients, and once the peak level is reached tumor burden decreases, similar to models of predator–prey interactions; these dynamic patterns were absent in nonresponder patients. To interrogate phenotype dynamics of circulating immune cells, we performed single-cell RNA sequencing at serial time points during treatment. These data show that peripheral immune cell phenotypes were linked to the increased strength of patients’ tumor–immune cell interaction, including increased cytotoxic differentiation and strong activation of interferon signaling in peripheral T cells in responder patients. Joint modeling of clinical and genomic data highlights the interactions between tumor and immune cell populations and reveals how variation in patient responsiveness can be explained by differences in peripheral immune cell signaling and differentiation soon after the initiation of immunotherapy.

Combining cyclin-dependent kinase (CDK) inhibitors with endocrine therapy improves outcomes for metastatic estrogen receptor positive (ER+) breast cancer patients but its value in earlier stage patients is unclear. We examined evolutionary trajectories of early-stage breast cancer tumors, using single cell RNA sequencing (scRNAseq) of serial biopsies from the FELINE clinical trial ( #NCT02712723 ) of endocrine therapy (letrozole) alone or combined with the CDK inhibitor ribociclib. Despite differences in subclonal diversity evolution across patients and treatments, common resistance phenotypes emerged. Resistant tumors treated with combination therapy showed accelerated loss of estrogen signaling with convergent up-regulation of JNK signaling through growth factor receptors. In contrast, cancer cells maintaining estrogen signaling during mono- or combination therapy showed potentiation of CDK4/6 activation and ERK upregulation through ERBB4 signaling. These results indicate that combination therapy in early-stage ER+ breast cancer leads to emergence of resistance through a shift from estrogen to alternative growth signal-mediated proliferation.

Background: CDK4/6 inhibitors such as ribociclib are becoming widely used targeted therapies in hormone-receptor-positive (HR+) human epidermal growth factor receptor 2-negative (HER2−) breast cancer. However, cancers can advance due to drug resistance, a problem in which tumor heterogeneity and evolution are key features. Methods: Ribociclib-resistant HR+/HER2− CAMA-1 breast cancer cells were generated through long-term ribociclib treatment. Characterization of sensitive and resistant cells were performed using RNA sequencing and whole exome sequencing. Lentiviral labeling with different fluorescent proteins enabled us to track the proliferation of sensitive and resistant cells under different treatments in a heterogeneous, 3D spheroid coculture system using imaging microscopy and flow cytometry. Results: Transcriptional profiling of sensitive and resistant cells revealed the downregulation of the G2/M checkpoint in the resistant cells. Exploiting this acquired vulnerability; resistant cells exhibited collateral sensitivity for the Wee-1 inhibitor, adavosertib (AZD1775). The combination of ribociclib and adavosertib achieved additional antiproliferative effect exclusively in the cocultures compared to monocultures, while decreasing the selection for resistant cells. Conclusions: Our results suggest that optimal antiproliferative effects in heterogeneous cancers can be achieved via an integrative therapeutic approach targeting sensitive and resistant cancer cell populations within a tumor, respectively.

The evolution of resistance in high-grade serous ovarian cancer (HGSOC) cells following chemotherapy is only partially understood. To understand the selection of factors driving heterogeneity before and through adaptation to treatment, we profile single-cell RNA-sequencing (scRNA-seq) transcriptomes of HGSOC tumors collected longitudinally during therapy. We analyze scRNA-seq data from two independent patient cohorts to reveal that HGSOC is driven by three archetypal phenotypes, defined as oncogenic states that describe the majority of the transcriptome variation. Using a multi-task learning approach to identify the biological tasks of each archetype, we identify metabolism and proliferation, cellular defense response, and DNA repair signaling as consistent cell states found across patients. Our analysis demonstrates a shift in favor of the metabolism and proliferation archetype versus cellular defense response archetype in cancer cells that received multiple lines of treatment. While archetypes are not consistently associated with specific whole-genome driver mutations, they are closely associated with subclonal populations at the single-cell level, indicating that subclones within a tumor often specialize in unique biological tasks. Our study reveals the core archetypes found in progressive HGSOC and shows consistent enrichment of subclones with the metabolism and proliferation archetype as resistance is acquired to multiple lines of therapy.