Cancer organoids to model therapy response: Cancer organoids are miniature, three-dimensional cell culture models that can be made from primary patient tumors and studied in the laboratory. Vlachogiannis et al. asked whether such “tumor-in-a-dish” approaches can be used to predict drug responses in the clinic. They generated a live organoid biobank from patients with metastatic gastrointestinal cancer who had previously been enrolled in phase I or II clinical trials. This allowed the authors to compare organoid drug responses with how the patient actually responded in the clinic. Encouragingly, the organoids had similar molecular profiles to those of the patient tumor, reinforcing their value as a platform for drug screening and development. Science , this issue p. 920

Sequential profiling of plasma cell-free DNA (cfDNA) holds immense promise for early detection of patient progression. However, how to exploit the predictive power of cfDNA as a liquid biopsy in the clinic remains unclear. RAS pathway aberrations can be tracked in cfDNA to monitor resistance to anti-EGFR monoclonal antibodies in patients with metastatic colorectal cancer. In this prospective phase II clinical trial of single-agent cetuximab in RAS wild-type patients, we combine genomic profiling of serial cfDNA and matched sequential tissue biopsies with imaging and mathematical modeling of cancer evolution. We show that a significant proportion of patients defined as RAS wild-type based on diagnostic tissue analysis harbor aberrations in the RAS pathway in pretreatment cfDNA and, in fact, do not benefit from EGFR inhibition. We demonstrate that primary and acquired resistance to cetuximab are often of polyclonal nature, and these dynamics can be observed in tissue and plasma. Furthermore, evolutionary modeling combined with frequent serial sampling of cfDNA allows prediction of the expected time to treatment failure in individual patients. This study demonstrates how integrating frequently sampled longitudinal liquid biopsies with a mathematical framework of tumor evolution allows individualized quantitative forecasting of progression, providing novel opportunities for adaptive personalized therapies. Significance: Liquid biopsies capture spatial and temporal heterogeneity underpinning resistance to anti-EGFR monoclonal antibodies in colorectal cancer. Dense serial sampling is needed to predict the time to treatment failure and generate a window of opportunity for intervention. Cancer Discov; 8(10); 1270–85. ©2018 AACR. See related commentary by Siravegna and Corcoran, p. 1213. This article is highlighted in the In This Issue feature, p. 1195

Drug resistance mediated by clonal evolution is arguably the biggest problem in cancer therapy today. However, evolving resistance to one drug may come at a cost of decreased fecundity or increased sensitivity to another drug. These evolutionary trade-offs can be exploited using ‘evolutionary steering’ to control the tumour population and delay resistance. However, recapitulating cancer evolutionary dynamics experimentally remains challenging. Here, we present an approach for evolutionary steering based on a combination of single-cell barcoding, large populations of 10⁸–10⁹ cells grown without re-plating, longitudinal non-destructive monitoring of cancer clones, and mathematical modelling of tumour evolution. We demonstrate evolutionary steering in a lung cancer model, showing that it shifts the clonal composition of the tumour in our favour, leading to collateral sensitivity and proliferative costs. Genomic profiling revealed some of the mechanisms that drive evolved sensitivity. This approach allows modelling evolutionary steering strategies that can potentially control treatment resistance.

Background & Aims Cholangiocarcinomas (CCA) are resistant to chemotherapy, so new therapeutic agents are needed. We performed a screen to identify small-molecule compounds that are active against CCAs. Levels of microRNA 21 (MIR21 or miRNA21) are increased in CCAs. We investigated whether miRNA21 mediates resistance of CCA cells and organoids to HSP90 inhibitors. Methods We performed a high-throughput screen of 484 small-molecule compounds to identify those that reduced viability of 6 human CCA cell lines. We tested the effects of HSP90 inhibitors on cells with disruption of the MIR21 gene, cells incubated with MIR21 inhibitors, and stable cell lines with inducible expression of MIR21. We obtained CCA biopsies from patients, cultured them as organoids (patient-derived organoids). We assessed their architecture, mutation and gene expression patterns, response to compounds in culture, and when grown as subcutaneous xenograft tumors in mice. Results Cells with IDH1 and PBRM1 mutations had the highest level of sensitivity to histone deacetylase inhibitors. HSP90 inhibitors were effective in all cell lines, irrespective of mutations. Sensitivity of cells to HSP90 inhibitors correlated inversely with baseline level of MIR21. Disruption of MIR21 increased cell sensitivity to HSP90 inhibitors. CCA cells that expressed transgenic MIR21 were more resistant to HSP90 inhibitors than cells transfected with control vectors; inactivation of MIR21 in these cells restored sensitivity to these agents. MIR21 was shown to target the DnaJ heat shock protein family (Hsp40) member B5 (DNAJB5). Transgenic expression of DNAJB5 in CCA cells that overexpressed MIR21 re-sensitized them to HSP90 inhibitors. Sensitivity of patient-derived organoids to HSP90 inhibitors, in culture and when grown as xenograft tumors in mice, depended on expression of miRNA21. Conclusions miRNA21 appears to mediate resistance of CCA cells to HSP90 inhibitors by reducing levels of DNAJB5. HSP90 inhibitors might be developed for the treatment of CCA and miRNA21 might be a marker of sensitivity to these agents.

Both normal tissue development and cancer growth are driven by a branching process of cell division and mutation accumulation that leads to intra-tissue genetic heterogeneity. However, quantifying somatic evolution in humans remains challenging. Here, we show that multi-sample genomic data from a single time point of normal and cancer tissues contains information on single-cell divisions. We present a new theoretical framework that, applied to whole-genome sequencing data of healthy tissue and cancer, allows inferring the mutation rate and the cell survival/death rate per division. On average, we found that cells accumulate 1.14 mutations per cell division in healthy haematopoiesis and 1.37 mutations per division in brain development. In both tissues, cell survival was maximal during early development. Analysis of 131 biopsies from 16 tumours showed 4 to 100 times increased mutation rates compared to healthy development and substantial inter-patient variation of cell survival/death rates.

The dominant mutational signature in colorectal cancer genomes is C > T deamination (COSMIC Signature 1) and, in a small subgroup, mismatch repair signature (COSMIC signatures 6 and 44). Mutations in common colorectal cancer driver genes are often not consistent with those signatures. Here we perform whole-genome sequencing of normal colon crypts from cancer patients, matched to a previous multi-omic tumour dataset. We analyse normal crypts that were distant vs adjacent to the cancer. In contrast to healthy individuals, normal crypts of colon cancer patients have a high incidence of pks + (polyketide synthases) E.coli (Escherichia coli) mutational and indel signatures, and this is confirmed by metagenomics. These signatures are compatible with many clonal driver mutations detected in the corresponding cancer samples, including in chromatin modifier genes, supporting their role in early tumourigenesis. These results provide evidence that pks + E.coli is a potential driver of carcinogenesis in the human gut.