From February 7–11, 2011, the multidisciplinary Lorentz Workshop Circulating Tumor Cell (CTC) Isolation and Diagnostics: Toward Routine Clinical Use was held in Leiden (The Netherlands) to discuss progress and define challenges and potential solutions for development of clinically useful circulating tumor cell (CTC) diagnostics. CTCs, captured as “liquid biopsy” from blood, for counting and characterization using pathology and molecular assays, are expected to replace metastatic tissue biopsies to be used to predict drug response and resistance and to monitor therapy response and cancer recurrence. CTCs are highly heterogeneous; therefore, cancer type–specific isolation technologies, as well as complex clinical interpretation software, are required. Cancer Res; 71(18); 5955–60. ©2011 AACR.

The concept of “Organs-on-Chips” has recently evolved and has been described as 3D (mini-) organs or tissues consisting of multiple and different cell types interacting with each other under closely controlled conditions, grown in a microfluidic chip, and mimicking the complex structures and cellular interactions in and between different cell types and organs in vivo, enabling the real time monitoring of cellular processes. In combination with the emerging iPSC (induced pluripotent stem cell) field this development offers unprecedented opportunities to develop human in vitro models for healthy and diseased organ tissues, enabling the investigation of fundamental mechanisms in disease development, drug toxicity screening, drug target discovery and drug development, and the replacement of animal testing. Capturing the genetic background of the iPSC donor in the organ or disease model carries the promise to move towards “in vitro clinical trials”, reducing costs for drug development and furthering the concept of personalized medicine and companion diagnostics. During the Lorentz workshop (Leiden, September 2012) an international multidisciplinary group of experts discussed the current state of the art, available and emerging technologies, applications and how to proceed in the field. Organ-on-a-chip platform technologies are expected to revolutionize cell biology in general and drug development in particular.

The idea of artificial intelligence (AI) has a long history. It turned out, however, that reaching intelligence at human levels is more complicated than originally anticipated. Currently, we are experiencing a renewed interest in AI, fueled by an enormous increase in computing power and an even larger increase in data, in combination with improved AI technologies like deep learning. Healthcare is considered the next domain to be revolutionized by artificial intelligence. While AI approaches are excellently suited to develop certain algorithms, for biomedical applications there are specific challenges. We propose six recommendations—the 6Rs—to improve AI projects in the biomedical space, especially clinical health care, and to facilitate communication between AI scientists and medical doctors: (1) Relevant and well-defined clinical question first; (2) Right data (ie, representative and of good quality); (3) Ratio between number of patients and their variables should fit the AI method; (4) Relationship between data and ground truth should be as direct and causal as possible; (5) Regulatory ready; enabling validation; and (6) Right AI method.

Signal transduction pathways are important in physiology and pathophysiology. Targeted drugs aim at modifying pathogenic pathway activity, e.g., in cancer. Optimal treatment choice requires assays to measure pathway activity in individual patient tissue or cell samples. We developed a method enabling quantitative measurement of functional pathway activity based on Bayesian computational model inference of pathway activity from measurements of mRNA levels of target genes of the pathway-associated transcription factor. Oestrogen receptor, Wnt, and PI3K-FOXO pathway assays have been described previously. Here, we report model development for androgen receptor, Hedgehog, TGFβ, and NFκB pathway assays, biological validation on multiple cell types, and analysis of data from published clinical studies (multiple sclerosis, amyotrophic lateral sclerosis, contact dermatitis, Ewing sarcoma, lymphoma, medulloblastoma, ependymoma, skin and prostate cancer). Multiple pathway analysis of clinical prostate cancer (PCa) studies showed increased AR activity in hyperplasia and primary PCa but variable AR activity in castrate resistant (CR) PCa, loss of TGFβ activity in PCa, increased Wnt activity in TMPRSS2:ERG fusion protein-positive PCa, active PI3K pathway in advanced PCa, and active PI3K and NFκB as potential hormonal resistance pathways. Potential value for future clinical practice includes disease subtyping and prediction and targeted therapy response prediction and monitoring.

Optimal treatment of cancer requires diagnostic methods to facilitate therapy choice and prevent ineffective treatments. Direct assessment of therapy response in viable tumor specimens could fill this diagnostic gap. Therefore, we designed a microfluidic platform for assessment of patient treatment response using tumor tissue slices under precisely controlled growth conditions. The optimized Cancer-on-Chip (CoC) platform maintained viability and sustained proliferation of breast and prostate tumor slices for 7 days. No major changes in tissue morphology or gene expression patterns were observed within this time frame, suggesting that the CoC system provides a reliable and effective way to probe intrinsic chemotherapeutic sensitivity of tumors. The customized CoC platform accurately predicted cisplatin and apalutamide treatment response in breast and prostate tumor xenograft models, respectively. The culture period for breast cancer could be extended up to 14 days without major changes in tissue morphology and viability. These culture characteristics enable assessment of treatment outcomes and open possibilities for detailed mechanistic studies. Significance: The Cancer-on-Chip platform with a 6-well plate design incorporating silicon-based microfluidics can enable optimal patient-specific treatment strategies through parallel culture of multiple tumor slices and diagnostic assays using primary tumor material.

The phosphatidylinositol 3-kinase (PI3K) pathway is commonly activated in cancer. Tumors are potentially sensitive to PI3K pathway inhibitors, but reliable diagnostic tests that assess functional PI3K activity are lacking. Because PI3K pathway activity negatively regulates forkhead box-O (FOXO) transcription factor activity, FOXO target gene expression is inversely correlated with PI3K activity. A knowledge-based Bayesian computational model was developed to infer PI3K activity in cancer tissue samples from FOXO target gene mRNA levels and validated in cancer cell lines treated with PI3K inhibitors. However, applied to patient tissue samples, FOXO was often active in cancer types with expected active PI3K. SOD2 was differentially expressed between FOXO-active healthy and cancer tissue samples, indicating that cancer-associated cellular oxidative stress alternatively activated FOXO. To enable correct interpretation of active FOXO in cancer tissue, threshold levels for normal SOD2 expression in healthy tissue were defined above which FOXO activity is oxidative stress induced and below which PI3K regulated. In slow-growing luminal A breast cancer and low Gleason score prostate cancer, FOXO was active in a PI3K-regulated manner, indicating inactive PI3K. In aggressive luminal B, HER2, and basal breast cancer, FOXO was increasingly inactive or actively induced by oxidative stress, indicating PI3K activity. We provide a decision tree that facilitates functional PI3K pathway activity assessment in tissue samples from patients with cancer for therapy response prediction and prognosis.