Determining the ownership of a patient's personal genomic data is important because it impacts how data is governed and shared, which has both clinical and research implications for precision oncology. The 21st Century Cures Act enacted in December 2016 defined the ownership of clinical genomic data, but the governance of research-grade genomic data remains a hotly contested topic. The many stakeholders often have competing perspectives about ownership of raw and processed genomic data derived in research settings and how to weigh risks versus benefits of sharing this data with study participants. A growing number of research studies, policy recommendations, and ethics reviews have not been enough to influence changes in practice. Most genomic research is conducted in academia, which is guided by Institutional Review Board-approved protocols to protect study participants. The current standard is to limit the return of research-grade data to study participants, and give data ownership solely to the researchers or the research institution, since this data is not vetted for clinical purposes and is meant for research use only. However, these practices conflict not only with recommendations from peer-reviewed literature on best practices for addressing research study participants' needs but might indeed run counter to legal and ethical guidelines about data ownership. For example, patient-participants faced with poorly understood or incurable diseases such as certain cancers want, and could potentially benefit from, having access to their personal genomic data in this rapidly evolving field. This commentary highlights the gap between the status quo as approved by the IRB and the literature suggesting that study participants should be given access to their personal genomic data. There is an opportunity to facilitate a more effective and ethical way to collect genomic data for research use across institutions.

Oral squamous cell carcinomas (OSCC) are the 6th most common cancer and the diagnosis is often belated for a curative treatment. The reliable and early differentiation between healthy and diseased cells is the main aim of this study in order to improve the quality of the treatment and to understand tumour pathogenesis. Here, the optical stretcher is used to analyse mechanical properties of cells and their potential to serve as a marker for malignancy. Stretching experiments revealed for the first time that cells of primary OSCCs were deformed by 2.9 % rendering them softer than cells of healthy mucosa which were deformed only by 1.9 %. Furthermore, the relaxation behaviour of the cells revealed that these malignant cells exhibit a faster contraction than their benign counterparts. This suggests that deformability as well as relaxation behaviour can be used as distinct parameters to evaluate emerging differences between these benign and malignant cells. Since many studies in cancer research are performed with cancer cell lines rather than primary cells, we have compared the deformability and relaxation of both types, showing that long time culturing leads to softening of cells. The higher degree of deformability and relaxation behaviour can enable cancer cells to traverse tissue emphasizing that changes in cell architecture may be a potential precondition for malignant transformation. Respecting the fact that even short culture times have an essential effect on the significance of the results, the use of primary cells for further research is recommended. The distinction between malignant and benign cells would enable an early confirmation of cancer diagnoses by testing cell samples of suspect oral lesions.

Author(s): Clark, Haley D; Thomas, Steven D; Reinsberg, Stefan A; Moiseenko, Vitali V; Hovan, Allan J; Wu, Jonn S

The question of the existence of cancer is inadequately answered by invoking somatic mutations or the disruptions of cellular and tissue control mechanisms. As such uniformly random events alone cannot account for the almost inevitable occurrence of an extremely complex process such as cancer. In the different epistemic realm, an ultimate explanation of cancer is that cancer is a reversion of a cell to an ancestral pre-Metazoan state, i.e. a cellular form of atavism. Several studies have suggested that genes involved in cancer have evolved at particular evolutionary time linked to the unicellular-multicellular transition. Here we used a refined phylostratigraphic analysis of evolutionary ages of the known genes/pathways associated with cancer and the genes differentially expressed between normal and cancer tissue as well as between embryonic and mature (differentiated) cells. We found that cancer-specific transcriptomes and cancer-related pathways were enriched for genes that evolved in the pre-Metazoan era and depleted of genes that evolved in the post-Metazoan era. By contrast an opposite relation was found for cell maturation: the age distribution frequency of the genes expressed in differentiated epithelial cells were enriched for post-Metazoan genes and depleted of pre-Metazoan ones. These findings support the atavism theory that cancer cells manifest the reactivation of an ancient ancestral state featuring unicellular modalities. Thus our bioinformatics analyses suggest that not only does oncogenesis recapitulate ontogenesis, and ontogenesis recapitulates phylogenesis, but also oncogenesis recapitulates phylogenesis. This more encompassing perspective may offer a natural organizing framework for genetic alterations in cancers and point to new treatment options that target the genes controlling the atavism transition.

The majority of cancers are diagnosed using excised biopsy specimens. These are graded, using a gold-standard histopathology protocol based on haemotoxylin and eosin ('H + E') chemical staining. However the grading is done by eye and if the same biopsy is graded by different practitioners, they typically only agree ~70% of the time. The resulting overtreatment problem constitutes a massive unmet need worldwide. Our new technology, uses mid-infrared imaging to map the fractional concentration of nucleic acids, i.e. the nuclear-to-cytoplasmic chemical ratio (NCR) across an unstained biopsy section. It allows a quantitative 'Digistain index' (DI) score, corresponding to the NCR, to be reproducibly extracted from an objective physical measurement of a cancer. Our objective here is to evaluate its potential for aiding cancer diagnosis for the first time. We correlate the DI scores with H + E grades in a double-blind clinical pilot trial. Two adjacent slices were taken from 75 breast cancer FFPE blocks; one was graded with the standard H + E protocol, and also used to define a 'region of interest' (RoI). Digistain was then used to acquire a DI value averaged over the corresponding RoI on the other (unstained) slice and the results were statistically analysed. We find the DI score correlates significantly (p = 0.0007) with tumor grade in a way that promises to significantly reduce the inherent subjectivity and variability in biopsy grading. The NCR is elevated by increased mitotic activity because cells divide when they are younger and, on average, become smaller as the disease progresses. Also, extra DNA and RNA is generated as the nuclear transcription machinery goes awry and nuclear pleomorphism occurs. Both effects make the NCR a recognized biomarker for a wide range of tumors, so we expect Digistain will find application in a very wide range of cancers.

With increasingly ubiquitous electronic medical record (EMR) implementation accelerated by the adoption of the HITECH Act, there is much interest in the secondary use of collected data to improve outcomes and promote personalized medicine. A plethora of research has emerged using EMRs to investigate clinical research questions and assess variations in both treatments and outcomes. However, whether because of genuine complexities of modeling disease physiology or because of practical problems regarding data capture, data accuracy, and data completeness, the state of current EMR research is challenging and gives rise to concerns regarding study accuracy and reproducibility. This work explores challenges in how different experimental design decisions can influence results using a specific example of breast cancer patients undergoing excision and reconstruction surgeries from EMRs in an academic hospital and the Veterans Health Administration (VHA) We discuss emerging strategies that will mitigate these limitations, including data sharing, application of natural language processing, and improved EMR user design.

Molecular analysis of circulating and disseminated tumor cells (CTCs/DTCs) has great potential as a means for continuous evaluation of prognosis and treatment efficacy in near-real time through minimally invasive liquid biopsies. To realize this potential, however, methods for molecular analysis of these rare cells must be developed and validated. Here, we describe the integration of imaging mass cytometry (IMC) using metal-labeled antibodies as implemented on the Fluidigm Hyperion Imaging System into the workflow of the previously established High Definition Single Cell Analysis (HD-SCA) assay for liquid biopsies, along with methods for image analysis and signal normalization. Using liquid biopsies from a metastatic prostate cancer case, we demonstrate that IMC can extend the reach of CTC characterization to include dozens of protein biomarkers, with the potential to understand a range of biological properties that could affect therapeutic response, metastasis and immune surveillance when coupled with simultaneous phenotyping of thousands of leukocytes.

Tumor heterogeneity is prevalent in both treatment-naïve and end-stage metastatic castration-resistant prostate cancer (PCa), and may contribute to the broad range of clinical presentation, treatment response, and disease progression. To characterize molecular heterogeneity associated with de novo metastatic PCa, multiplatform single cell profiling was performed using high definition single cell analysis (HD-SCA). HD-SCA enabled morphoproteomic and morphogenomic profiling of single cells from touch preparations of tissue cores (prostate and bone marrow biopsies) as well as liquid samples (peripheral blood and bone marrow aspirate). Morphology, nuclear features, copy number alterations, and protein expression were analyzed. Tumor cells isolated from prostate tissue touch preparation (PTTP) and bone marrow touch preparation (BMTP) as well as metastatic tumor cells (MTCs) isolated from bone marrow aspirate were characterized by morphology and cytokeratin expression. Although peripheral blood was examined, circulating tumor cells were not definitively observed. Targeted proteomics of PTTP, BMTP, and MTCs revealed cell lineage and luminal prostate epithelial differentiation associated with PCa, including co-expression of EpCAM, PSA, and PSMA. Androgen receptor expression was highest in MTCs. Hallmark PCa copy number alterations, including PTEN and ETV6 deletions and NCOA2 amplification, were observed in cells within the primary tumor and bone marrow biopsy samples. Genomic landscape of MTCs revealed to be a mix of both primary and bone metastatic tissue. This multiplatform analysis of single cells reveals several clonal origins of metastatic PCa in a newly diagnosed, untreated patient with polymetastatic disease. This case demonstrates that real-time molecular profiling of cells collected through prostate and bone marrow biopsies is feasible and has the potential to elucidate the origin and evolution of metastatic tumor cells. Altogether, biological and genomic data obtained through longitudinal biopsies can be used to reveal the properties of PCa and can impact clinical management.