Mustafa H. Kabeer

Cancer genomic research at the crossroads: realizing the changing genetic landscape as intratumoral spatial and temporal heterogeneity becomes a confounding factor.

The US National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI) created the Cancer Genome Atlas (TCGA) Project in 2006. The TCGA’s goal was to sequence the genomes of 10,000 tumors to identify common genetic changes among different types of tumors for developing genetic-based treatments. TCGA offered great potential for cancer patients, but in reality has little impact on clinical applications. Recent reports place the past TCGA approach of testing a small tumor mass at a single time-point at a crossroads. This crossroads presents us with the conundrum of whether we should sequence more tumors or obtain multiple biopsies from each individual tumor at different time points. Sequencing more tumors with the past TCGA approach of single time-point sampling can neither capture the heterogeneity between different parts of the same tumor nor catch the heterogeneity that occurs as a function of time, error rates, and random drift. Obtaining multiple biopsies from each individual tumor presents multiple logistical and financial challenges. Here, we review current literature and rethink the utility and application of the TCGA approach. We discuss that the TCGA-led catalogue may provide insights into studying the functional significance of oncogenic genes in reference to non-cancer genetic background. Different methods to enhance identifying cancer targets, such as single cell technology, real time imaging of cancer cells with a biological global positioning system, and cross-referencing big data sets, are offered as ways to address sampling discrepancies in the face of tumor heterogeneity. We predict that TCGA landmarks may prove far more useful for cancer prevention than for cancer diagnosis and treatment when considering the effect of non-cancer genes and the normal genetic background on tumor microenvironment. Cancer prevention can be better realized once we understand how therapy affects the genetic makeup of cancer over time in a clinical setting. This may help create novel therapies for gene mutations that arise during a tumor’s evolution from the selection pressure of treatment.

Training stem cells for treatment of malignant brain tumors

The treatment of malignant brain tumors remains a challenge. Stem cell technology has been applied in the treatment of brain tumors largely because of the ability of some stem cells to infiltrate into regions within the brain where tumor cells migrate as shown in preclinical studies. However, not all of these efforts can translate in the effective treatment that improves the quality of life for patients. Here, we perform a literature review to identify the problems in the field. Given the lack of efficacy of most stem cell-based agents used in the treatment of malignant brain tumors, we found that stem cell distribution (i.e., only a fraction of stem cells applied capable of targeting tumors) are among the limiting factors. We provide guidelines for potential improvements in stem cell distribution. Specifically, we use an engineered tissue graft platform that replicates the in vivo microenvironment, and provide our data to validate that this culture platform is viable for producing stem cells that have better stem cell distribution than with the Petri dish culture system.

Microfluidic enrichment of plasma cells improves treatment of multiple myeloma

Cytogenetic alterations form the basis for risk stratification for multiple myeloma (MM) and guide the selection of therapy; however, current pathology assays performed on bone marrow samples can produce false‐negatives due to the unpredictable distribution and rarity of MM cells. Here, we report on a microfluidic device used to facilitate CD45 depletion to enhance the detection of cytogenetic alterations in plasma cells (PCs). Bone marrow samples from 48 patients with MM were each divided into two aliquots. One aliquot was subjected to classic flow cytometry and fluorescent in situ hybridization (FISH). The other first went through CD45+ cell depletion, further enriched by microfluidic size selection. The enriched samples were then analyzed using flow cytometry and FISH and compared to those analyzed using the classic method only. Unlike the traditional method, the microfluidic device removed the CD45+ leukocytes and specifically selected PCs from the remaining white blood cells. Therefore, the microfluidic method (MF‐CD45‐TACs) significantly increased the percentage of CD38+/CD138+ cells to 37.7 ± 20.4% (P < 0.001) from 10.3 ± 8.5% in bone marrow. After the MF‐CD45‐TAC enrichment, the detection rate of IgH rearrangement, del(13q14), del(17p), and 1q21 gains, rose to 56.3% (P < 0.001), 37.5% (P < 0.001), 22.9% (P < 0.001), and 41.7% (P = 0.001), respectively; all rates of detection were significantly increased compared to the classically analyzed samples. In this clinical trial, this microfluidic‐assisted assay provided a precise detection of cytogenetic alterations in PCs and improved clinical outcomes.

Spatiotemporal switching signals for cancer stem cell activation in pediatric origins of adulthood cancer: Towards a watch-and-wait lifetime strategy for cancer treatment

Pediatric origin of cancer stem cell hypothesis holds great promise and potential in adult cancer treatment, however; the road to innovation is full of obstacles as there are plenty of questions left unanswered. First, the key question is to characterize the nature of such stem cells (concept). Second, the quantitative imaging of pediatric stem cells should be implemented (technology). Conceptually, pediatric stem cell origins of adult cancer are based on the notion that plasticity in early life developmental programming evolves local environments to cancer. Technologically, such imaging in children is lacking as all imaging is designed for adult patients. We postulate that the need for quantitative imaging to measure space-time changes of plasticity in early life developmental programming in children may trigger research and development of the imaging technology. Such quantitative imaging of pediatric origin of adulthood cancer will help develop a spatiotemporal monitoring system to determine cancer initiation and progression. Clinical validation of such speculative hypothesis-that cancer originates in a pediatric environment-will help implement a wait-and-watch strategy for cancer treatment.

Single-cell transcriptomes reveal the mechanism for a breast cancer prognostic gene panel

The clinical benefits of the MammaPrint® signature for breast cancer is well documented; however, how these genes are related to cell cycle perturbation have not been well determined. Our single-cell transcriptome mapping (algorithm) provides details into the fine perturbation of all individual genes during a cell cycle, providing a view of the cell-cycle-phase specific landscape of any given human genes. Specifically, we identified that 38 out of the 70 (54%) MammaPrint® signature genes are perturbated to a specific phase of the cell cycle. The MammaPrint® signature panel derived its clinical prognosis power from measuring the cell cycle activity of specific breast cancer samples. Such cell cycle phase index of the MammaPrint® signature suggested that measurement of the cell cycle index from tumors could be developed into a prognosis tool for various types of cancer beyond breast cancer, potentially improving therapy through targeting a specific phase of the cell cycle of cancer cells.

Relapse pathway of glioblastoma revealed by single-cell molecular analysis

Glioblastoma multiforme (GBM) remains an incurable brain tumor. The highly malignant behavior of GBM may, in part, be attributed to its intraclonal genetic and phenotypic diversity (subclonal evolution). Identifying the molecular pathways driving GBM relapse may provide novel, actionable targets for personalized diagnosis, characterization of prognosis and improvement of precision therapy. We screened single-cell transcriptomes, namely RNA-seq data of primary and relapsed GBM tumors from a patient, to define the molecular profile of relapse. Characterization of hundreds of individual tumor cells identified three mutated genes within single cells, involved in the RAS/GEF GTP-dependent signaling pathway. The identified molecular pathway was further verified by meta-analysis of RNA-seq data from more than 3000 patients. This study showed that single-cell molecular analysis overcomes the inherent heterogeneity of bulk tumors with respect to defining tumor subclonal evolution relevant to GBM relapse.