Marc Martignoni, M.D., is a surgeon and clinical researcher with Klinikum Rechts der Isar in Munich. As part of a team led by Professor Helmut Friess, director of surgery at the Klinikum Rechts der Isar, Dr. Martignoni’s research focuses on improving outcomes for patients with pancreatic cancer. Pancreatic cancer has an abysmal prognosis, therefore targets for early detection, prevention, and therapy are desperately needed.
Prior research directed by Professor Friess identified several genes of interest in the quest to better understand the genetics of pancreatic cancer. To date, the team has analyzed gene expression using tumor samples that consisted of 1,000 cells or more in order to extract the quantities of genetic material needed for microarray analysis or conventional qPCR.
Dr. Martignoni now wants to investigate how gene expression for those genes of interest differs between individual tumor cells, and how the differences help explain prognosis and response to treatment. Differences between gene expression in tumor cells—tumor heterogeneity—are a direct result of the genetic mutations that occur during tumorigenesis. However, due to the methodological limitations of conventional microarray or PCR technologies, only a few research groups have directly measured tumor heterogeneity, let alone studied the associations between degree of heterogeneity and clinical outcomes.
In order to achieve the sensitivity needed to obtain robust multiplex gene-expression data from individual tumor cells, Dr. Martignoni is using the AmpliGrid single-cell molecular analysis platform. Initially, he will be working with circulating tumor cells. First he wants to deliver a molecular proof that circulating EPCAM-positive cells from patients with pancreatic cancer that are isolated via flow cytometry do indeed originate from the pancreatic tumor. This process will be accomplished by comparing their expression profile with cells extracted from the primary tumor.
Next he will determine if circulating tumor cells (CTC) can be substratified by their individual expression differences, and whether the degree of heterogeneity is associated with clinical parameters such as prognosis or response to treatment.
If such subpopulations exist, and they can be shown to drive clinical outcomes, genetic analysis of CTCs would present a significant refinement to approaches that rely solely on the number of CTCs detected. Another aspect of Dr. Martignoni’s work will be to determine whether and how chemotherapy changes the expression patterns in CTCs. To what extent are apoptosis markers, which are downregulated in cancer cells, upregulated in CTCs following chemotherapy? Ultimately, the insight gained from measuring heterogeneity may lead to a more personalized approach to selecting the course of chemotherapy most likely to be successful for a given patient.