School of Veterinary Medicine, University College Dublin, Ireland

Dr. Sourav Bhattacharjee is a physician (MBBS) and graduated from the Medical College and Hospital Kolkata (India). After postgraduate residency training in orthopedic surgery, he finished MSc in Biomolecular Sciences/Cell Biology from the Vrije Universiteit Amsterdam (2006-2008). His MSc thesis work was done in the lab of Prof. Vicki Stone in the Napier University (Edinburgh, UK). He began his Ph.D. in the Wageningen University (Netherlands) in 2008 which he successfully defended in 2012 with a very good thesis and quite few research papers. Following that he worked for almost a year as a postdoc in the MESA+ Institute for Nanotechnology (University of Twente, Netherlands). From March 2014, he joined UCD (Ireland) as postdoc trying to develop nanoparticulate platforms for oral insulin delivery as part of the EU FP7 funded TRANS-INT consortium. From February 2016 he was appointed as Assistant Professor in the UCD, where apart from being a teacher of anatomy in the medical school, he is engaged with developing a broad range of advanced nanotech-based tools for theranostic purposes.

Speech Title: Toward developing an optical platform for the early detection of colorectal cancer: Quo vadis?

Abstract: Colorectal cancer (CRC)—the third commonest cancer in the world—is a challenge for the healthcare sector due to the cumulative human suffering and financial burden it causes. An early detection holds the key in successful management of the patients; albeit remains elusive so far, particularly in the borderline or CIS (carcinoma in situ) cases. Current histopathologic examination of the tissue biopsy specimens stained in H&E (hematoxylin and eosin) unfortunately suffers from paucity of data, lack of 3D visualization or HTS (high-throughput screening), and is inherently vulnerable toward flaws due to the empirical interpretation of data. In this project, a paradigm shift in histopathologic tissue examination was proposed on the basis of excellent autofluorescence demonstrated by human colonic tissues, which in addition to its established advantages, such as hardly any necessity for tissue manipulation or to follow time-consuming expensive protocols to label tissues with fluorophores, also demonstrates resistance toward photobleaching. We hypothesized that as an ultrasensitive technique, fluorescence will be able to spot even the minutest changes in the tissue blocs triggered by the onset of neoplasia—thus, enabling detection at a nascent state. Surgical biopsy samples of human CRC collected under ethical approval were subjected to extensive epifluorescence and FLIM (fluorescence lifetime imaging microscopy)-based studies exploiting its autofluorescence, and was followed by in-depth texture analysis with the aid of advanced machine learning tools. Overall, the cancer tissues demonstrated higher emission than the normal tissues, while the texture analysis was able to discern them from the normal ones on the basis of the characteristic pathology ingrained within the fabric of TME (tumor microenvironment). The integrated data provided a niche for exploring further avenues toward devising a sensitive diagnostic platform for CRC, highlighted its salient features, and prioritized few perspectives as possible future directions in the field of oncotherapeutics.

Keywords: Colorectal cancer, biophotonics, autofluorescence, machine learning, FLIM, tissue microscopy