A novel breakthrough in predicting treatment resistance for cancer patients

Cancer care has changed dramatically in the past few years following the COVID-19 pandemic. The goal of researchers everywhere is to develop more advanced and targeted treatments, such that patients may experience better outcomes and higher survival rates.

To mark World Cancer Research Day, we caught up with Dr Michal Marek Hoppe, a data analyst at our programme, the Singapore Translational Cancer Consortium ↗ (opens in new tab) (STCC) and joint fellow at CSI Singapore.

Michal has over 15 years of experience in biomedical and translational cancer research. In addition to joining STCC, he has been contributing actively to ground-breaking cancer research as a joint fellow at the Cancer Science Institute of Singapore (CSI Singapore). Together with his team led by Dr Anand Jeyasekharan, Principal Investigator and Facility Head (Microscopy and Multiplex Assays Core), CSI Singapore, they discovered a breakthrough novel approach for predicting resistance against cancer therapy in patients with diffuse large B-cell lymphoma (DLBCL). They embarked on the project in 2018 and the results were recently published in Cancer Discovery ↗ (opens in new tab), the flagship journal of the American Association of Cancer Research (AACR). ^[1]

DLBCL is the most common type of blood cancer globally and in Singapore. A combination of chemo-immunotherapy drugs, known as R-CHOP, is commonly recommended as a first-line treatment for DLBCL. ^[2] However, when patients do not respond to these standard therapies or experience a relapse, they are unlikely to respond to other forms of treatment. Their prospects for alternative treatment options become starkly limited. ^[3]
Hence, there is a need to identify patients who are likely to exhibit resistance to standard therapies early, such that more effective treatment modalities can be sought for them sooner.

Understanding the impact of oncogenes in cancer patients

Michal and his team discovered a unique combination of oncogenes that could predict treatment resistance for patients with DLBCL, providing insights which are highly significant for the clinical management of the cancer.

Using samples from patients with DLBCL, the team studied how specific combinations of oncogenes in malignant cells would lead to treatment resistance. Presently, immunohistochemistry, which measures protein expression of three oncogenes - MYC, BCL2 and BCL6 - is used in clinical practice to detect high-risk DLBCL cases but can only evaluate oncogene expression one at a time. This limitation makes it impossible for researchers to spot cell subgroups with specific oncogenic combinations.

Discovery of an unfavourable combination of oncogenes

To surmount this challenge, the team turned to multi-spectral microscopy with quantitative immunofluorescence. The microscopy system, which has become more prominent in Southeast Asia research facilities, was set up in CSI Singapore by Michal back in 2013.

Michal programming the microscopy system in 2013

With this method, the team could stain, image, and quantify these oncogenes simultaneously in a large number of samples from DLBCL patients. ^[4] They discovered that patients with a high percentage of cells that are positive for MYC and BCL2, but negative for BCL6, have low survival rates. Across multiple patient groups, the presence of this specific combination was consistently associated with poor overall survival, compared to all other cellular combinations of the three oncogenes.

To put simply, patients with few bad co-expressing cells identified in the tumour mass, could proceed with routine traditional forms of treatment. For those who have a larger extent of those bad-prognostic cells among malignant cells, which indicates treatment resistance, they can be considered for alternative forms of cancer therapy up-front. ^[5]

Multispectral microscopy with quantitative immunofluorescence in comparison to immunohistochemistry

Propelling their research forward

Originally conceived back in 2018, the idea to study a combination of oncogenes to analyse the impact of their combined influence on cancer prognosis gained momentum through active patient profiling and research. “The extension of the study beyond protein profiling was a concept I had developed during the COVID-19 circuit breaker in 2020,” he said. Amid the circuit breaker trademarks of dalgona coffee and sourdough bread, the addition of his concept coincided with the period when the study reached its breakthrough and entered its final stages.

Michal’s chickens that accompanied him as he hatched his eggcellent concept during the circuit breaker

With that concept, the research team at CSI Singapore went a step further to develop a simple mathematical formula that can predict the fraction of cells with this unique unfavourable combination from routine immunohistochemistry data and bulk RNA sequencing. The formula paves the way for this digital pathology method to be used in routine clinical practice and clinical management of DLBCL.

Michal shared that the mathematical formula will be further investigated through international collaborations led by the team, with the aim of validating recent findings and to solidify the utility of the algorithm to stratify patients for poor survival after R-CHOP therapy. Additionally, molecular mechanisms explaining the rise of bad-prognostic cells among malignant B-cells are being studied using molecular and spatial technologies. 

Ultimately, their findings could potentially be applied to other cancer types as well, for simultaneous detection of oncogenes which is vital to provide targeted treatment plans and better outcomes for patients.

Michal shares the experimental setup and overview results derived from the team’s research

Overall, this breakthrough discovery was made possible by a large team of researchers led by Dr Jeyasekharan. Michal described this as a large international effort which featured a number of key opinion leaders. “Dr Patrick Jaynes of CSI Singapore played an instrumental role in coordinating the project, as well as Prof Claudio Tripodo of University of Palermo, whose expert opinion on the topic helped to shape the research into its final format,” he shared.

Yet, Michal knows there is much more to be done.

Advancements for the cancer research landscape

Dr Jeyasekharan is also the lead for STCC’s Translational Research Integration & Support ↗ (opens in new tab) (TRIS) platform, where Michal is also a team member. TRIS is focused on developing, testing, and validating potential new biomarkers and molecular diagnostics.

He shared with excitement about the multi-institutional studies led by STCC, namely SPACER and SUPER. The former aims to identify molecular features in the tumour micro-environment in four types of cancers - soft tissue sarcomas, breast cancer, multiple myeloma, and hepatocellular carcinoma, which are associated with resistance towards immunotherapy. Meanwhile, the objective of SUPER is to find new ways to predict which patients are suitable for immunotherapy and to develop better treatments for those who do not respond favourably. 

Tapping on his expertise in translational cancer research, Michal is analysing the data from the two projects, which will adopt the application of cutting-edge technologies to simultaneously detect multiple cancer markers. 

“With the concerted efforts of various research teams across Singapore, along with STCC’s oversight and analytical capabilities, we aim to develop novel prediction models to characterise patients with poor prognosis across various clinically-relevant modalities,” he explained.

As such, Michal aspires to advance biomarker-driven personalised cancer treatment in Singapore, such that more effective therapy with minimal side effects can be developed and ultimately, improve patient outcomes.

“Unbiased critical evaluation of data is a foundation of innovative and reliable advancement of science,” he said with a smile.

Citations

^[1] Michal Marek Hoppe, Patrick Jaynes, Fan Shuangyi, Yanfen Peng, Shruti Sridhar, Phuong Mai Hoang, Clementine Xin Liu, Sanjay De Mel, Limei Poon, Esther Hian Li Chan, Joanne Lee, Choon Kiat Ong, Tiffany Tang, Soon Thye Lim, Chandramouli Nagarajan, Nicholas F. Grigoropoulos, Soo-Yong Tan, Susan Swee-Shan Hue, Sheng-Tsung Chang, Shih-Sung Chuang, Shaoying Li, Joseph D. Khoury, Hyungwon Choi, Carl Harris, Alessia Bottos, Laura J. Gay, Hendrik F.P. Runge, Ilias Moutsopoulos, Irina Mohorianu, Daniel J. Hodson, Pedro Farinha, Anja Mottok, David W. Scott, Jason J. Pitt, Jinmiao Chen, Gayatri Kumar, Kasthuri Kannan, Wee Joo Chng, Yen Lin Chee, Siok-Bian Ng, Claudio Tripodo, Anand D. Jeyasekharan; Patterns of oncogene coexpression at single-cell resolution influence survival in lymphoma. Cancer Discov 1 May 2023; 13 (5): 1144–1163.
https://doi.org/10.1158/2159-8290.CD-22-0998 ↗ (opens in new tab)

^[2] SingHealth, Defining Med, Medical News (8 Oct 2021). A new approach to treating cancer – Chimeric Antigen Receptor (CAR) T-cell immunotherapy
https://www.singhealth.com.sg/news/defining-med/a-new-approach-to-treating-cancer-chimeric-antigen-receptor-car-t-cell-immunotherapy ↗ (opens in new tab)

^[3] The Straits Times (14 Oct 2020). Lymphoma: Higher rates of survival on the horizon.
https://www.straitstimes.com/singapore/health/lymphoma-higher-rates-of-survival-on-the-horizon ↗ (opens in new tab) 

^[4] OpenGov Asia (28 Jul 2023). Singapore: Innovative imaging revolutionises cancer diagnosis.
https://www.opengovasia.com/singapore-innovative-imaging-revolutionises-cancer-diagnosis/ ↗ (opens in new tab) 

^[5] NUS News (19 Jul 2023). NUS researchers develop novel approach for predicting resistance against cancer therapy.
https://news.nus.edu.sg/novel-approach-predicting-resistance-against-cancer-therapy/ ↗ (opens in new tab)