Lymphomas are cancers arising from lymphocytes, most often from B lymphocytes that are part of our immune system. WHO has recognized 70 different types of lymphoma, and these have highly variable disease course. Diffuse large B-cell lymphoma (DLBCL) is the most common form of aggressive lymphoma, while follicular lymphoma (FL) is the most common form of indolent lymphoma. Although treatment with rituximab, an anti-CD20 monoclonal antibody, has highly improved survival when combined with chemotherapy, some types are still considered incurable, such as FL and mantle cell lymphoma (MCL). Patients with FL usually have good prognosis, but can transform to aggressive disease with dismal outcome. More than 65% of DLBCL patients are cured with chemo-immunotherapy (R-CHOP). However, those who experience early relapse, have a very poor prognosis. In this project, our overall goal was to perform molecular characterization of tumor cells and the tumor microenvironment to identify better predictors for therapeutic responses, and to identify new targets for therapeutic intervention.
For risk stratification of MCL, high expression of proliferation genes is associated with poor outcome. Several efforts has been made to translate these results into laboratory tests that can be implemented in the clinic, using paraffin embedded (FFPE) biopsies. As a collaborative effort of the Lymphoma and Leukemia Molecular Profiling Project (LLMPP, headed by Dr. Louis Staudt, NCI), a the MCL35 assay was developed. This assay, based on detection of 17 proliferation genes in FFPE biopsies, could define groups of patients with different outcome (Scott, J Clin Oncol 2017). The expression of Ki-67 protein is a surrogate marker for the proliferation signature in MCL. We developed a computerized image analysis software, to quantify the percentage of Ki-67 positive tumor cells (Blaker, Histopathology 2015), that easily can be implemented in routine diagnostics. In collaboration with Stanford University, we characterized B-cell receptor (BCR) signaling pathways in different types of lymphoma (FL, MCL, DLBCL and chronic lymphocytic leukemia (CLL)). Here, we identified that BCR signaling strength might serve as a new biomarker for therapy response to BCR pathway inhibitors (Myklebust, Blood 2017).
To identify genetic changes underlying development of therapy resistance and poor patient survival, we initiated two large next generation sequencing projects, using patient biopsies from FL and DLBCL patients. These projects were part of the Norwegian Cancer Genomics Consortium (NCGC). For both patient cohorts, serial biopsies from the same patients, i.e. samples taken at diagnosis and at relapse were included. In DLBCL, we identified 105 potential cancer driver genes, and validated these in a separate cohort. Importantly, patient samples at relapse had higher mutational burden of genes in the p53 DNA damage signaling pathway. Hence, these patients will likely not benefit from chemotherapy that depends on a functional p53 pathway to be effective (Wise, under review). Similar to the DLBCL project, we have initiated a large sequencing study of 100 tumors from 42 patients with FL. The sequencing is completed, and the bioinformatics analysis is ongoing to identify cancer driver genes, and to identify mutated genes associated with risk of transformation. For the FL cohort, analysis of clonal evolution will also be done. These two comprehensive projects should enable identification of specific mutations driving therapy resistance, and guide development of biomarkers to identify patients who will not benefit from standard therapy (R-CHOP).
Immunotherapy with checkpoint blockade represents a major breakthrough for cancer treatment, and has induced long-lasting remissions in patients with otherwise dismal prognosis. Although checkpoint therapy holds great promise, the majority of cancer patients do not respond to blockade of PD-1 or CTLA-4, the two best studied co-inhibitory receptors. We used high dimensional flow cytometry to characterize the expression pattern of these and other co-inhibitory receptors in tumor infiltrating immune cells, as well as to explore the function of the immune cells. This study revealed that the novel receptor TIGIT was highly expressed in T cells in FL tumors (Josefsson, Clin Cancer Res 2018). We have also performed a similar study in different lymphoma types, and discovered that co-expression of TIGIT and PD-1 mark exhausted effector T cells in DLBCL, MCL and CLL (Josefsson, under review). This suggests TIGIT in combination with PD-1 to be a relevant strategy for checkpoint blockade in B-cell lymphoma.
Overall, this FRIMEDBIO project resulted in development of more reliable prognostic biomarkers and led to the discovery of new targets for immune checkpoint blockade. We expect that these results will translate into better treatment options for lymphoma patients with improved survival as outcome.
Lymphomas are cancers that arise from lymphoid cells, often from B lymphocytes which are part of the immune system. B-cell lymphoma is a heterogeneous group of diseases with as many as 70 distinct types recognized by WHO. In addition, patients with identi cal diagnosis can have remarkably variable prognosis. Although new therapeutic approaches (in particular monoclonal antibodies) have highly improved overall survival, some patients do not benefit from therapy, and others develop resistance to further trea tment. We aim to identify biomarkers for targeted therapies and to develop new therapeutic strategies. We will focus on changes that correlate with response to therapy or clinical outcome and identify biomarkers, which can be useful in the diagnosis, moni toring or treatment of the diseases. Via our collaboration partners in the lymphoma program at the hospital and our international collaborations, we have access to a large number of primary patient samples and the patients' clinical data. We will use exom e sequencing to identify genetic abnormalities. Furthermore, we will use phospho-flow cytometry and CyTOF mass cytometry to identify aberrant signaling pathways in lymphoma cells, including detection of constitutive active pathways. Here, we will focus on druggable signaling targets. We will also use flow cytometry and/or immunohistochemical staining of tissue microarray to study protein expression in the tumor biopsies. These techniques will enable us to examine immune cell composition and identify prot eins and kinases involved in proliferation, death regulation and signaling pathways. Finally, we will use shRNA or overexpression by retroviral transduction of B-cell lines and normal B cells to examine the functional roles of abnormal genes identified by exome sequencing. Overall, this comprehensive approach has the potential to identify new biomarkers for targeted therapy response, and development new strategies for therapy.