Inflammatory and subtype-dependent serum protein signatures predict survival beyond the ctDNA in aggressive B cell lymphomas.

BACKGROUND: Biological heterogeneity of large B cell lymphomas (LBCLs) is poorly captured by current prognostic tools, hampering optimal treatment decisions. METHODS: We dissected the levels of 1,463 serum proteins in a uniformly treated trial cohort of 109 patients with high-risk primary LBCL (ClinicalTrials.gov: NCT01325194) and correlated the profiles with molecular data from tumor tissue and circulating tumor DNA (ctDNA) together with clinical data. FINDINGS: We discovered clinically and biologically relevant associations beyond established clinical estimates and ctDNA. We identified an inflamed serum protein profile, which reflected host response to lymphoma, associated with inflamed and exhausted tumor microenvironment features and high ctDNA burden, and translated to poor outcome. We composed an inflammation score based on the identified inflammatory proteins and used the score to predict survival in an independent LBCL trial cohort (ClinicalTrials.gov: NCT03293173). Furthermore, joint analyses with ctDNA uncovered multiple serum proteins that correlate with tumor burden. We found that SERPINA9, TACI, and TARC complement minimally invasive subtype profiling and that TACI and TARC can be used to evaluate treatment response in a subtype-dependent manner in the liquid biopsy. CONCLUSIONS: Altogether, we discovered distinct serum protein landscapes that dissect the heterogeneity of LBCLs and provide agile, minimally invasive tools for precision oncology. FUNDING: This research was funded by grants from the Research Council of Finland, Finnish Cancer Organizations, Sigrid Juselius Foundation, University of Helsinki, iCAN Digital Precision Cancer Medicine Flagship, Orion Research Foundation sr, and Helsinki University Hospital.

Serum protein profiling reveals an inflammation signature as a predictor of early breast cancer survival.

BACKGROUND: Breast cancers exhibit considerable heterogeneity in their biology, immunology, and prognosis. Currently, no validated, serum protein-based tools are available to evaluate the prognosis of patients with early breast cancer. METHODS: The study population consisted of 521 early-stage breast cancer patients with a median follow-up of 8.9 years. Additionally, 61 patients with breast fibroadenoma or atypical ductal hyperplasia were included as controls. We used a proximity extension assay to measure the preoperative serum levels of 92 proteins associated with inflammatory and immune response processes. The invasive cancers were randomly split into discovery (n = 413) and validation (n = 108) cohorts for the statistical analyses. RESULTS: Using LASSO regression, we identified a nine-protein signature (CCL8, CCL23, CCL28, CSCL10, S100A12, IL10, IL10RB, STAMPB2, and TNFß) that predicted various survival endpoints more accurately than traditional prognostic factors. In the time-dependent analyses, the prognostic power of the model remained rather stable over time. We also developed and validated a 17-protein model with the potential to differentiate benign breast lesions from malignant lesions (Wilcoxon p < 2.2*10- 16; AUC 0.94). CONCLUSIONS: Inflammation and immunity-related serum proteins have the potential to rise above the classical prognostic factors of early-stage breast cancer. They may also help to distinguish benign from malignant breast lesions.

Characterization and clinical impact of the tumor microenvironment in post-transplant aggressive B-cell lymphomas.

Post-transplant lymphoproliferative disorders (PTLD) are iatrogenic immune deficiency-associated lymphoid/plasmacytic proliferations developing due to immunosuppression in solid organ or hematopoietic stem cell allograft patients. PTLD are characterized by abnormal proliferation of lymphoid cells and have a heterogeneous clinical behavior. We profiled expression of >700 tumor microenvironment (TME)-related genes in 75 post-transplant aggressive B-cell lymphomas (PTABCL). Epstein-Barr virus (EBV)-positive PT-ABCL clustered together and were enriched for type I interferon pathway and antiviral-response genes. Additionally, a cytotoxicity gene signature associated with EBV-positivity and favorable overall survival (OS) (hazard ratio =0.61; P=0.019). In silico immunophenotyping revealed two subgroups with distinct immune cell compositions. The inflamed subgroup with higher proportions of immune cells had better outcome compared to noninflamed subgroup (median OS >200.0 vs. 15.2 months; P=0.006). In multivariable analysis with EBV status, International Prognostic Index, and rituximab-containing treatment, inflamed TME remained as an independent predictor for favorable outcome. We also compared TME between post-transplant and immunocompetent host diffuse large B-cell lymphomas (n=75) and discovered that the proportions of T cells were lower in PT-diffuse large B-cell lymphomas. In conclusion, we provide a comprehensive phenotypic characterization of PT-ABCL, highlighting the importance of immune cell composition of TME in determining the clinical behavior and prognosis of PT-ABCL.

High-throughput screen in vitro identifies dasatinib as a candidate for combinatorial treatment with HER2-targeting drugs in breast cancer.

Human epidermal growth factor receptor 2-positive (HER2+) breast cancer is an aggressive subtype of this disease. Targeted treatment has improved outcome, but there is still a need for new therapeutic strategies as some patients respond poorly to treatment. Our aim was to identify compounds that substantially affect viability in HER2+ breast cancer cells in response to combinatorial treatment. We performed a high-throughput drug screen of 278 compounds in combination with trastuzumab and lapatinib using two HER2+ breast cancer cell lines (KPL4 and SUM190PT). The most promising drugs were validated in vitro and in vivo, and downstream molecular changes of the treatments were analyzed. The screen revealed multiple drugs that could be used in combination with lapatinib and/or trastuzumab. The Src-inhibitor dasatinib showed the largest combinatorial effect together with lapatinib in the KPL4 cell line compared to treatment with dasatinib alone (p < 0.01). In vivo, only lapatinib significantly reduced tumor growth (p < 0.05), whereas dasatinib alone, or in combination with lapatinib, did not show significant effects. Protein analyses of the treated xenografts showed significant alterations in protein levels compared to untreated controls, suggesting that all drugs reached the tumor and exerted a measurable effect. In silico analyses suggested activation of apoptosis and reduced activity of survival pathways by all treatments, but the opposite pattern was observed for the combinatorial treatment compared to lapatinib alone.

Low lymphocyte-to-monocyte ratio predicts poor outcome in high-risk aggressive large B-cell lymphoma.

Low lymphocyte-to-monocyte-ratio (LMR) has been associated with unfavorable survival in patients with diffuse large B-cell lymphoma (DLBCL). To date, however, the impact of LMR on survival has not been examined in a uniformly treated cohort of patients with high-risk aggressive large B-cell lymphoma. We collected peripheral blood absolute lymphocyte counts (ALCs) and absolute monocyte counts (AMC) prior to treatment and calculated LMR from 112 adult patients, who were less than 65 years of age, had age-adjusted International Prognostic Index 2-3, or site-specific risk factors for central nervous system (CNS) recurrence, and were treated in a Nordic Lymphoma Group LBC-05 trial with dose-dense immunochemotherapy and early systemic CNS prophylaxis (www.ClinicalTrials.gov, number NCT01325194). Median pretreatment ALC was 1.40 × 109/l (range, 0.20-4.95), AMC 0.68 × 109/l (range, 0.10-2.62), and LMR 2.08 (range, 0.10-12.00). ALC did not correlate with tumor-infiltrating lymphocytes, AMC did not correlate with tumor-associated macrophages, and neither ALC nor AMC correlated with survival. However, low LMR (<1.72) translated to unfavourable progression-free survival (PFS) (5-year PFS 70% vs. 92%, p = 0.002) and overall survival (OS) (5-year OS, 77% vs. 92%, p = 0.020). In the patients with low LMR, relative risk of progression was 4.4-fold (95% confidence interval [CI] 1.60-12.14, p = 0.004), and relative risk of death was 3.3-fold (95% CI 1.18-9.50, p = 0.024) in comparison to the patients with high LMR. We conclude that low LMR is an adverse prognostic factor in uniformly treated young patients with high-risk aggressive large B-cell lymphoma.

Clinical Impact of Immune Cells and Their Spatial Interactions in Diffuse Large B-Cell Lymphoma Microenvironment.

PURPOSE: Tumor-infiltrating immune cells have prognostic significance and are attractive therapeutic targets. Yet, the clinical significance of their spatial organization and phenotype in diffuse large B-cell lymphoma (DLBCL) is unclear. EXPERIMENTAL DESIGN: We characterized T cells, macrophages, and their spatial interactions by multiplex IHC (mIHC) in 178 patients with DLBCL and correlated the data with patient demographics and survival. We validated the findings on gene expression data from two external DLBCL cohorts comprising 633 patients. RESULTS: Macrophage and T-cell contents divided the samples into T cell-inflamed (60%) and noninflamed (40%) subgroups. The T cell-inflamed lymphoma microenvironment (LME) was also rich in other immune cells, defining immune hot phenotype, which did not as such correlate with outcome. However, when we divided the patients according to T-cell and macrophage contents, LME characterized by high T-cell/low macrophage content or a corresponding gene signature was associated with superior survival [5-year overall survival (OS): 92.3% vs. 74.4%, P = 0.036; 5-year progression-free survival (PFS): 92.6% vs. 69.8%, P = 0.012]. High proportion of PD-L1- and TIM3-expressing CD163- macrophages in the T cell-inflamed LME defined a group of patients with poor outcome [OS: HR = 3.22, 95% confidence interval (CI), 1.63-6.37, Padj = 0.011; PFS: HR = 2.76, 95% CI, 1.44-5.28, Padj = 0.016]. Furthermore, PD-L1 and PD-1 were enriched on macrophages interacting with T cells. CONCLUSIONS: Our data demonstrate that the interplay between macrophages and T cells in the DLBCL LME is immune checkpoint dependent and clinically meaningful.

Checkpoint protein expression in the tumor microenvironment defines the outcome of classical Hodgkin lymphoma patients.

Emerging evidence indicates a major impact for the tumor microenvironment (TME) and immune escape in the pathogenesis and clinical course of classical Hodgkin lymphoma (cHL). We used gene expression profiling (n = 88), CIBERSORT, and multiplex immunohistochemistry (n = 131) to characterize the immunoprofile of cHL TME and correlated the findings with survival. Gene expression analysis divided tumors into subgroups with T cell-inflamed and -noninflamed TME. Several macrophage-related genes were upregulated in samples with the non-T cell-inflamed TME, and based on the immune cell proportions, the samples clustered according to the content of T cells and macrophages. A cluster with high proportions of checkpoint protein (programmed cell death protein 1, PD-1 ligands, indoleamine 2,3 dioxygenase 1, lymphocyte-activation gene 3, and T-cell immunoglobulin and mucin domain containing protein 3) positive immune cells translated to unfavorable overall survival (OS) (5-year OS 76% vs 96%; P = .010) and remained an independent prognostic factor for OS in multivariable analysis (HR, 4.34; 95% CI, 1.05-17.91; P = .043). cHL samples with high proportions of checkpoint proteins overexpressed genes coding for cytolytic factors, proposing paradoxically that they were immunologically active. This checkpoint molecule gene signature translated to inferior survival in a validation cohort of 290 diagnostic cHL samples (P < .001) and in an expansion cohort of 84 cHL relapse samples (P = .048). Our findings demonstrate the impact of T cell- and macrophage-mediated checkpoint system on the survival of patients with cHL.

Testicular Diffuse Large B-Cell Lymphoma-Clinical, Molecular, and Immunological Features.

Primary testicular lymphoma is a rare lymphoma entity, yet it is the most common testicular malignancy among elderly men. The majority of the cases represent non-germinal center B-cell-like (non-GCB) diffuse large B-cell lymphoma (DLBCL) with aggressive clinical behavior and a relatively high relapse rate. Due to the rareness of the disease, no randomized clinical trials have been conducted and the currently recognized standard of care is based on retrospective analyses and few phase II trials. During recent years, the tumor microenvironment (TME) and tumor-related immunity have been the focus of many tumor biology studies, and the emergence of targeted therapies and checkpoint inhibitors has significantly modulated the field of cancer therapies. Testicular DLBCL (T-DLBCL) is presented in an immune-privileged site of the testis, and the roles of NF-κB pathway signaling, 9p24.1 aberrations, and tumor-infiltrating immune cells, especially immune checkpoint expressing lymphocytes and macrophages, seem to be unique compared to other lymphoma entities. Preliminary data on the use of immune checkpoint inhibitors in the treatment of T-DLBCL are promising and more studies are ongoing.

MicroRNA in combination with HER2-targeting drugs reduces breast cancer cell viability in vitro.

HER2-positive (HER2 +) breast cancer patients that do not respond to targeted treatment have a poor prognosis. The effects of targeted treatment on endogenous microRNA (miRNA) expression levels are unclear. We report that responsive HER2 + breast cancer cell lines had a higher number of miRNAs with altered expression after treatment with trastuzumab and lapatinib compared to poorly responsive cell lines. To evaluate whether miRNAs can sensitize HER2 + cells to treatment, we performed a high-throughput screen of 1626 miRNA mimics and inhibitors in combination with trastuzumab and lapatinib in HER2 + breast cancer cells. We identified eight miRNA mimics sensitizing cells to targeted treatment, miR-101-5p, mir-518a-5p, miR-19b-2-5p, miR-1237-3p, miR-29a-3p, miR-29c-3p, miR-106a-5p, and miR-744-3p. A higher expression of miR-101-5p predicted better prognosis in patients with HER2 + breast cancer (OS: p = 0.039; BCSS: p = 0.012), supporting the tumor-suppressing role of this miRNA. In conclusion, we have identified miRNAs that sensitize HER2 + breast cancer cells to targeted therapy. This indicates the potential of combining targeted drugs with miRNAs to improve current treatments for HER2 + breast cancers.

miRNA normalization enables joint analysis of several datasets to increase sensitivity and to reveal novel miRNAs differentially expressed in breast cancer.

Different miRNA profiling protocols and technologies introduce differences in the resulting quantitative expression profiles. These include differences in the presence (and measurability) of certain miRNAs. We present and examine a method based on quantile normalization, Adjusted Quantile Normalization (AQuN), to combine miRNA expression data from multiple studies in breast cancer into a single joint dataset for integrative analysis. By pooling multiple datasets, we obtain increased statistical power, surfacing patterns that do not emerge as statistically significant when separately analyzing these datasets. To merge several datasets, as we do here, one needs to overcome both technical and batch differences between these datasets. We compare several approaches for merging and jointly analyzing miRNA datasets. We investigate the statistical confidence for known results and highlight potential new findings that resulted from the joint analysis using AQuN. In particular, we detect several miRNAs to be differentially expressed in estrogen receptor (ER) positive versus ER negative samples. In addition, we identify new potential biomarkers and therapeutic targets for both clinical groups. As a specific example, using the AQuN-derived dataset we detect hsa-miR-193b-5p to have a statistically significant over-expression in the ER positive group, a phenomenon that was not previously reported. Furthermore, as demonstrated by functional assays in breast cancer cell lines, overexpression of hsa-miR-193b-5p in breast cancer cell lines resulted in decreased cell viability in addition to inducing apoptosis. Together, these observations suggest a novel functional role for this miRNA in breast cancer. Packages implementing AQuN are provided for Python and Matlab: https://github.com/YakhiniGroup/PyAQN.

Soluble PD-1 but Not PD-L1 Levels Predict Poor Outcome in Patients with High-Risk Diffuse Large B-Cell Lymphoma.

Interaction of checkpoint receptor programmed death 1 (PD-1) with its ligand 1 (PD-L1) downregulates T cell effector functions and thereby leads to tumor immune escape. Here, we aimed to determine the clinical significance of soluble PD-1 (sPD-1) and soluble PD-L1 (sPD-L1) in patients with diffuse large B-cell lymphoma (DLBCL). We included 121 high-risk DLBCL patients treated in the Nordic NLG-LBC-05 trial with dose-dense immunochemotherapy. sPD-1 and sPD-L1 levels were measured from serum samples collected prior to treatment, after three immunochemotherapy courses, and at the end of therapy. sPD-1 and sPD-L1 levels were the highest in pretreatment samples, declining after three courses, and remaining low post-treatment. Pretreatment sPD-1 levels correlated with the quantities of PD1+ T cells in tumor tissue and translated to inferior survival, while no correlation was observed between sPD-L1 levels and outcome. The relative risk of death was 2.9-fold (95% CI 1.12-7.75, p = 0.028) and the risk of progression was 2.8-fold (95% CI 1.16-6.56, p = 0.021) in patients with high pretreatment sPD-1 levels compared to those with low levels. In conclusion, pretreatment sPD-1 level is a predictor of poor outcome after dose-dense immunochemotherapy and may be helpful in further improving molecular risk profiles in DLBCL.

Immune cell constitution in the tumor microenvironment predicts the outcome in diffuse large B-cell lymphoma.

The tumor microenvironment (TME) and limited immune surveillance play important roles in lymphoma pathogenesis. Here we aimed to characterize immunological profiles of diffuse large B-cell lymphoma (DLBCL) and predict the outcome in response to immunochemotherapy. We profiled the expression of 730 immune-related genes in tumor tissues of 81 patients with DLBCL utilizing the Nanostring platform, and used multiplex immunohistochemistry to characterize T-cell phenotypes, including cytotoxic T cells (CD8, Granzyme B, OX40, Ki67), T-cell immune checkpoint (CD3, CD4, CD8, PD1, TIM3, LAG3), as well as regulatory T-cells and Th1 effector cells (CD3, CD4, FOXP3, TBET) in 188 patients. We observed a high degree of heterogeneity at the transcriptome level. Correlation matrix analysis identified gene expression signatures with highly correlating genes, the main cluster containing genes for cytolytic factors, immune checkpoint molecules, T cells and macrophages, together named a TME immune cell signature. Immunophenotyping of the distinct cell subsets revealed that a high proportion of immune checkpoint positive T cells translated to unfavorable survival. Together, our results demonstrate that the immunological profile of DLBCL TME is heterogeneous and clinically meaningful. This highlights the potential impact of T-cell immune checkpoint in regulating survival and resistance to immunochemotherapy. (Registered at clinicaltrials.gov identifiers: NCT01502982 and NCT01325194.)

Immunogenomic Landscape of Hematological Malignancies.

Understanding factors that shape the immune landscape across hematological malignancies is essential for immunotherapy development. We integrated over 8,000 transcriptomes and 2,000 samples with multilevel genomics of hematological cancers to investigate how immunological features are linked to cancer subtypes, genetic and epigenetic alterations, and patient survival, and validated key findings experimentally. Infiltration of cytotoxic lymphocytes was associated with TP53 and myelodysplasia-related changes in acute myeloid leukemia, and activated B cell-like phenotype and interferon-γ response in lymphoma. CIITA methylation regulating antigen presentation, cancer type-specific immune checkpoints, such as VISTA in myeloid malignancies, and variation in cancer antigen expression further contributed to immune heterogeneity and predicted survival. Our study provides a resource linking immunology with cancer subtypes and genomics in hematological malignancies.

Adverse prognostic impact of regulatory T-cells in testicular diffuse large B-cell lymphoma.

OBJECTIVES: Testicular diffuse large B-cell lymphoma (T-DLBCL) is a rare and aggressive extranodal lymphoma. We have previously shown that high content of tumor-infiltrating lymphocytes (TILs) and PD-1 expressing TILs associate with better survival in T-DLBCL. In this study, we have further characterized distinct TIL subtypes and their proportions in association with patient demographics and survival. METHODS: We used multiplex immunohistochemistry to characterize TIL phenotypes, including cytotoxic T-cells (CTLs; CD8+ , OX40+ , Granzyme B+ , Ki-67+ , LAG-3+ , TIM-3+ , PD-1+ ), CD4+ T-cells (CD3+ , CD4+ , TIM-3+ , LAG-3+ ), regulatory T-cells (Tregs; CD3+ , CD4+ , FoxP3+ ), and T helper 1 cells (Th1; CD3+ , CD4+ , T-bet+ ) in 79 T-DLBCLs, and correlated the findings with patient demographics and outcome. RESULTS: We observed a substantial variation in TIL phenotypes between the patients. The most prominent CD8+ TILs were Ki-67+ and TIM-3+ CTLs, whereas the most prominent CD4+ TILs were FoxP3+ Tregs. Despite the overall favorable prognostic impact of high TIL content, we found a subpopulation of T-bet+ FoxP3+ Tregs that had a significant adverse impact on survival. Lower content of CTLs with activated or exhausted phenotypes correlated with aggressive clinical features. CONCLUSIONS: Our results demonstrate significant variation in TIL phenotypes and emphasize the adverse prognostic impact of Tregs in T-DLBCL.

Prognostic Impact of Tumor-Associated Macrophages on Survival Is Checkpoint Dependent in Classical Hodgkin Lymphoma.

Tumor microenvironment and immune escape affect pathogenesis and survival in classical Hodgkin lymphoma (cHL). While tumor-associated macrophage (TAM) content has been associated with poor outcomes, macrophage-derived determinants with clinical impact have remained undefined. Here, we have used multiplex immunohistochemistry and digital image analysis to characterize TAM immunophenotypes with regard to expression of checkpoint molecules programmed cell death ligand 1 (PD-L1) and indoleamine 2,3-dioxygenase 1 (IDO-1) from the diagnostic tumor tissue samples of 130 cHL patients, and correlated the findings with clinical characteristics and survival. We show that a large proportion of TAMs express PD-L1 (CD68+, median 32%; M2 type CD163+, median 22%), whereas the proportion of TAMs expressing IDO-1 is lower (CD68+, median 5.5%; CD163+, median 1.4%). A high proportion of PD-L1 and IDO-1 expressing TAMs from all TAMs (CD68+), or from CD163+ TAMs, is associated with inferior outcome. In multivariate analysis with age and stage, high proportions of PD-L1+ and IDO-1+ TAMs remain independent prognostic factors for freedom from treatment failure (PD-L1+CD68+/CD68+, HR = 2.63, 95% CI 1.17-5.88, p = 0.019; IDO-1+CD68+/CD68+, HR = 2.48, 95% CI 1.03-5.95, p = 0.042). In contrast, proportions of PD-L1+ tumor cells, all TAMs or PD-L1- and IDO-1- TAMs are not associated with outcome. The findings implicate that adverse prognostic impact of TAMs is checkpoint-dependent in cHL.

Drug screening approach combines epigenetic sensitization with immunochemotherapy in cancer.

BACKGROUND: The epigenome plays a key role in cancer heterogeneity and drug resistance. Hence, a number of epigenetic inhibitors have been developed and tested in cancers. The major focus of most studies so far has been on the cytotoxic effect of these compounds, and only few have investigated the ability to revert the resistant phenotype in cancer cells. Hence, there is a need for a systematic methodology to unravel the mechanisms behind epigenetic sensitization. RESULTS: We have developed a high-throughput protocol to screen non-simultaneous drug combinations, and used it to investigate the reprogramming potential of epigenetic inhibitors. We demonstrated the effectiveness of our protocol by screening 60 epigenetic compounds on diffuse large B-cell lymphoma (DLBCL) cells. We identified several histone deacetylase (HDAC) and histone methyltransferase (HMT) inhibitors that acted synergistically with doxorubicin and rituximab. These two classes of epigenetic inhibitors achieved sensitization by disrupting DNA repair, cell cycle, and apoptotic signaling. The data used to perform these analyses are easily browsable through our Results Explorer. Additionally, we showed that these inhibitors achieve sensitization at lower doses than those required to induce cytotoxicity. CONCLUSIONS: Our drug screening approach provides a systematic framework to test non-simultaneous drug combinations. This methodology identified HDAC and HMT inhibitors as successful sensitizing compounds in treatment-resistant DLBCL. Further investigation into the mechanisms behind successful epigenetic sensitization highlighted DNA repair, cell cycle, and apoptosis as the most dysregulated pathways. Altogether, our method adds supporting evidence in the use of epigenetic inhibitors as sensitizing agents in clinical settings.

Distinct subtypes of diffuse large B-cell lymphoma defined by hypermutated genes.

Diffuse large B-cell lymphoma (DLBCL) is a biologically and clinically heterogeneous disease whose personalized clinical management requires robust molecular stratification. Here, we show that somatic hypermutation (SHM) patterns constitute a marker for DLBCL molecular classification. The activity of SHM mutational processes delineated the cell of origin (COO) in DLBCL. Expression of the herein identified 36 SHM target genes stratified DLBCL into four novel SHM subtypes. In a meta-analysis of patients with DLBCL treated with immunochemotherapy, the SHM subtypes were significantly associated with overall survival (1642 patients) and progression-free survival (795 patients). Multivariate analysis of survival indicated that the prognostic impact of the SHM subtypes is independent from the COO classification and the International Prognostic Index. Furthermore, the SHM subtypes had a distinct clinical outcome within each of the COO subtypes, and strikingly, even within unclassified DLBCL. The genetic landscape of the four SHM subtypes indicated unique associations with driver alterations and oncogenic signaling in DLBCL, which suggests a possibility for therapeutic exploitation. These findings provide a biologically driven classification system in DLBCL with potential clinical applications.