Association between parity and pregnancy-associated tumor features in high-grade serous ovarian cancer.

PURPOSE: High-grade serous ovarian cancer (HGSC) is the most common ovarian cancer subtype. Parity is an important risk-reducing factor, but the underlying mechanism behind the protective effect is unclear. Our aim was to study if the expression of hormones and proteins involved in pregnancy were affected by the woman's parity status, and if they may be associated with tumor stage and survival. METHODS: We evaluated expression of progesterone receptor (PR), progesterone receptor membrane component 1 (PGRMC1), relaxin-2, and transforming growth factor beta 1 (TGFß1) in tumor tissue from 92 women with HGSC parous (n = 73) and nulliparous (n = 19). Key findings were then evaluated in an independent expansion cohort of 49 patients. Survival rates by hormone/protein expression were illustrated using the Kaplan-Meier method. The independent prognostic value was tested by Cox regression, using models adjusted for established poor-prognostic factors (age at diagnosis, FIGO stage, type of surgery, and macroscopic residual tumor after surgery). RESULTS: HGSC tumors from parous women were PR positive (≥ 1% PR expression in tumor cells) more often than tumors from nulliparous women (42% vs. 16%; p-value 0.04), and having more children was associated with developing PR positive tumors [i.e., ≥ 3 children versus nulliparity, adjusted for age at diagnosis and stage: OR 4.31 (95% CI 1.12-19.69)]. A similar result was seen in the expansion cohort. Parity status had no impact on expression of PGRMC1, relaxin-2 and TGFß1. No associations were seen with tumor stage or survival. CONCLUSION: Tumors from parous women with HGSC expressed PR more often than tumors from nulliparous women, indicating that pregnancies might possibly have a long-lasting impact on ovarian cancer development.

Improved automated tumor segmentation in whole-body 3D scans using multi-directional 2D projection-based priors.

Early cancer detection, guided by whole-body imaging, is important for the overall survival and well-being of the patients. While various computer-assisted systems have been developed to expedite and enhance cancer diagnostics and longitudinal monitoring, the detection and segmentation of tumors, especially from whole-body scans, remain challenging. To address this, we propose a novel end-to-end automated framework that first generates a tumor probability distribution map (TPDM), incorporating prior information about the tumor characteristics (e.g. size, shape, location). Subsequently, the TPDM is integrated with a state-of-the-art 3D segmentation network along with the original PET/CT or PET/MR images. This aims to produce more meaningful tumor segmentation masks compared to using the baseline 3D segmentation network alone. The proposed method was evaluated on three independent cohorts (autoPET, CAR-T, cHL) of images containing different cancer forms, obtained with different imaging modalities, and acquisition parameters and lesions annotated by different experts. The evaluation demonstrated the superiority of our proposed method over the baseline model by significant margins in terms of Dice coefficient, and lesion-wise sensitivity and precision. Many of the extremely small tumor lesions (i.e. the most difficult to segment) were missed by the baseline model but detected by the proposed model without additional false positives, resulting in clinically more relevant assessments. On average, an improvement of 0.0251 (autoPET), 0.144 (CAR-T), and 0.0528 (cHL) in overall Dice was observed. In conclusion, the proposed TPDM-based approach can be integrated with any state-of-the-art 3D UNET with potentially more accurate and robust segmentation results.

Long-Term Follow-Up of the Response-Adjusted Therapy for Advanced Hodgkin Lymphoma Trial.

Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported.We analyzed long-term results of the response-adapted trial for adult patients with advanced-stage Hodgkin lymphoma. The aim was to confirm noninferiority of treatment de-escalation by omission of bleomycin from doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) for interim fluorodeoxyglucose positron emission tomography (iPET)-negative patients and assess efficacy and long-term safety for iPET-positive patients who underwent treatment intensification with escalated bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisolone (BEACOPP/BEACOPP14). The median follow-up is 7.3 years. For all patients, the 7-year progression-free survival (PFS) and overall survival (OS) are 78.2% (95% CI, 75.6 to 80.5) and 91.6% (95% CI, 89.7 to 93.2), respectively. The 1.3% difference in 3-year PFS (95% CI, -3.0 to 4.7) between ABVD and doxorubicin, vinblastine, and dacarbazine (AVD) now falls within the predefined noninferiority margin. Among 172 patients with positive iPET, the 7-year PFS was 65.9% (95% CI, 58.1 to 72.6) and the 7-year OS was 83.2% (95% CI, 76.2 to 88.3). The cumulative incidence of second malignancies at 7 years was 5.5% (95% CI, 4.0 to 7.5) for those receiving ABVD/AVD and 2.5% (95% CI, 0.8 to 7.7) for those escalated to BEACOPP. With extended follow-up, these results confirm noninferiority of treatment de-escalation after a negative iPET. Escalation with BEACOPP for iPET-positive patients is effective and safe, with no increase in second malignancies.

Genetic and transcriptomic analyses of diffuse large B-cell lymphoma patients with poor outcomes within two years of diagnosis.

Despite the improvements in clinical outcomes for DLBCL, a significant proportion of patients still face challenges with refractory/relapsed (R/R) disease after receiving first-line R-CHOP treatment. To further elucidate the underlying mechanism of R/R disease and to develop methods for identifying patients at risk of early disease progression, we integrated clinical, genetic and transcriptomic data derived from 2805 R-CHOP-treated patients from seven independent cohorts. Among these, 887 patients exhibited R/R disease within two years (poor outcome), and 1918 patients remained in remission at two years (good outcome). Our analysis identified four preferentially mutated genes (TP53, MYD88, SPEN, MYC) in the untreated (diagnostic) tumor samples from patients with poor outcomes. Furthermore, transcriptomic analysis revealed a distinct gene expression pattern linked to poor outcomes, affecting pathways involved in cell adhesion/migration, T-cell activation/regulation, PI3K, and NF-κB signaling. Moreover, we developed and validated a 24-gene expression score as an independent prognostic predictor for treatment outcomes. This score also demonstrated efficacy in further stratifying high-risk patients when integrated with existing genetic or cell-of-origin subtypes, including the unclassified cases in these models. Finally, based on these findings, we developed an online analysis tool ( https://lymphprog.serve.scilifelab.se/app/lymphprog ) that can be used for prognostic prediction for DLBCL patients.

Strict self-isolation did not protect Swedish cancer patients on active treatment from the risk of becoming seropositive for SARS-CoV-2.

BACKGROUND: Swedish recommendations to reduce the risk of COVID-19 relied on each citizen's own sense of responsibility rather than mandatory lockdowns. We studied how COVID-19-related self-isolation and anxiety correlated to SARS-CoV-2 seropositivity and PCR-positivity in patients with active cancer treatment. METHODS: In a longitudinal cohort study at Uppsala University Hospital patients and cancer personnel were included between April 1st 2020 to August 1st 2020. Serological testing for SARS-CoV-2 was done every 8-12-weeks until 30 March 2021. Patients completed a survey at inclusion regarding self-reported COVID-19-related anxiety and self-isolation. RESULTS: A total of 622 patients [n = 475 with solid malignancies (SM), n = 147 with haematological malignancies (HM)], and 358 healthcare personnel were included. The seropositivity rate was lower for patients than for personnel; 10.5% for SM patients, 6.8% for HM patients, and 16.2% for personnel (p = 0.005). Strict adherence to self-isolation guidelines was reported by 54% of patients but was not associated with a lower risk of becoming seropositive [OR = 1.4 (0.8-2.5), p = 0.2]. High anxiety was expressed by 32% of patients, more often by SM patients than HM patients (34% vs 25% [OR = 1.6 (1.1-2.5, p = 0.03)]). Female gender [OR = 3.5 (2.4-5.2), p < 0.001] and being born outside of Europe [OR = 2.9 (1.4-6.4), p = 0.007] were both associated with high anxiety. Patients reporting high anxiety became seropositive to a similar degree as those with low anxiety [OR = 0.7 (0.3-1.2), p = 0.2]. HM patients with PCR-positive COVID-19 were more likely than SM patients to require oxygen therapy, including non-invasive ventilation/intubation (69% vs. 26%, p = 0.005). CONCLUSION: For Swedish patients on active cancer treatment, high self-assessed COVID-19-related anxiety or strict adherence to self-isolation guidelines were not associated with a lower risk of COVID-19. Patients with HM were less likely to develop serological antibody response after COVID-19 and were more likely to require advanced hospital care, but expressed less COVID-19-related anxiety than patients with SM.

A whole-body diffusion MRI normal atlas: development, evaluation and initial use.

BACKGROUND: Statistical atlases can provide population-based descriptions of healthy volunteers and/or patients and can be used for region- and voxel-based analysis. This work aims to develop whole-body diffusion atlases of healthy volunteers scanned at 1.5T and 3T. Further aims include evaluating the atlases by establishing whole-body Apparent Diffusion Coefficient (ADC) values of healthy tissues and including healthy tissue deviations in an automated tumour segmentation task. METHODS: Multi-station whole-body Diffusion Weighted Imaging (DWI) and water-fat Magnetic Resonance Imaging (MRI) of healthy volunteers (n = 45) were acquired at 1.5T (n = 38) and/or 3T (n = 29), with test-retest imaging for five subjects per scanner. Using deformable image registration, whole-body MRI data was registered and composed into normal atlases. Healthy tissue ADCmean was manually measured for ten tissues, with test-retest percentage Repeatability Coefficient (%RC), and effect of age, sex and scanner assessed. Voxel-wise whole-body analyses using the normal atlases were studied with ADC correlation analyses and an automated tumour segmentation task. For the latter, lymphoma patient MRI scans (n = 40) with and without information about healthy tissue deviations were entered into a 3D U-Net architecture. RESULTS: Sex- and Body Mass Index (BMI)-stratified whole-body high b-value DWI and ADC normal atlases were created at 1.5T and 3T. %RC of healthy tissue ADCmean varied depending on tissue assessed (4-48% at 1.5T, 6-70% at 3T). Scanner differences in ADCmean were visualised in Bland-Altman analyses of dually scanned subjects. Sex differences were measurable for liver, muscle and bone at 1.5T, and muscle at 3T. Volume of Interest (VOI)-based multiple linear regression, and voxel-based correlations in normal atlas space, showed that age and ADC were negatively associated for liver and bone at 1.5T, and positively associated with brain tissue at 1.5T and 3T. Adding voxel-wise information about healthy tissue deviations in an automated tumour segmentation task gave numerical improvements in the segmentation metrics Dice score, sensitivity and precision. CONCLUSIONS: Whole-body DWI and ADC normal atlases were created at 1.5T and 3T, and applied in whole-body voxel-wise analyses.

Single-Cell RNA Analysis Reveals Cell-Intrinsic Functions of CAR T Cells Correlating with Response in a Phase II Study of Lymphoma Patients.

PURPOSE: Although CD19 chimeric antigen receptor T cells (CAR-T) therapy has shown remarkable success in B-cell malignancies, a substantial fraction of patients do not obtain a long-term clinical response. This could be influenced by the quality of the individual CAR-T infusion product. To shed some light on this, clinical outcome was correlated to characteristics of CAR-T infusion products. PATIENTS AND METHODS: In this phase II study, patients with B-cell lymphoma (n = 23) or leukemia (n = 1) received one or two infusions of third-generation CD19-directed CAR-Ts (2 × 108/m2). The clinical trial was registered at clinicaltrials.gov: NCT03068416. We investigated the transcriptional profile of individual CD19 CAR-T infusion products using targeted single-cell RNA sequencing and multicolor flow cytometry. RESULTS: Two CAR-T infusions were not better than one in the settings used in this study. As for the CAR-T infusion products, we found that effector-like CD8+CAR-Ts with a high polyfunctionality, high cytotoxic and cytokine production profile, and low dysfunctional signature were associated with clinical response. An extended ex vivo expansion time during CAR-T manufacturing negatively influenced the proportion of effector CD8+CAR-Ts in the infusion product. CONCLUSIONS: We identified cell-intrinsic characteristics of effector CD8+CAR-Ts correlating with response that could be used as an indicator for clinical outcome. The results in the study also serve as a guide to CAR-T manufacturing practices.

Next generation pan-cancer blood proteome profiling using proximity extension assay.

A comprehensive characterization of blood proteome profiles in cancer patients can contribute to a better understanding of the disease etiology, resulting in earlier diagnosis, risk stratification and better monitoring of the different cancer subtypes. Here, we describe the use of next generation protein profiling to explore the proteome signature in blood across patients representing many of the major cancer types. Plasma profiles of 1463 proteins from more than 1400 cancer patients are measured in minute amounts of blood collected at the time of diagnosis and before treatment. An open access Disease Blood Atlas resource allows the exploration of the individual protein profiles in blood collected from the individual cancer patients. We also present studies in which classification models based on machine learning have been used for the identification of a set of proteins associated with each of the analyzed cancers. The implication for cancer precision medicine of next generation plasma profiling is discussed.

Soluble CD163 predicts outcome in both chemoimmunotherapy and targeted therapy-treated mantle cell lymphoma.

The outcome for patients with mantle cell lymphoma (MCL) has drastically improved with new treatments directed toward the tumor immune microenvironment, where macrophages play an important role. In MCL, the presence of M2 macrophages defined by CD163 expression in diagnostic biopsies has been associated with a worse prognosis. An alternative way to assess the abundance of M2 macrophages is by measuring the level of soluble CD163 in serum (sCD163). We aimed to investigate the prognostic value of sCD163 in 131 patients with MCL. We found that high sCD163 at diagnosis was associated with shorter progression-free survival (PFS) and shorter overall survival (OS) in 81 patients who were newly diagnosed and subsequently treated with chemoimmunotherapy. The same was seen in a cohort of 50 patients with relapsed MCL that were mainly treated within the phase 2 Philemon-trial with rituximab, ibrutinib, and lenalidomide. In patients who were newly diagnosed and had low levels of sCD163, 5-year survival was 97%. There was a moderate correlation between sCD163 and tissue CD163. The association with a poor prognosis was independent of MCL international prognostic index, Ki67, p53 status, and blastoid morphology, as assessed in a multivariable Cox proportional hazards model. In this study, high sCD163 was associated with both shorter PFS and shorter OS, showing that high levels of the M2 macrophage marker sCD163 is an independent negative prognostic factor in MCL, both in the chemoimmunotherapy and ibrutinib/lenalidomide era. In addition, low sCD163 levels identify patients with MCL with a very good prognosis.

ADAR1-mediated RNA editing promotes B cell lymphomagenesis.

Diffuse large B cell lymphoma (DLBCL) is one of the most common types of aggressive lymphoid malignancies. Here, we explore the contribution of RNA editing to DLBCL pathogenesis. We observed that DNA mutations and RNA editing events are often mutually exclusive, suggesting that tumors can modulate pathway outcomes by altering sequences at either the genomic or the transcriptomic level. RNA editing targets transcripts within known disease-driving pathways such as apoptosis, p53 and NF-κB signaling, as well as the RIG-I-like pathway. In this context, we show that ADAR1-mediated editing within MAVS transcript positively correlates with MAVS protein expression levels, associating with increased interferon/NF-κB signaling and T cell exhaustion. Finally, using targeted RNA base editing tools to restore editing within MAVS 3'UTR in ADAR1-deficient cells, we demonstrate that editing is likely to be causal to an increase in downstream signaling in the absence of activation by canonical nucleic acid receptor sensing.

Tumor-activated lymph node fibroblasts suppress T cell function in diffuse large B cell lymphoma.

Recent transcriptomic-based analysis of diffuse large B cell lymphoma (DLBCL) has highlighted the clinical relevance of LN fibroblast and tumor-infiltrating lymphocyte (TIL) signatures within the tumor microenvironment (TME). However, the immunomodulatory role of fibroblasts in lymphoma remains unclear. Here, by studying human and mouse DLBCL-LNs, we identified the presence of an aberrantly remodeled fibroblastic reticular cell (FRC) network expressing elevated fibroblast-activated protein (FAP). RNA-Seq analyses revealed that exposure to DLBCL reprogrammed key immunoregulatory pathways in FRCs, including a switch from homeostatic to inflammatory chemokine expression and elevated antigen-presentation molecules. Functional assays showed that DLBCL-activated FRCs (DLBCL-FRCs) hindered optimal TIL and chimeric antigen receptor (CAR) T cell migration. Moreover, DLBCL-FRCs inhibited CD8+ TIL cytotoxicity in an antigen-specific manner. Notably, the interrogation of patient LNs with imaging mass cytometry identified distinct environments differing in their CD8+ TIL-FRC composition and spatial organization that associated with survival outcomes. We further demonstrated the potential to target inhibitory FRCs to rejuvenate interacting TILs. Cotreating organotypic cultures with FAP-targeted immunostimulatory drugs and a bispecific antibody (glofitamab) augmented antilymphoma TIL cytotoxicity. Our study reveals an immunosuppressive role of FRCs in DLBCL, with implications for immune evasion, disease pathogenesis, and optimizing immunotherapy for patients.

Survival by First-line Treatment Type and Timing of Progression Among Follicular Lymphoma Patients: A National Population-based Study in Sweden.

In follicular lymphoma (FL), progression of disease ≤24 months (POD24) has emerged as an important prognostic marker for overall survival (OS). We aimed to investigate survival more broadly by timing of progression and treatment in a national population-based setting. We identified 948 stage II-IV indolent FL patients in the Swedish Lymphoma Register diagnosed 2007-2014 who received first-line systemic therapy, followed through 2020. Hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated by first POD at any time during follow-up using Cox regression. OS was predicted by POD using an illness-death model. During a median follow-up of 6.1 years (IQR: 3.5-8.4), 414 patients experienced POD (44%), of which 270 (65%) occurred ≤24 months. POD was represented by a transformation in 15% of cases. Compared to progression-free patients, POD increased all-cause mortality across treatments, but less so among patients treated with rituximab(R)-single (HR = 4.54, 95% CI: 2.76-7.47) than R-chemotherapy (HR = 8.17, 95% CI: 6.09-10.94). The effect of POD was similar following R-CHOP (HR = 8.97, 95% CI: 6.14-13.10) and BR (HR = 10.29, 95% CI: 5.60-18.91). The negative impact of POD on survival remained for progressions up to 5 years after R-chemotherapy, but was restricted to 2 years after R-single. After R-chemotherapy, the 5-year OS conditional on POD occurring at 12, 24, and 60 months was 34%, 46%, and 57% respectively, versus 78%, 82%, and 83% if progression-free. To conclude, POD before but also beyond 24 months is associated with worse survival, illustrating the need for individualized management for optimal care of FL patients.

Sex- and Female Age-Dependent Differences in Gene Expression in Diffuse Large B-Cell Lymphoma-Possible Estrogen Effects.

For most lymphomas, including diffuse large B-cell lymphoma (DLBCL), the male incidence is higher, and the prognosis is worse compared to females. The reasons are unclear; however, epidemiological and experimental data suggest that estrogens are involved. With this in mind, we analyzed gene expression data from a publicly available cohort (EGAD00001003600) of 746 DLBCL samples based on RNA sequencing. We found 1293 genes to be differentially expressed between males and females (adj. p-value < 0.05). Few autosomal genes and pathways showed common sex-regulated expression between germinal center B-cell (GCB) and activated B-cell lymphoma (ABC) DLBCL. Analysis of differentially expressed genes between pre- vs. postmenopausal females identified 208 GCB and 345 ABC genes, with only 5 being shared. When combining the differentially expressed genes between females vs. males and pre- vs. postmenopausal females, nine putative estrogen-regulated genes were identified in ABC DLBCL. Two of them, NR4A2 and MUC5B, showed induced and repressed expression, respectively. Interestingly, NR4A2 has been reported as a tumor suppressor in lymphoma. We show that ABC DLBCL females with a high NR4A2 expression showed better survival. Inversely, MUC5B expression causes a more malignant phenotype in several cancers. NR4A2 and MUC5B were confirmed to be estrogen-regulated when the ABC cell line U2932 was grafted to mice. The results demonstrate sex- and female reproductive age-dependent differences in gene expression between DLBCL subtypes, likely due to estrogens. This may contribute to the sex differences in incidence and prognosis.

Whole body FDG PET/MR for progression free and overall survival prediction in patients with relapsed/refractory large B-cell lymphomas undergoing CAR T-cell therapy.

BACKGROUND: To find semi-quantitative and quantitative Positron Emission Tomography/Magnetic Resonance (PET/MR) imaging metrics of both tumor and non-malignant lymphoid tissue (bone marrow and spleen) for Progression Free Survival (PFS) and Overall Survival (OS) prediction in patients with relapsed/refractory (r/r) large B-cell lymphoma (LBCL) undergoing Chimeric Antigen Receptor (CAR) T-cell therapy. METHODS: A single-center prospective study of 16 r/r LBCL patients undergoing CD19-targeted CAR T-cell therapy. Whole body 18F-fluorodeoxyglucose (FDG) PET/MR imaging pre-therapy and 3 weeks post-therapy were followed by manual segmentation of tumors and lymphoid tissues. Semi-quantitative and quantitative metrics were extracted, and the metric-wise rate of change (Δ) between post-therapy and pre-therapy calculated. Tumor metrics included maximum Standardized Uptake Value (SUVmax), mean SUV (SUVmean), Metabolic Tumor Volume (MTV), Tumor Lesion Glycolysis (TLG), structural volume (V), total structural tumor burden (Vtotal) and mean Apparent Diffusion Coefficient (ADCmean). For lymphoid tissues, metrics extracted were SUVmean, mean Fat Fraction (FFmean) and ADCmean for bone marrow, and SUVmean, V and ADCmean for spleen. Univariate Cox regression analysis tested the relationship between extracted metrics and PFS and OS. Survival curves were produced using Kaplan-Meier analysis and compared using the log-rank test, with the median used for dichotomization. Uncorrected p-values < 0.05 were considered statistically significant. Correction for multiple comparisons was performed, with a False Discovery Rate (FDR) < 0.05 considered statistically significant. RESULTS: Pre-therapy (p < 0.05, FDR < 0.05) and Δ (p < 0.05, FDR > 0.05) total tumor burden structural and metabolic metrics were associated with PFS and/or OS. According to Kaplan-Meier analysis, a longer PFS was reached for patients with pre-therapy MTV ≤ 39.5 ml, ΔMTV≤1.35 and ΔTLG≤1.35. ΔSUVmax was associated with PFS (p < 0.05, FDR > 0.05), while ΔADCmean was associated with both PFS and OS (p < 0.05, FDR > 0.05). ΔADCmean > 0.92 gave longer PFS and OS in the Kaplan-Meier analysis. Pre-therapy bone marrow SUVmean was associated with PFS (p < 0.05, FDR < 0.05) and OS (p < 0.05, FDR > 0.05). For bone marrow FDG uptake, patient stratification was possible pre-therapy (SUVmean ≤ 1.8). CONCLUSIONS: MTV, tumor ADCmean and FDG uptake in bone marrow unaffected by tumor infiltration are possible PET/MR parameters for prediction of PFS and OS in r/r LBCL treated with CAR T-cells. TRIAL REGISTRATION: EudraCT 2016-004043-36.

Noninvasive detection of any-stage cancer using free glycosaminoglycans.

Cancer mortality is exacerbated by late-stage diagnosis. Liquid biopsies based on genomic biomarkers can noninvasively diagnose cancers. However, validation studies have reported ~10% sensitivity to detect stage I cancer in a screening population and specific types, such as brain or genitourinary tumors, remain undetectable. We investigated urine and plasma free glycosaminoglycan profiles (GAGomes) as tumor metabolism biomarkers for multi-cancer early detection (MCED) of 14 cancer types using 2,064 samples from 1,260 cancer or healthy subjects. We observed widespread cancer-specific changes in biofluidic GAGomes recapitulated in an in vivo cancer progression model. We developed three machine learning models based on urine (Nurine = 220 cancer vs. 360 healthy) and plasma (Nplasma = 517 vs. 425) GAGomes that can detect any cancer with an area under the receiver operating characteristic curve of 0.83-0.93 with up to 62% sensitivity to stage I disease at 95% specificity. Undetected patients had a 39 to 50% lower risk of death. GAGomes predicted the putative cancer location with 89% accuracy. In a validation study on a screening-like population requiring ≥ 99% specificity, combined GAGomes predicted any cancer type with poor prognosis within 18 months with 43% sensitivity (21% in stage I; N = 121 and 49 cases). Overall, GAGomes appeared to be powerful MCED metabolic biomarkers, potentially doubling the number of stage I cancers detectable using genomic biomarkers.

The dual role of CD70 in B-cell lymphomagenesis.

BACKGROUND: CD70 is a costimulatory molecule that is transiently expressed on a small set of activated lymphocytes and is involved in T-cell-mediated immunity. However, the role of CD70 in B-cell malignancies remains controversial. METHODS: We investigated the clinical relevance of CD70 genetic alterations and its protein expression in two diffuse large B-cell lymphoma (DLBCL) cohorts with different ethnic backgrounds. We also performed transcriptomic analysis to explore the role of CD70 alterations in tumour microenvironment. We further tested the blockade of CD70 in combination with PD-L1 inhibitor in a murine lymphoma model. RESULTS: We showed that CD70 genetic aberrations occurred more frequently in the Chinese DLBCL cohort (56/233, 24.0%) than in the Swedish cohort (9/84, 10.8%), especially in those with concomitant hepatitis B virus (HBV) infection. The CD70 genetic changes in DLBCL resulted in a reduction/loss of protein expression and/or CD27 binding, which might impair T cell priming and were independently associated with poor overall survival. Paradoxically, we observed that over-expression of CD70 protein was also associated with a poor treatment response, as well as an advanced disease stage and EBV infection. More exhausted CD8+ T cells were furthermore identified in CD70 high-expression DLBCLs. Finally, in a murine lymphoma model, we demonstrated that blocking the CD70/CD27 and/or PD1/PD-L1 interactions could reduce CD70+ lymphoma growth in vivo, by directly impairing the tumour cell proliferation and rescuing the exhausted T cells. CONCLUSIONS: Our findings suggest that CD70 can play a role in either tumour suppression or oncogenesis in DLBCL, likely via distinct immune evasion mechanisms, that is, impairing T cell priming or inducing T cell exhaustion. Characterisation of specific dysfunction of CD70 in DLBCL may thus provide opportunities for the development of novel targeted immuno-therapeutic strategies.

Donor-derived urologic cancers after renal transplantation: A retrospective non-randomized scientific analysis.

BACKGROUND: Malignancies in the urinary tract and the kidney graft are quite common after kidney transplantation. In some selected cases tumours develop from donor-derived tissue. OBJECTIVES: We hypothesised that there is a clinical value to investigate donor/recipient origin in urologic malignancies in renal transplant recipients. METHODS: In this retrospective study, including patients transplanted between the years 1969 and 2014 at Uppsala University Hospital, Sweden, 11 patients with malignancies in urinary tract and 4 patients with malignancies in kidney transplants were investigated. Donor/recipient origin of tumour tissue was analysed by polymerase chain reaction (PCR) of human leucocyte antigen (HLA) genotypes or by fluorescence in situ hybridization (FISH analysis) of sex chromosomes. HLA genotype and sex chromosomes of the tumour were compared to the known HLA genotype and sex chromosomes of recipient and donor. RESULTS: Three of ten cancers in the urinary tract and three of four cancers in the kidney transplants were donor-derived. CONCLUSIONS: We suggest that urologic malignancies in renal transplant recipients can be investigated for transplant origin. In addition to conventional therapy the allograft immune response against these tumours can be valuable to treat donor-derived cancers.

Plasma protein biomarker profiling reveals major differences between acute leukaemia, lymphoma patients and controls.

Aiming to accommodate the unmet need for easily accessible biomarkers with a focus on biological differences between haematological diseases, the diagnostic value of plasma proteins in acute leukaemias and lymphomas was investigated. A multiplex proximity extension assay (PEA) was used to analyze 183 proteins in diagnostic plasma samples from 251 acute leukaemia and lymphoma patients and compared with samples from 60 healthy controls. Multivariate modelling using partial least square discriminant analysis revealed highly significant differences between distinct disease subgroups and controls. The model allowed explicit distinction between leukaemia and lymphoma, with few patients misclassified. Acute leukaemia samples had higher levels of proteins associated with haemostasis, inflammation, cell differentiation and cell-matrix integration, whereas lymphoma samples demonstrated higher levels of proteins known to be associated with tumour microenvironment and lymphoma dissemination. PEA technology can be used to screen for large number of plasma protein biomarkers in low µL sample volumes, enabling the distinction between controls, acute leukaemias and lymphomas. Plasma protein profiling could help gain insights into the pathophysiology of acute leukaemia and lymphoma and the technique may be a valuable tool in the diagnosis of these diseases.