Introduction The application of circulating cell-free DNA (cfDNA) has attracted recent interest for cancer detection and monitoring. The presence of somatic copy number alterations (SCNAs) can be used to differentiate between cancer cases and healthy controls (PMID: 29109393). This information can be retrieved from low-coverage whole genome sequencing (lcWGS) and used to determine the proportion of tumor derived cfDNA (ctDNA) in a tube of blood at a reasonable cost. Previous studies observed that cancer patients tend to have a higher fraction of shorter cfDNA fragments compared to healthy controls, irrespective of the presence of genomic events (PMID: 30404863). Here, we evaluate if a combination of cfDNA genomic and epigenomic features that can be retrieved from a single run of lcWGS, has potential for the early prediction of end of induction (EoI) response, in patients with high-grade lymphoma with MYC and BCL2 and/or BLC6 rearrangements (HGBL-DH/TH). Methods In the HOVON-152 phase II trial (NCT03620578) HGBL-DH/TH patients were treated with induction immunochemotherapy with one cycle of R-CHOP followed by five cycles of DA-EPOCH-R. Patients in complete metabolic response (CMR, defined as Deauville score 1-3) at the end of induction receive 1-year nivolumab consolidation. Blood was collected from 40 patients using PAXgene ccfDNA tubes after one cycle (timepoint 1, T1), three (T2) and six (T3) cycles of treatment. At T3, response to induction treatment was determined using 18F-FDG-PET scan. Patients with CMR at EoI were considered responders. In this study, we included 40 out of 97 patients from the HOVON-152 phase II trial, and enriched for patients with no CMR. Plasma was separated using dual centrifugation protocol, and cfDNA was isolated using the QIASymphony kit (QIAGEN). Sequencing libraries were prepared using the ThruPLEX Plasma-seq kit (Takara). lcWGS was performed on a Novaseq 6000 (Illumina). Somatic copy number aberrations (SCNAs) were retrieved with ichorCNA, insert size profiles were generated using Picard tools. SCNAs were classified as detected when the tumor fraction quantified with ichorCNA exceeded 3%. Results We assessed the detection of SCNAs and the SCNA-derived tumor fraction using the ichorCNA software. The ctDNA tumor fraction was found to be significantly increased in non-responders (NR, n=24) compared to responders (R, n=16), irrespective of sampling timepoint (Wilcoxon, p<0.001). At T1, the tumor fraction was significantly elevated in non-responders (Wilcoxon, p=0.014), and SCNAs were detected in 6/16 (38%) of the responders versus 19/24 (79%) of the non-responders, with negative predictive value (NPV): 71%, positive predictive value (PPV): 74%. Therefore, non-responders tend to have a higher fraction of tumor-derived signal which is already apparent at earlier timepoints. To evaluate the potential of using cfDNA fragmentation for the early detection of response, we retrieved the fragment size profiles. The proportion of short fragments (P20-150 bp), was found to be increased in non-responders compared to responders at T1 (Wilcoxon, p<0.001) and T2 (Wilcoxon, p=0.033), which suggests that the plasma of non-responders contains a higher fraction of tumor-signal (Figure 1A). Previous reports leveraged the size properties of ctDNA in order to increase the sensitivity of SCNA based methods (PMID: 30404863). In order to utilize both epigenomic and genomic properties to increase the detection rate of tumor-signal, we performed in silico size selection to computationally filter out fragments in the 20-150bp size range. Upon repeating the SCNA analysis, we observed that 20/24 (83%) non-responders and 1/15 (19%) responders had detectable ctDNA at T1 (Figure 1B). This yields a NPV and PPV of 80% and 86% respectively for EoI response detection at T1. By leveraging the fragmentomic properties of cfDNA, the sensitivity of SCNA-based methods can be improved, which leads to an increased detection of response at earlier timepoints. Discussion In patients with HGBL-DH/TH, after one cycle of R-CHOP, the presence of SCNAs enhanced by fragment size analysis in plasma, is significantly associated with an unfavourable EoI response, with a NPV and PPV of 80% and 86% respectively. This novel approach can be performed without prior knowledge of genetic alterations, and may have high potential to guide early risk-adapted treatment strategies in HGBL-DH/TH. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Many refractory classical Hodgkin lymphoma (cHL) patients are uniquely susceptible to immune checkpoint PD-1 blockade (anti-PD-1). Because of these encouraging clinical results, anti-PD-1 is rapidly becoming an integral component of cHL treatment regimens. Unclear is how patients that might benefit from anti-PD-1 can be selected and evaluated during response, highlighting a need to evaluate and compare currently available tissue- and blood-based biomarkers. Blood-based biomarkers may provide a minimally invasive, patient-friendly alternative for response assessment and can be easily obtained during treatment. One of the promising blood-based response biomarkers studied in cHL, focuses on the detection of cell free DNA (cfDNA) in the blood of cancer patients. A proportion of the cfDNA derived from tumor cells is known as circulating tumor DNA (ctDNA). Current cfDNA studies of cHL revolve around the detection of minimal residual disease (MRD) on the basis of mutational profiling of ctDNA.1,2 We and others have shown that detection of genome-wide chromosomal copy number alterations (CNAs) by next generation sequencing (NGS) from ctDNA is relatively straightforward and could serve as a cost and labor attractive alternative to mutational profiling for disease monitoring.3,4 Extracellular vesicle associated microRNAs (EV-miRNAs) are described as potential monitoring strategy in cHL and reflect FDG-PET status.5,6 Additional blood-based biomarkers described in cHL include the protein thymus and activation-regulated chemokine (TARC), of which expression correlates with progression free survival7,8 and circulating soluble PD-L1, which has been detected in cHL patients.9,10 In this letter, we address the potential applicability of these biomarkers for response monitoring of anti-PD-1 in cHL. In an observational cohort study (BioLymph-study, NL60245.029.17), we longitudinally collected blood samples during anti-PD-1 in 4 R/R cHL patients. Additionally, matched tissue biopsies were collected at different timepoints and evaluated for 9p24.1/PD-L1/PD-L2 genetic alterations by fluorescence in situ hybridization (FISH)11,12 and expression of PD-L1 and antigen presentation molecules (HLA-I/II) by immunohistochemistry.11,13 Blood samples were assessed for CNAs in ctDNA4 in all patients and MRD-detection by mutational profiling2 in 2 patients. Furthermore, expression of EV-miRNAs: miR-155-5p, miR-127-3p and let-7a-5p by qRT-PCR,6and serum TARC and soluble PD-L1 protein expression levels by ELISA were measured. Detailed protocols are described in the Suppl. Methods. Promising initial responses to anti-PD-1 were observed in all 4 patients, of which 2 patients had a durable response to anti-PD-1 and 2 other patients responded initially but eventually progressed. Clinical and biomarker characteristics and results of biomarker analyses of all 4 patients are shown in Figures 1 and 2,respectively.Figure 1.: Clinical and biomarker characteristics of cHL patients that received anti-PD-1. Treatment timelines of patient 1–4 together with the timepoints of the blood-based monitoring. Imaging response (by FDG-PET/CT) are shown in the timeline. (A) Patient 1 is a chemorefractory cHL patient who, at baseline, showed no response (SD) after BV as third-line treatment. After 4 cycles of the anti-PD-1, the patient had a PR with a SD after 8 cycles on CT. Two years after the start of anti-PD-1, the patient progressed which was confirmed with FDG-PET/CT and tissue biopsy. After a 2-month without any treatment, followed by 2 additional cycles of anti-PD-1, the patient showed progression on FDG-PET/CT. (B) Patient 2 is an advanced chemo- and BV-treatment-refractory cHL patient who received a matched unrelated allogenic stem cell transplantation, complicated by GvHD. After progression under BV, the patient started anti-PD-1. After 2 cycles of anti-PD-1, the GvHD reactivated and the anti-PD-1 was put on hold. Once the GvHD was under control, the cHL had progressed and the patient received radiotherapy on the pulmonal and abdominal lesions, whereafter anti-PD-1 was restarted. The patient showed response to retreatment (PR, after 4 cycles) but the PET/CT scan was showed signs of pulmonary infectious disease. The patient died shortly thereafter of severe infectious complications. (C) Patient 3 is a chemorefractory cHL patient, who relapsed after allogeneic stem cell transplantation. The patient initially started on BV treatment but showed progression after 3 cycles and switched to anti-PD-1. The patient responded very well (VGPR) and at last consultation (follow-up time: 33 months), the patient has shown no clinical signs of cHL progression under maintenance. (D) Patient 4 is an advanced stage cHL patient. After 2 cycles of BEACOPPesc, the diagnosis was revised as AITL with secondary HRS-like large B-cells, and treatment was switched to CHOEP. The patient progressed under treatment and continued with salvage therapy (DHAP). After PR to DHAP, the patient continued with BV treatment, showed progression and received anti-PD-1. After 8 cycles of anti-PD-1, the patient had a MR on FDG-PET/CT and no signs of disease were seen in the tissue biopsy. AITL = angioimmunoblastic T-cell lymphoma; BEACOPPesc = escalated dose of bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, prednisolone; BV = brentuximab vedotin; cHL = classical Hodgkin lymphoma; CHOEP = cyclophosphamide, doxorubicin, etoposide, vincristine, prednisone; DHAP = dexamethasone, high-dose cytarabine, cisplatin; FDG-PET/CT = fluorodeoxyglucose positron emission tomography/computed tomography; GvHD = graft-versus-host disease; HRS = Hodgkin-Reed Sternberg; MR = mixed response; PD = progressive disease; PR= partial response; SD = stable disease; VGPR= very good partial response.Figure 2.: Blood-based and tissue biomarkers in cHL patients that received anti-PD-1. (A) Blood-based biomarkers are shown as positive or negative for disease-detection based on the cutoffs depicted on next to the figure. Response on the second line is the imaging response (by FDG-PET/CT). (B) Overview table with all the different samples added to the analysis, together with PD-L1 H-score and HLA class I and II. (C) Immunohistochemistry staining’s pretreatment and at progression (PD) during treatment. (D) Fish and example of PD-L1 H-score. (E) HLA-DR staining of patients 1, 3, and 4. cHL = classical Hodgkin lymphoma; FDG-PET/CT = fluorodeoxyglucose positron emission tomography/computed tomography; inf. = PET-positive inflammation which is tissue biopsy confirmed; MR= mixed response; n.a.= not applicable; PD = progressive disease; PR= partial response; SD = stable disease; VGPR= very good partial response.Patient 1 is a chemo- and brentuximab vedotin (BV)-treatment-refractory patient. In tissue, copy gain at 9p24.1/PD-L1/PD-L2 was detected by FISH. The PD-L1 H-score decreased during anti-PD-1 at progression, with only very weak PD-L1 expressing Hodgkin-Reed Sternberg (HRS) cells in the biopsy (Figure 2B). HLA-I expression on HRS cells reverted from positive to negative at progression (Figure 2C). The patient showed no HLA-II expression on HRS cells at baseline and progression (Figure 2E, left panel). For blood-based analyses, CNAs in ctDNA were detected at baseline but not at partial response (PR) and stable disease. At timepoint 4 and 5, before progression was observed by fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT), CNAs were detected (Figure 2A; Suppl. Figure S2). All EV-miRNAs were increased at baseline and decreased during treatment. sTARC was increased at baseline and decreased markedly at PR. Notably, sTARC levels gradually increased after every cycle of anti-PD-1 until progression was detected on FDG-PET/CT (n = 31 samples; Suppl. Figure S3). Patient 2 is a chemo- and BV-treatment-refractory, postallogenic stem cell transplantation patient. In the preceding 3 years to starting anti-PD-1, tissue PD-L1 expression was high, along with copy gain of 9p24.1/PD-L1/PD-L2. As for the blood-based biomarkers, CNAs in ctDNA were detected throughout the complete disease period. A clear decrease relative to the baseline sample of ctDNA fraction was seen at PR ( Suppl. Figure S3 and S3). EV-miRNAs decreased steeply after start of anti-PD-1 at PR, increased during time of graft-versus-host disease (GvHD) and progression, and decreased after restart of anti-PD-1. The sTARC levels dropped sharply at PR and steadily increased until progression. Similar to sTARC, sPD-L1 increased throughout treatment until start of the second period of anti-PD-1 whereafter it decreased (Suppl. Figure S1). Patient 3 is a chemorefractory, postallogeneic stem cell transplantation patient, progressive after 3 cycles of BV, switching to anti-PD-1. In tissue, significant fluctuation was observed in PD-L1 positive HRS cells. Largest changes were observed after allogeneic stem cell transplantation, before anti-PD-1: only low PD-L1 and no HLA expression were observed. At start of anti-PD-1, the majority of HRS cells were positive for PD-L1, and showed copy gain of 9p24.1/PD-L1/PD-L2 (Figure 2D). HL-I and -II were expressed, although it was at lower levels than surrounding reactive cells (Figure 2E, middle panel). As for blood-based biomarkers, ctDNA fraction was overall low, but CNAs were seen before start BV and anti-PD-1 (Suppl. Figure S5). This patient was also analyzed for MRD in ctDNA by mutational profiling.2 Compared with timepoint 2, patient 3 had an MRD reduction of only 0.02 log-levels, which means that almost the same amount of ctDNA was detected in both samples. EV-miRNAs initially increased at progression, and thereafter showed a stable decrease. sTARC initially decreased, and was already low before start of BV (Suppl. Figure S1). Patient 4 is an advanced stage patient, progressive under salvage treatment and BV before starting anti-PD-1. In tissue before start of anti-PD-1, PD-L1 was expressed in a few HRS cells. In cells where PD-L1 expression was observed, the intensity of expression was very high (3+), consistent with 9p24.1/PD-L1/PD-L2 amplification observed in a minority of the HRS cells. No HLA-I was observed, but HRS cells were positive for HLA-II (Figure 2E, right panel). As for blood-based biomarkers, CNAs were detected at start of BEACOPPesc and at PR, although a clear decrease in ctDNA fraction was seen (Suppl. Figure S1 and S6). After 8 cycles, the patient had a mixed response on FDG-PET/CT and no signs of disease were seen in the tissue biopsy, still a very low ctDNA fraction was seen, that disappeared at later timepoints (Figure 2A). Compared with the baseline timepoint, patient 4 had no detectable MRD, the best possible response with this assay. EV-miRNAs and sTARC were detectable at start of BEACOPPesc, and then decreased. sPD-L1 was very high in this patient initially, and then also decreased (Suppl. Figure S1). In line with this, 9p24.1/PD-L1/PD-L2 amplification was observed in the tissue and in ctDNA. In summary, we performed longitudinal response evaluation during anti-PD-1 in 4 patients using tissue- and blood-based biomarkers. Here, we show that expression of PD-L1 in tissue, as well as HLA-I and -II may modulate over time and during treatment, in line with previous findings.14 PD-L1 expression is decreased on HRS cells in consecutive biopsies before and during anti-PD-1, suggesting that anti-PD-1 may cause a depletion of PD-L1 positive HRS cells. However, in a previous report of Sasse et al., PD-L1 expression seemed unaffected by anti-PD-1.15 The observed expression of HLA-I and -II was quite heterogeneous. In 1 patient, HLA-I expression changed from positive to negative during anti-PD-1, suggesting that additional immune evasion strategies were obtained. Our results demonstrate that expression of various tissue-related biomarkers is not stable over time prior to anti-PD-1. Therefore, to potentially predict response to anti-PD-1, such biomarkers should be determined shortly before start of anti-PD-1. As shown, blood-based technologies can be valuable for response monitoring, each with their own strengths and limitations. In general, the presence or absence of CNAs correspond with treatment response. In 2 patients, an increase in CNAs was observed before progression was detected by FDG/PET-CT. The main advantage of ctDNA using genome-wide CNA detection by NGS is that it can be easily included in routine high-throughput workflows. Also promising is mutational profiling of ctDNA, as shown for patients 3 and 4. Although sensitivity with this method may be higher than CNA evaluation,1,2 mutation-based analyses (ie, CAPPseq) is more time-consuming and costly. EV-miRNAs have the benefit of being highly abundant in the circulation of cHL patients and for response monitoring of anti-PD-1, there is a good correlation with disease status in all patients. The only potential confounder for detection of EV-miRNAs is the presence of infection and GvHD, as seen here for patient 2, and reported previously.6 We show that sTARC levels correlate to disease status in 3 of the 4 patients. Interestingly, 2 patients already had relatively low sTARC prior to start of anti-PD-1, potentially hampering sTARC as biomarker. In our set of patients, sPD-L1 did not appear to be a suitable biomarker, in contrast to other studies.9,10 One of the potential explanations for this discrepancy is that we used serum to detect sPD-L1 instead of plasma, as done by Veldman et al.9 In conclusion, blood-based biomarkers are very promising for disease detection and monitoring of anti-PD-1 responses in cHL. For the most accurate response monitoring, our results suggest a multianalyte approach, using a combination of ctDNA, EV-miRNA and sTARC detection. ACKNOWLEDGMENTS We are thankful to the cHL MRD Consortium for their fruitful collaboration and support. We are thankful to Mai Tran, Leah Prins, Melissa Fidler and Jennifer Perez Boza for helping with the sample collection and Mandy Kerkhoff for help with scanning the immunohistochemistry slides. We are thankful to Helge Dörr and Elisabeth Kirst for excellent technical assistance. AUTHOR CONTRIBUTIONS EEED and MGMR did conception and design. EEED, JMZ, YWSJ, and NJH did provision of study and patient materials. EEED, EvD, SB, SAWMV, PS, NJG, DRAIB, EM, DH, AK, TJM, DMP, BY, DdJ, JMZ, and MGMR did collection and assembly of data. MGMR, BY, DMP, JMZ, EvD, and EEED did data analysis and interpretation. EEED, BY, DDJ, JMZ, and MGMR did article writing. All authors did final approval of article. DISCLOSURES DMP is cofounder and CSO of Exbiome BV. DMP served as an advisor for Takeda for which he received travel compensation. SB is founder, shareholder and CEO of Liqomics. All the other authors have no conflicts of interest to disclose. SOURCES OF FUNDING The blood-based biomarker work was funded by the Dutch Cancer Society (KWF-5510), Cancer Center Amsterdam Foundation (CCA-2013), the Technology Foundation STW (STW Perspective CANCER-ID) grants awarded to D.M. Pegtel. This publication is part of the Veni project of M.G.M. Roemer with project number 101737 which is (partly) financed by the Dutch Research Council (NWO). STUDY APPROVAL Samples were collected in the BioLymph-study. The study is registered in the Dutch CCMO-register (toetsingonline.nl, NL60245.029.17) and is being conducted in accordance to the Declaration of Helsinki (7th revision, October 2013) and in accordance with the Medical Research Involving Human Subjects Act (WMO).

Cancer patients benefit from early tumor detection since treatment outcomes are more favorable for less advanced cancers. Platelets are involved in cancer progression and are considered a promising biosource for cancer detection, as they alter their RNA content upon local and systemic cues. We show that tumor-educated platelet (TEP) RNA-based blood tests enable the detection of 18 cancer types. With 99% specificity in asymptomatic controls, thromboSeq correctly detected the presence of cancer in two-thirds of 1,096 blood samples from stage I-IV cancer patients and in half of 352 stage I-III tumors. Symptomatic controls, including inflammatory and cardiovascular diseases, and benign tumors had increased false-positive test results with an average specificity of 78%. Moreover, thromboSeq determined the tumor site of origin in five different tumor types correctly in over 80% of the cancer patients. These results highlight the potential properties of TEP-derived RNA panels to supplement current approaches for blood-based cancer screening.

Consensus about a standard segmentation method to derive metabolic tumor volume (MTV) in classical Hodgkin lymphoma (cHL) is lacking, and it is unknown how different segmentation methods influence quantitative PET features. Therefore, we aimed to evaluate the delineation and completeness of lesion selection and the need for manual adaptation with different segmentation methods, and to assess the influence of segmentation methods on the prognostic value of MTV, intensity, and dissemination radiomics features in cHL patients. Methods: We analyzed a total of 105 18F-FDG PET/CT scans from patients with newly diagnosed (n = 35) and relapsed/refractory (n = 70) cHL with 6 segmentation methods: 2 fixed thresholds on SUV4.0 and SUV2.5, 2 relative methods of 41% of SUVmax (41max) and a contrast-corrected 50% of SUVpeak (A50P), and 2 combination majority vote (MV) methods (MV2, MV3). Segmentation quality was assessed by 2 reviewers on the basis of predefined quality criteria: completeness of selection, the need for manual adaptation, and delineation of lesion borders. Correlations and prognostic performance of resulting radiomics features were compared among the methods. Results: SUV4.0 required the least manual adaptation but tended to underestimate MTV and often missed small lesions with low 18F-FDG uptake. SUV2.5 most frequently included all lesions but required minor manual adaptations and generally overestimated MTV. In contrast, few lesions were missed when using 41max, A50P, MV2, and MV3, but these segmentation methods required extensive manual adaptation and overestimated MTV in most cases. MTV and dissemination features significantly differed among the methods. However, correlations among methods were high for MTV and most intensity and dissemination features. There were no significant differences in prognostic performance for all features among the methods. Conclusion: A high correlation existed between MTV, intensity, and most dissemination features derived with the different segmentation methods, and the prognostic performance is similar. Despite frequently missing small lesions with low 18F-FDG avidity, segmentation with a fixed threshold of SUV4.0 required the least manual adaptation, which is critical for future research and implementation in clinical practice. However, the importance of small, low 18F-FDG-avidity lesions should be addressed in a larger cohort of cHL patients.

Background: Early and accurate outcome prediction is essential in the clinical management of high-grade B-cell lymphoma (HGBL). An early switch to salvage treatments for those patients who are likely to develop refractory/relapsed disease may improve overall survival. Unfortunately, the positive predictive value of an interim PET-CT is not high enough to guide treatment decisions. Extracellular vesicle-associated microRNAs (EV-miRNAs) are considered promising liquid biopsy-based biomarkers for lymphomas. We performed small RNA sequencing of plasma samples collected during treatment and applied machine learning to build EV-miRNA signatures for early response prediction in patients with HGBL with MYC and BCL2 and/or BCL6 rearrangements (HGBL-DH/TH). Methods: We analyzed PAXgene ccfDNA plasma samples, from 38 of the 97 patients included in the HOVON-152 trial (NCT03620578), a prospective, multicenter, non-randomized phase II trial. In this trial, patients with HGBL-DH/TH receive one cycle of rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) followed by five cycles of dose adjusted etoposide, prednisone, vincristine, cyclophosphamide, doxorubicin, and rituximab (DA-EPOCH-R). Patients who achieve complete metabolic response (CMR) at the end-of-induction (EOI) receive one year of nivolumab consolidation. Response was assessed by an EOI PET-CT and classified as CMR (Deauville score 1-3) (responders) or no-CMR (non-responders). 20 responders and 18 non-responders (enrichment for non-responders), were selected for this analysis. We isolated plasma EVs with size exclusion chromatography as confirmed with transmission electron microscopy (TEM), tunable resistive pulse sensing (TRPS), and western blot (WB). Library preparation was done according to an unbiased, unique molecular identifier (UMI)-enhanced small RNA sequencing protocol (IsoSeek) (van Eijndhoven et al., 2021. bioRxiv) and sequenced on the NovaSeq 6000 (Illumina). We applied machine learning including the least absolute shrinkage and selection operator (LASSO), Elastic Net, and Ridge Regression to build models with EV-miRNAs for early EOI response prediction. We selected the most optimal model based on the lowest misclassification error. Then the model was internally validated and tested with bootstrapping (1000x) and over optimism estimate as well as the adjusted AUC was calculated. Results: TEM after one cycle of R-CHOP revealed abundant particles < 200 nm and TRPS measured significantly higher particle concentration in EV-enriched fractions. Plasma EVs were positive for CD63, CD81, flotillin-1, syntenin, HSP70, and negative for calnexin as determined by WB in accordance with the Minimal Information for Studies of EVs (MISEV) criteria 2018 for EV characterization. The most optimal model was an Elastic Net regression (a = 0.4) model consisting of 199 miRNAs with an area under the curve (AUC) of 0.95 (Confidence Interval (CI): 0.90 - 0.99) (Figure 1) [Sensitivity: 88%, Specificity: 90%; Positive Predictive Value (PPV): 90%, Negative Predictive Value (NPV): 87%]. We tested our model with bootstrapping (1,000x). After taking into account of over optimism estimate of 0.14, the adjusted AUC was 0.81 (CI: 0.64-0.96), which is higher than the performance of interim PET/CT [Sensitivity: 33-87%, Specificity: 49-94%; PPV: 20-74%, NPV: 64-95%] (Burggraaff 2019, PMID: 30141066). Conclusion: Machine learning models using plasma EV-miRNAs prepared with the IsoSeek small RNA sequencing protocol yielded a robust signature that can predict EOI response already after one cycle of R-CHOP with a NPV of 87% and a PPV of 90%. The next step is to validate this model in a large cohort of HGBL-DH/TH cases and explore its potential in all subtypes of diffuse large B-cell lymphoma. If validated in independent cohorts, this novel approach could potentially, in combination with other modalities such as cell-free DNA and interim PET-CT, guide early risk-adapted treatment strategies in aggressive high-grade B-cell lymphomas. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Somatic copy number alterations can be detected in cell-free DNA (cfDNA) by shallow whole genome sequencing (sWGS). PCR is typically included in library preparations, but a PCR-free method could serve as a high-throughput alternative. To evaluate a PCR-free method for research and diagnostics, archival peripheral blood or bone marrow plasma samples, collected in EDTA- or lithium-heparin-containing tubes, were collected from patients with non-small-cell lung cancer (n = 10 longitudinal samples; 4 patients), B-cell lymphoma (n = 31), and acute myeloid leukemia (n = 15), or from healthy donors (n = 14). sWGS was performed on PCR-free and PCR library preparations, and the mapping quality, percentage of unique reads, genome coverage, fragment lengths, and copy number profiles were compared. The percentage of unique reads was significantly higher for PCR-free method compared with PCR method, independent of the type of collection tube: EDTA PCR-free method, 96.4% (n = 35); EDTA PCR method, 85.1% (n = 32); heparin PCR-free method, 94.5% (n = 25); and heparin PCR method, 89.4% (n = 10). All other evaluated metrics were highly comparable for PCR-free and PCR library preparations. These results demonstrate the feasibility of somatic copy number alteration detection by PCR-free sWGS using cfDNA from plasma collected in EDTA- or lithium-heparin-containing tubes and pave the way for an automated cfDNA analysis workflow for samples from cancer patients. (J Mol Diagn 2021, 23: 1553-1563; https://doi.org/10.1016/j.jmoldx.2021.08.008)

Abstract Minimally‐invasive tools to assess tumour presence and burden may improve clinical management. FDG‐PET (metabolic) imaging is the current gold standard for interim response assessment in patients with classical Hodgkin Lymphoma (cHL), but this technique cannot be repeated frequently. Here we show that microRNAs (miRNA) associated with tumour‐secreted extracellular vesicles (EVs) in the circulation of cHL patients may improve response assessment. Small RNA sequencing and qRT‐PCR reveal that the relative abundance of cHL‐expressed miRNAs, miR‐127‐3p, miR‐155‐5p, miR‐21‐5p, miR‐24‐3p and let‐7a‐5p is up to hundred‐fold increased in plasma EVs of cHL patients pre‐treatment when compared to complete metabolic responders (CMR). Notably, in partial responders (PR) or treatment‐refractory cases (n = 10) the EV‐miRNA levels remain elevated. In comparison, tumour specific copy number variations (CNV) were detected in cell‐free DNA of 8 out of 10 newly diagnosed cHL patients but not in patients with PR. Combining EV‐miR‐127‐3p and/or EV‐let‐7a‐5p levels, with serum TARC (a validated protein cHL biomarker), increases the accuracy for predicting PET‐status (n = 129) to an area under the curve of 0.93 (CI: 0.87‐0.99), 93.5% sensitivity, 83.8/85.0% specificity and a negative predictive value of 96%. Thus the level of tumour‐associated miRNAs in plasma EVs is predictive of metabolic tumour activity in cHL patients. Our findings suggest that plasma EV‐miRNA are useful for detection of small residual lesions and may be applied as serial response prediction tool.

Terminal nucleotidyl transferases are enzymes that add non-templated nucleotides to RNA molecules. In the case of microRNAs, this process was shown to be functionally relevant for their maturation process and generation of isomiRs with non-canonical mRNA targets. Deconvolution of these posttranscriptional modifications is challenging in particular for extracellular miRNAs that are considered as a target for minimally-invasive diagnostics. Massively parallel RNA sequencing is the only method that can truthfully reveal isomiR diversity in biological samples and determine relative quantities. Improvements aside, current small RNA sequencing strategies remain imprecise. We developed IsoSeek that diverges from these methods by making use of randomized 5’- and 3’-adapters combined with a 10N unique molecular identifier (UMI). Using synthetic miRNA and isomiR spike-in sets and testing depletion and RNA competition strategies in 7 sequencing rounds of >100 samples, we rigorously optimized and validated the technical accuracy of the IsoSeek method. In genetically-altered HEK293, we characterized the terminal uridylase (TUT4/TUT7) dependent miRNA uridylome and discovered extensive uridylation of disease-associated miRNAs. Notably, 3’-uridylated isomiR profiles of plasma extracellular vesicles (EVs) rely on UMI-correction. Thus, IsoSeek advances our knowledge of cell-free miRNAs and supports development into non-invasive biomarkers.

Individualizing treatment is key to improve outcome and reduce long-term side-effects in any cancer. In Hodgkin lymphoma (HL), individualization of treatment is hindered by a lack of genomic characterization and technology for sensitive, molecular response assessment. Sequencing of cell-free (cf)DNA is a powerful strategy to understand an individual cancer genome and can be used to develop assays for extremely sensitive disease monitoring. In HL, a high proportion of cfDNA is tumor-derived making it a highly relevant disease model to study the role of cfDNA sequencing in cancer. Here, we introduce our targeted cfDNA sequencing platform and present the largest genomic landscape of HL to date, which was entirely derived by cfDNA sequencing. We comprehensively genotype and assess minimal residual disease in 324 samples from 121 patients, presenting an integrated landscape of mutations and copy number variations in HL. In addition, we perform a deep analysis of mutational processes driving HL, investigate the clonal structure of HL and link several genotypes to HL phenotypes and outcome. Finally, we show that minimal residual disease assessment by repeat cfDNA sequencing as early as a week after treatment initiation is feasible and predicts overall treatment response allowing highly improved treatment guidance and relapse prediction. Our study also serves as a blueprint showcasing the utility of our platform for other cancers with similar therapeutic challenges.

B cell lymphomas are heterogeneous malignancies of hematological origin with vastly different biology and clinical outcomes. Histopathology of tissue biopsies and image-based assessment guide clinical decisions. Given that tissue biopsies cannot be frequently repeated and will not inform on systemic responses to the treatment, more accessible biomarkers, such as circulating miRNAs, are considered. Aberrant miRNA expression in lymphoma tissues and ongoing immune reactions may lead to miRNA alterations in circulation. miRNAs bound to extracellular vesicles (EVs) are of interest because of their role in intercellular communication and organ crosstalk. Herein, we highlight the role of miRNAs and EVs in B cell lymphomagenesis and explain how circulating miRNAs may be turned into robust liquid biopsy tests for aggressive B cell lymphoma.

Owing to the relationship between extracellular vesicles (EVs) and physiological and pathological conditions, the interest in EVs is exponentially growing. EVs hold high hopes for novel diagnostic and translational discoveries. This review provides an expert-based update of recent advances in the methods to study EVs and summarizes currently accepted considerations and recommendations from sample collection to isolation, detection, and characterization of EVs. Common misconceptions and methodological pitfalls are highlighted. Although EVs are found in all body fluids, in this review, we will focus on EVs from human blood, not only our most complex but also the most interesting body fluid for cardiovascular research.

BACKGROUND. Cell-free circulating nucleic acids, including 22-nt microRNAs (miRNAs), represent noninvasive biomarkers for treatment response monitoring of cancer patients. While the majority of plasma miRNA is bound to proteins, a smaller, less well-characterized pool is associated with extracellular vesicles (EVs). Here, we addressed whether EV-associated miRNAs reflect metabolic disease in classical Hodgkin lymphoma (cHL) patients. METHODS. With standardized size-exclusion chromatography (SEC), we isolated EV-associated extracellular RNA (exRNA) fractions and protein-bound miRNA from plasma of cHL patients and healthy subjects. We performed a comprehensive small RNA sequencing analysis and validation by TaqMan qRT-PCR for candidate discovery. Fluorodeoxyglucose-PET (FDG-PET) status before treatment, directly after treatment, and during long-term follow-up was compared directly with EV miRNA levels. RESULTS. The plasma EV miRNA repertoire was more extensive compared with protein-bound miRNA that was heavily dominated by a few abundant miRNA species and was less informative of disease status. Purified EV fractions of untreated cHL patients and tumor EVs had enriched levels of miR24-3p, miR127-3p, miR21-5p, miR155-5p, and let7a-5p compared with EV fractions from healthy subjects and disease controls. Serial monitoring of EV miRNA levels in patients before treatment, directly after treatment, and during long-term follow-up revealed robust, stable decreases in miRNA levels matching a complete metabolic response, as observed with FDG-PET. Importantly, EV miRNA levels rose again in relapse patients. CONCLUSION. We conclude that cHL-related miRNA levels in circulating EVs reflect the presence of vital tumor tissue and are suitable for therapy response and relapse monitoring in individual cHL patients. FUNDING. Cancer Center Amsterdam Foundation (CCA-2013), Dutch Cancer Society (KWF-5510), Technology Foundation STW (STW Perspectief CANCER-ID).

PURPOSE:Non-small-cell lung cancers harboring EML4-ALK rearrangements are sensitive to crizotinib. However, despite initial response, most patients will eventually relapse, and monitoring EML4-ALK rearrangements over the course of treatment may help identify these patients. However, challenges associated with serial tumor biopsies have highlighted the need for blood-based assays for the monitoring of biomarkers. Platelets can sequester RNA released by tumor cells and are thus an attractive source for the non-invasive assessment of biomarkers.METHODS:EML4-ALK rearrangements were analyzed by RT-PCR in platelets and plasma isolated from blood obtained from 77 patients with non-small-cell lung cancer, 38 of whom had EML4-ALK-rearranged tumors. In a subset of 29 patients with EML4-ALK-rearranged tumors who were treated with crizotinib, EML4-ALK rearrangements in platelets were correlated with progression-free and overall survival.RESULTS:RT-PCR demonstrated 65% sensitivity and 100% specificity for the detection of EML4-ALK rearrangements in platelets. In the subset of 29 patients treated with crizotinib, progression-free survival was 3.7 months for patients with EML4-ALK+ platelets and 16 months for those with EML4-ALK- platelets (hazard ratio, 3.5; P = 0.02). Monitoring of EML4-ALK rearrangements in the platelets of one patient over a period of 30 months revealed crizotinib resistance two months prior to radiographic disease progression.CONCLUSIONS:Platelets are a valuable source for the non-invasive detection of EML4-ALK rearrangements and may prove useful for predicting and monitoring outcome to crizotinib, thereby improving clinical decisions based on radiographic imaging alone.

8082 Background: Non-small-cell lung cancer (NSCLC) with EML4-ALK rearrangements is sensitive to crizotinib. However, despite initial response most patients (p) will eventually relapse and monitoring EML4-ALK rearrangements over the course of treatment may help identify them. Challenges associated with serial tumor biopsies have highlighted the need for blood-based assays for monitoring biomarkers. Platelets can sequester RNA released by tumor cells and are an attractive source for non-invasive biomarker assessment. Methods: EML4-ALK rearrangements were analyzed by reverse transcription-polymerase chain reaction (RT-PCR) in platelets and plasma isolated from blood obtained from 77 NSCLC p, 38 of whom had EML4-ALK-rearranged tumors. In a subset of 29 p with EML4-ALK-rearranged tumors treated with crizotinib, EML4-ALK rearrangements in platelets were correlated with progression-free survival (PFS) and overall survival (OS). Results: The study was designed with three parallel objectives: firstly to determine the sensitivity and specificity of detecting EML4-ALK rearrangements in platelets with plasma serving as a control biosource; secondly, to examine the potential impact of EML4-ALK rearrangement in platelets on outcome to crizotinib; thirdly, to test the feasibility of monitoring a p throughout treatment with EML4-ALK rearrangement assessment in platelets. RT-PCR demonstrated 65% sensitivity and 100% specificity for detection of EML4-ALK rearrangements in platelets. In the subset of 29 p treated with crizotinib, PFS was 3.7 months for p with EML4-ALK+ platelets and 16 months for those with EML4-ALK− platelets (hazard ratio, 3.5; P = 0.02). Monitoring EML4-ALK rearrangements in platelets of one index p over a period of 30 months revealed crizotinib resistance two months prior to radiographic disease progression. Conclusions: Platelets may provide a useful source for non-invasive assessment of EML4-ALK rearrangements and may prove useful for predicting outcome to crizotinib. Serial analyses of EML4-ALK rearrangements in platelets may help improve clinical decisions based on radiographic imaging alone by detecting resistance to therapy sooner.

Abstract Background: Novel targeted therapies have been successfully used against subgroups of non-small-cell lung cancer (NSCLC) patients, however, despite initial good response the cancer will eventually relapse. One of those subgroups harbors a rearranged EML4-ALK fusion gene that makes them responsive to crizotinib treatment, but therapy resistance often soon occurs. Real-time monitoring of rearrangement status over the course of treatment will help identify patients showing therapy resistance, but monitoring through serial tumor biopsies has been an obstacle. Therefore, new blood-based ´liquid biopsy´ platforms need to be developed to monitoring biomarkers in the circulation. Here we present one platform using the ability of platelets to sequester RNA released by tumor cells and represent an attractive source for non-invasive biomarker assessment. Methods: EML4-ALK rearrangements were analyzed by reverse transcription-polymerase chain reaction (RT-PCR) in platelets and plasma isolated from blood obtained from 77 NSCLC patients, 38 of whom had EML4-ALK-rearranged tumors. In a subset patients (n = 29) that were treated with crizotinib, progression-free survival (PFS) and overall survival (OS) were correlated with presence of EML4-ALK rearrangements in platelets. Results: The study was designed with three parallel objectives: firstly to determine the sensitivity and specificity of detecting EML4-ALK rearrangements in platelets; secondly, to examine the potential impact of EML4-ALK rearrangement in platelets on outcome to crizotinib; thirdly, to test the feasibility of monitoring patients throughout treatment with EML4-ALK rearrangement assessment in platelets. Detection of EML4-ALK rearrangements in platelets demonstrated 65% sensitivity and 100% specificity. The PFS in patients treated with crizotinib was 3.7 months in patients with a positive EML4-ALK platelet status compared to 16 months for a negative EML4-ALK status (hazard ratio, 3.5; P = 0.02). Furthermore, longitudinal monitoring of EML4-ALK rearrangements in platelets was feasible, as demonstrated in an index patient where crizotinib resistance was observed two months prior to radiographic disease progression. Conclusions: Platelets may provide a useful source for non-invasive assessment of EML4-ALK rearrangements and may prove useful for predicting outcome to crizotinib. Serial analyses of EML4-ALK rearrangements in platelets may help improve clinical decisions based on radiographic imaging alone by detecting resistance to therapy sooner. Citation Format: Jonas A. Nilsson, Niki Karachaliou, Pepijn Schellen, Ana Gimenez-Capitan, Jordi Berenguer, Cristina Teixido, Justine L. Kuiper, Esther Drees, Magda Grabowska, Marte van Keulen, Jihane M. Tannous, Danielle A.M. Heideman, Erik Thunnissen, Anne-Marie C. Dingemans, Santiago Viteri, Bakhos A. Tannous, Ana Drozdowskyj, Rafael Rosell, Egbert F. Smit, Thomas Wurdinger. Monitoring rearrangement of EML4-ALK in blood platelets predicts outcome to crizotinib treatment in non-small-cell lung cancer patients. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr LB-053. doi:10.1158/1538-7445.AM2015-LB-053

We isolated, by the subtraction cloning method, a pepsinogen C (PGC) gene fragment (the sequence between the 968th and 1179th base pairs) from a rat gastric mucosal cDNA library as a cDNA clone encoding a substance that promotes growth of the normal rat gastric mucosal cell line RGM1. Northern blot analysis revealed that PGC gene expression was enhanced not only in acetic acid-induced chronic gastric ulcers but also in indomethacin-induced gastric mucosal lesions. PGC gene expression was also increased in the Helicobacter felis-infected stomachs. Thus, the PGC gene may play a role in gastric epithelial cell growth during gastric mucosal healing.