Noninvasive Early Identification of Therapeutic Benefit from Immune Checkpoint Inhibition.

Although treatment of non-small cell lung cancer (NSCLC) with immune checkpoint inhibitors (ICIs) can produce remarkably durable responses, most patients develop early disease progression. Furthermore, initial response assessment by conventional imaging is often unable to identify which patients will achieve durable clinical benefit (DCB). Here, we demonstrate that pre-treatment circulating tumor DNA (ctDNA) and peripheral CD8 T cell levels are independently associated with DCB. We further show that ctDNA dynamics after a single infusion can aid in identification of patients who will achieve DCB. Integrating these determinants, we developed and validated an entirely noninvasive multiparameter assay (DIREct-On, Durable Immunotherapy Response Estimation by immune profiling and ctDNA-On-treatment) that robustly predicts which patients will achieve DCB with higher accuracy than any individual feature. Taken together, these results demonstrate that integrated ctDNA and circulating immune cell profiling can provide accurate, noninvasive, and early forecasting of ultimate outcomes for NSCLC patients receiving ICIs.

Dynamic Risk Profiling Using Serial Tumor Biomarkers for Personalized Outcome Prediction.

Accurate prediction of long-term outcomes remains a challenge in the care of cancer patients. Due to the difficulty of serial tumor sampling, previous prediction tools have focused on pretreatment factors. However, emerging non-invasive diagnostics have increased opportunities for serial tumor assessments. We describe the Continuous Individualized Risk Index (CIRI), a method to dynamically determine outcome probabilities for individual patients utilizing risk predictors acquired over time. Similar to "win probability" models in other fields, CIRI provides a real-time probability by integrating risk assessments throughout a patient's course. Applying CIRI to patients with diffuse large B cell lymphoma, we demonstrate improved outcome prediction compared to conventional risk models. We demonstrate CIRI's broader utility in analogous models of chronic lymphocytic leukemia and breast adenocarcinoma and perform a proof-of-concept analysis demonstrating how CIRI could be used to develop predictive biomarkers for therapy selection. We envision that dynamic risk assessment will facilitate personalized medicine and enable innovative therapeutic paradigms.

Distinct Hodgkin lymphoma subtypes defined by noninvasive genomic profiling.

The scarcity of malignant Hodgkin and Reed-Sternberg cells hampers tissue-based comprehensive genomic profiling of classic Hodgkin lymphoma (cHL). By contrast, liquid biopsies show promise for molecular profiling of cHL due to relatively high circulating tumour DNA (ctDNA) levels1-4. Here we show that the plasma representation of mutations exceeds the bulk tumour representation in most cases, making cHL particularly amenable to noninvasive profiling. Leveraging single-cell transcriptional profiles of cHL tumours, we demonstrate Hodgkin and Reed-Sternberg ctDNA shedding to be shaped by DNASE1L3, whose increased tumour microenvironment-derived expression drives high ctDNA concentrations. Using this insight, we comprehensively profile 366 patients, revealing two distinct cHL genomic subtypes with characteristic clinical and prognostic correlates, as well as distinct transcriptional and immunological profiles. Furthermore, we identify a novel class of truncating IL4R mutations that are dependent on IL-13 signalling and therapeutically targetable with IL-4Rα-blocking antibodies. Finally, using PhasED-seq5, we demonstrate the clinical value of pretreatment and on-treatment ctDNA levels for longitudinally refining cHL risk prediction and for detection of radiographically occult minimal residual disease. Collectively, these results support the utility of noninvasive strategies for genotyping and dynamic monitoring of cHL, as well as capturing molecularly distinct subtypes with diagnostic, prognostic and therapeutic potential.

Practical recommendations for using ctDNA in clinical decision making.

The continuous improvement in cancer care over the past decade has led to a gradual decrease in cancer-related deaths. This is largely attributed to improved treatment and disease management strategies. Early detection of recurrence using blood-based biomarkers such as circulating tumour DNA (ctDNA) is being increasingly used in clinical practice. Emerging real-world data shows the utility of ctDNA in detecting molecular residual disease and in treatment-response monitoring, helping clinicians to optimize treatment and surveillance strategies. Many studies have indicated ctDNA to be a sensitive and specific biomarker for recurrence. However, most of these studies are largely observational or anecdotal in nature, and peer-reviewed data regarding the use of ctDNA are mainly indication-specific. Here we provide general recommendations on the clinical utility of ctDNA and how to interpret ctDNA analysis in different treatment settings, especially in patients with solid tumours. Specifically, we provide an understanding around the implications, strengths and limitations of this novel biomarker and how to best apply the results in clinical practice.

Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA.

Circulating tumour DNA (ctDNA) can be used to detect and profile residual tumour cells persisting after curative intent therapy1. The study of large patient cohorts incorporating longitudinal plasma sampling and extended follow-up is required to determine the role of ctDNA as a phylogenetic biomarker of relapse in early-stage non-small-cell lung cancer (NSCLC). Here we developed ctDNA methods tracking a median of 200 mutations identified in resected NSCLC tissue across 1,069 plasma samples collected from 197 patients enrolled in the TRACERx study2. A lack of preoperative ctDNA detection distinguished biologically indolent lung adenocarcinoma with good clinical outcome. Postoperative plasma analyses were interpreted within the context of standard-of-care radiological surveillance and administration of cytotoxic adjuvant therapy. Landmark analyses of plasma samples collected within 120 days after surgery revealed ctDNA detection in 25% of patients, including 49% of all patients who experienced clinical relapse; 3 to 6 monthly ctDNA surveillance identified impending disease relapse in an additional 20% of landmark-negative patients. We developed a bioinformatic tool (ECLIPSE) for non-invasive tracking of subclonal architecture at low ctDNA levels. ECLIPSE identified patients with polyclonal metastatic dissemination, which was associated with a poor clinical outcome. By measuring subclone cancer cell fractions in preoperative plasma, we found that subclones seeding future metastases were significantly more expanded compared with non-metastatic subclones. Our findings will support (neo)adjuvant trial advances and provide insights into the process of metastatic dissemination using low-ctDNA-level liquid biopsy.

Circulating tumor DNA in advanced solid tumors: Clinical relevance and future directions.

The application of genomic profiling assays using plasma circulating tumor DNA (ctDNA) is rapidly evolving in the management of patients with advanced solid tumors. Diverse plasma ctDNA technologies in both commercial and academic laboratories are in routine or emerging use. The increasing integration of such testing to inform treatment decision making by oncology clinicians has complexities and challenges but holds significant potential to substantially improve patient outcomes. In this review, the authors discuss the current role of plasma ctDNA assays in oncology care and provide an overview of ongoing research that may inform real-world clinical applications in the near future.

Deep whole-genome ctDNA chronology of treatment-resistant prostate cancer.

Circulating tumour DNA (ctDNA) in blood plasma is an emerging tool for clinical cancer genotyping and longitudinal disease monitoring1. However, owing to past emphasis on targeted and low-resolution profiling approaches, our understanding of the distinct populations that comprise bulk ctDNA is incomplete2-12. Here we perform deep whole-genome sequencing of serial plasma and synchronous metastases in patients with aggressive prostate cancer. We comprehensively assess all classes of genomic alterations and show that ctDNA contains multiple dominant populations, the evolutionary histories of which frequently indicate whole-genome doubling and shifts in mutational processes. Although tissue and ctDNA showed concordant clonally expanded cancer driver alterations, most individual metastases contributed only a minor share of total ctDNA. By comparing serial ctDNA before and after clinical progression on potent inhibitors of the androgen receptor (AR) pathway, we reveal population restructuring converging solely on AR augmentation as the dominant genomic driver of acquired treatment resistance. Finally, we leverage nucleosome footprints in ctDNA to infer mRNA expression in synchronously biopsied metastases, including treatment-induced changes in AR transcription factor signalling activity. Our results provide insights into cancer biology and show that liquid biopsy can be used as a tool for comprehensive multi-omic discovery.

ctDNA guiding adjuvant immunotherapy in urothelial carcinoma.

Minimally invasive approaches to detect residual disease after surgery are needed to identify patients with cancer who are at risk for metastatic relapse. Circulating tumour DNA (ctDNA) holds promise as a biomarker for molecular residual disease and relapse1. We evaluated outcomes in 581 patients who had undergone surgery and were evaluable for ctDNA from a randomized phase III trial of adjuvant atezolizumab versus observation in operable urothelial cancer. This trial did not reach its efficacy end point in the intention-to-treat population. Here we show that ctDNA testing at the start of therapy (cycle 1 day 1) identified 214 (37%) patients who were positive for ctDNA and who had poor prognosis (observation arm hazard ratio = 6.3 (95% confidence interval: 4.45-8.92); P < 0.0001). Notably, patients who were positive for ctDNA had improved disease-free survival and overall survival in the atezolizumab arm versus the observation arm (disease-free survival hazard ratio = 0.58 (95% confidence interval: 0.43-0.79); P = 0.0024, overall survival hazard ratio = 0.59 (95% confidence interval: 0.41-0.86)). No difference in disease-free survival or overall survival between treatment arms was noted for patients who were negative for ctDNA. The rate of ctDNA clearance at week 6 was higher in the atezolizumab arm (18%) than in the observation arm (4%) (P = 0.0204). Transcriptomic analysis of tumours from patients who were positive for ctDNA revealed higher expression levels of cell-cycle and keratin genes. For patients who were positive for ctDNA and who were treated with atezolizumab, non-relapse was associated with immune response signatures and basal-squamous gene features, whereas relapse was associated with angiogenesis and fibroblast TGFß signatures. These data suggest that adjuvant atezolizumab may be associated with improved outcomes compared with observation in patients who are positive for ctDNA and who are at a high risk of relapse. These findings, if validated in other settings, would shift approaches to postoperative cancer care.

Bridging biological cfDNA features and machine learning approaches.

Liquid biopsies (LBs), particularly using circulating tumor DNA (ctDNA), are expected to revolutionize precision oncology and blood-based cancer screening. Recent technological improvements, in combination with the ever-growing understanding of cell-free DNA (cfDNA) biology, are enabling the detection of tumor-specific changes with extremely high resolution and new analysis concepts beyond genetic alterations, including methylomics, fragmentomics, and nucleosomics. The interrogation of a large number of markers and the high complexity of data render traditional correlation methods insufficient. In this regard, machine learning (ML) algorithms are increasingly being used to decipher disease- and tissue-specific signals from cfDNA. Here, we review recent insights into biological ctDNA features and how these are incorporated into sophisticated ML applications.

Entirely noninvasive outcome prediction in central nervous system lymphomas using circulating tumor DNA.

ABSTRACT: State-of-the-art response assessment of central nervous system lymphoma (CNSL) by magnetic resonance imaging is challenging and an insufficient predictor of treatment outcomes. Accordingly, the development of novel risk stratification strategies in CNSL is a high unmet medical need. We applied ultrasensitive circulating tumor DNA (ctDNA) sequencing to 146 plasma and cerebrospinal fluid (CSF) samples from 67 patients, aiming to develop an entirely noninvasive dynamic risk model considering clinical and molecular features of CNSL. Our ultrasensitive method allowed for the detection of CNSL-derived mutations in plasma ctDNA with high concordance to CSF and tumor tissue. Undetectable plasma ctDNA at baseline was associated with favorable outcomes. We tracked tumor-specific mutations in plasma-derived ctDNA over time and developed a novel CNSL biomarker based on this information: peripheral residual disease (PRD). Persistence of PRD after treatment was highly predictive of relapse. Integrating established baseline clinical risk factors with assessment of radiographic response and PRD during treatment resulted in the development and independent validation of a novel tool for risk stratification: molecular prognostic index for CNSL (MOP-C). MOP-C proved to be highly predictive of outcomes in patients with CNSL (failure-free survival hazard ratio per risk group of 6.60; 95% confidence interval, 3.12-13.97; P < .0001) and is publicly available at www.mop-c.com. Our results highlight the role of ctDNA sequencing in CNSL. MOP-C has the potential to improve the current standard of clinical risk stratification and radiographic response assessment in patients with CNSL, ultimately paving the way toward individualized treatment.

Acalabrutinib, venetoclax, and obinutuzumab in relapsed/refractory CLL: final efficacy and ctDNA analysis of the CLL2-BAAG trial.

ABSTRACT: The phase 2 CLL2-BAAG trial tested the measurable residual disease (MRD)-guided triple combination of acalabrutinib, venetoclax, and obinutuzumab after optional bendamustine debulking in 45 patients with relapsed/refractory chronic lymphocytic leukemia (CLL). MRD was measured by flow cytometry (FCM; undetectable MRD <10-4) in peripheral blood (PB) and circulating tumor DNA (ctDNA) using digital droplet polymerase chain reaction of variable-diversity-joining (VDJ) rearrangements and CLL-related mutations in plasma. The median number of previous treatments was 1 (range, 1-4); 18 patients (40%) had received a Bruton tyrosine kinase inhibitor (BTKi) and/or venetoclax before inclusion, 14 of 44 (31.8%) had TP53 aberrations, and 34 (75.6%) had unmutated immunoglobulin heavy-chain variable region genes. With a median observation time of 36.3 months and all patients off-treatment for a median of 21.9 months, uMRD <10-4 in PB was achieved in 42 of the 45 patients (93.3%) at any time point, including 17 of 18 (94.4%) previously exposed to venetoclax/BTKi and 13 of 14 (92.9%) with TP53 aberrations. The estimated 3-year progression-free and overall survival rates were 85.0% and 93.8%, respectively. Overall, 585 paired FCM/ctDNA samples were analyzed and 18 MRD recurrences (5 with and 13 without clinical progression) occurred after the end of treatment. Twelve samples were first detected by ctDNA, 3 by FCM, and 3 synchronously. In conclusion, time-limited MRD-guided acalabrutinib, venetoclax, and obinutuzumab achieved deep remissions in almost all patients with relapsed/refractory CLL. The addition of ctDNA-based analyses to FCM MRD assessment seems to improve early detection of relapses. This trial was registered at www.clinicaltrials.gov as #NCT03787264.

ctDNA improves prognostic prediction for patients with relapsed/refractory MM receiving ixazomib, lenalidomide, and dexamethasone.

ABSTRACT: It remains elusive how driver mutations, including those detected in circulating tumor DNA (ctDNA), affect prognosis in relapsed/refractory multiple myeloma (RRMM). Here, we performed targeted-capture sequencing using bone marrow plasma cells (BMPCs) and ctDNA of 261 RRMM cases uniformly treated with ixazomib, lenalidomide, and dexamethasone in a multicenter, prospective, observational study. We detected 24 and 47 recurrently mutated genes in BMPC and ctDNA, respectively. In addition to clonal hematopoiesis-associated mutations, varying proportion of driver mutations, particularly TP53 mutations (59.2% of mutated cases), were present in only ctDNA, suggesting their subclonal origin. In univariable analyses, ctDNA mutations of KRAS, TP53, DIS3, BRAF, NRAS, and ATM were associated with worse progression-free survival (PFS). BMPC mutations of TP53 and KRAS were associated with inferior PFS, whereas KRAS mutations were prognostically relevant only when detected in both BMPC and ctDNA. A total number of ctDNA mutations in the 6 relevant genes was a strong prognostic predictor (2-year PFS rates: 57.3%, 22.7%, and 0% for 0, 1, and ≥2 mutations, respectively) and independent of clinical factors and plasma DNA concentration. Using the number of ctDNA mutations, plasma DNA concentration, and clinical factors, we developed a prognostic index, classifying patients into 3 categories with 2-year PFS rates of 57.9%, 28.6%, and 0%. Serial analysis of ctDNA mutations in 94 cases revealed that TP53 and KRAS mutations frequently emerge after therapy. Thus, we clarify the genetic characteristics and clonal architecture of ctDNA mutations and demonstrate their superiority over BMPC mutations for prognostic prediction in RRMM. This study is a part of the C16042 study, which is registered at www.clinicaltrials.gov as #NCT03433001.

Integrating genomic features for non-invasive early lung cancer detection.

Radiologic screening of high-risk adults reduces lung-cancer-related mortality1,2; however, a small minority of eligible individuals undergo such screening in the United States3,4. The availability of blood-based tests could increase screening uptake. Here we introduce improvements to cancer personalized profiling by deep sequencing (CAPP-Seq)5, a method for the analysis of circulating tumour DNA (ctDNA), to better facilitate screening applications. We show that, although levels are very low in early-stage lung cancers, ctDNA is present prior to treatment in most patients and its presence is strongly prognostic. We also find that the majority of somatic mutations in the cell-free DNA (cfDNA) of patients with lung cancer and of risk-matched controls reflect clonal haematopoiesis and are non-recurrent. Compared with tumour-derived mutations, clonal haematopoiesis mutations occur on longer cfDNA fragments and lack mutational signatures that are associated with tobacco smoking. Integrating these findings with other molecular features, we develop and prospectively validate a machine-learning method termed 'lung cancer likelihood in plasma' (Lung-CLiP), which can robustly discriminate early-stage lung cancer patients from risk-matched controls. This approach achieves performance similar to that of tumour-informed ctDNA detection and enables tuning of assay specificity in order to facilitate distinct clinical applications. Our findings establish the potential of cfDNA for lung cancer screening and highlight the importance of risk-matching cases and controls in cfDNA-based screening studies.

Transposon DNA sequences facilitate the tissue-specific gene transfer of circulating tumor DNA between human cells.

The exchange of genes between cells is known to play an important physiological and pathological role in many organisms. We show that circulating tumor DNA (ctDNA) facilitates cell-specific gene transfer between human cancer cells and explain part of the mechanisms behind this phenomenon. As ctDNA migrates into the nucleus, genetic information is transferred. Cell targeting and ctDNA integration require ERVL, SINE or LINE DNA sequences. Chemically manufactured AluSp and MER11C sequences replicated multiple myeloma (MM) ctDNA cell targeting and integration. Additionally, we found that ctDNA may alter the treatment response of MM and pancreatic cancer models. This study shows that retrotransposon DNA sequences promote cancer gene transfer. However, because cell-free DNA has been detected in physiological and other pathological conditions, our findings have a broader impact than just cancer. Furthermore, the discovery that transposon DNA sequences mediate tissue-specific targeting will open up a new avenue for the delivery of genes and therapies.

Circulating Tumor DNA Analysis Guiding Adjuvant Therapy in Stage II Colon Cancer.

BACKGROUND: The role of adjuvant chemotherapy in stage II colon cancer continues to be debated. The presence of circulating tumor DNA (ctDNA) after surgery predicts very poor recurrence-free survival, whereas its absence predicts a low risk of recurrence. The benefit of adjuvant chemotherapy for ctDNA-positive patients is not well understood. METHODS: We conducted a trial to assess whether a ctDNA-guided approach could reduce the use of adjuvant chemotherapy without compromising recurrence risk. Patients with stage II colon cancer were randomly assigned in a 2:1 ratio to have treatment decisions guided by either ctDNA results or standard clinicopathological features. For ctDNA-guided management, a ctDNA-positive result at 4 or 7 weeks after surgery prompted oxaliplatin-based or fluoropyrimidine chemotherapy. Patients who were ctDNA-negative were not treated. The primary efficacy end point was recurrence-free survival at 2 years. A key secondary end point was adjuvant chemotherapy use. RESULTS: Of the 455 patients who underwent randomization, 302 were assigned to ctDNA-guided management and 153 to standard management. The median follow-up was 37 months. A lower percentage of patients in the ctDNA-guided group than in the standard-management group received adjuvant chemotherapy (15% vs. 28%; relative risk, 1.82; 95% confidence interval [CI], 1.25 to 2.65). In the evaluation of 2-year recurrence-free survival, ctDNA-guided management was noninferior to standard management (93.5% and 92.4%, respectively; absolute difference, 1.1 percentage points; 95% CI, -4.1 to 6.2 [noninferiority margin, -8.5 percentage points]). Three-year recurrence-free survival was 86.4% among ctDNA-positive patients who received adjuvant chemotherapy and 92.5% among ctDNA-negative patients who did not. CONCLUSIONS: A ctDNA-guided approach to the treatment of stage II colon cancer reduced adjuvant chemotherapy use without compromising recurrence-free survival. (Supported by the Australian National Health and Medical Research Council and others; DYNAMIC Australian New Zealand Clinical Trials Registry number, ACTRN12615000381583.).

Lesion Shedding Model: unraveling site-specific contributions to ctDNA.

Sampling circulating tumor DNA (ctDNA) using liquid biopsies offers clinically important benefits for monitoring cancer progression. A single ctDNA sample represents a mixture of shed tumor DNA from all known and unknown lesions within a patient. Although shedding levels have been suggested to hold the key to identifying targetable lesions and uncovering treatment resistance mechanisms, the amount of DNA shed by any one specific lesion is still not well characterized. We designed the Lesion Shedding Model (LSM) to order lesions from the strongest to the poorest shedding for a given patient. By characterizing the lesion-specific ctDNA shedding levels, we can better understand the mechanisms of shedding and more accurately interpret ctDNA assays to improve their clinical impact. We verified the accuracy of the LSM under controlled conditions using a simulation approach as well as testing the model on three cancer patients. The LSM obtained an accurate partial order of the lesions according to their assigned shedding levels in simulations and its accuracy in identifying the top shedding lesion was not significantly impacted by number of lesions. Applying LSM to three cancer patients, we found that indeed there were lesions that consistently shed more than others into the patients' blood. In two of the patients, the top shedding lesion was one of the only clinically progressing lesions at the time of biopsy suggesting a connection between high ctDNA shedding and clinical progression. The LSM provides a much needed framework with which to understand ctDNA shedding and to accelerate discovery of ctDNA biomarkers. The LSM source code has been available in the IBM BioMedSciAI Github (https://github.com/BiomedSciAI/Geno4SD).

Current and future perspectives of liquid biopsies in genomics-driven oncology.

Precision oncology seeks to leverage molecular information about cancer to improve patient outcomes. Tissue biopsy samples are widely used to characterize tumours but are limited by constraints on sampling frequency and their incomplete representation of the entire tumour bulk. Now, attention is turning to minimally invasive liquid biopsies, which enable analysis of tumour components (including circulating tumour cells and circulating tumour DNA) in bodily fluids such as blood. The potential of liquid biopsies is highlighted by studies that show they can track the evolutionary dynamics and heterogeneity of tumours and can detect very early emergence of therapy resistance, residual disease and recurrence. However, the analytical validity and clinical utility of liquid biopsies must be rigorously demonstrated before this potential can be realized.

Genome-wide cell-free DNA fragmentation in patients with cancer.

Cell-free DNA in the blood provides a non-invasive diagnostic avenue for patients with cancer1. However, characteristics of the origins and molecular features of cell-free DNA are poorly understood. Here we developed an approach to evaluate fragmentation patterns of cell-free DNA across the genome, and found that profiles of healthy individuals reflected nucleosomal patterns of white blood cells, whereas patients with cancer had altered fragmentation profiles. We used this method to analyse the fragmentation profiles of 236 patients with breast, colorectal, lung, ovarian, pancreatic, gastric or bile duct cancer and 245 healthy individuals. A machine learning model that incorporated genome-wide fragmentation features had sensitivities of detection ranging from 57% to more than 99% among the seven cancer types at 98% specificity, with an overall area under the curve value of 0.94. Fragmentation profiles could be used to identify the tissue of origin of the cancers to a limited number of sites in 75% of cases. Combining our approach with mutation-based cell-free DNA analyses detected 91% of patients with cancer. The results of these analyses highlight important properties of cell-free DNA and provide a proof-of-principle approach for the screening, early detection and monitoring of human cancer.

Circulating tumour DNA in patients with hepatocellular carcinoma across tumour stages and treatments.

OBJECTIVE: Circulating tumour DNA (ctDNA) is a promising non-invasive biomarker in cancer. We aim to assess the dynamic of ctDNA in patients with hepatocellular carcinoma (HCC). DESIGN: We analysed 772 plasmas from 173 patients with HCC collected at the time of diagnosis or treatment (n=502), 24 hours after locoregional treatment (n=154) and during follow-up (n=116). For controls, 56 plasmas from patients with chronic liver disease without HCC were analysed. All samples were analysed for cell free DNA (cfDNA) concentration, and for mutations in TERT promoter, CTNNB1, TP53, PIK3CA and NFE2L2 by sequencing and droplet-based digital PCR. Results were compared with 232 corresponding tumour samples. RESULTS: In patients with active HCC, 40.2% of the ctDNA was mutated vs 14.6% in patients with inactive HCC and 1.8% in controls (p<0.001). In active HCC, we identified 27.5% of mutations in TERT promoter, 21.3% in TP53, 13.1% in CTNNB1, 0.4% in PIK3CA and 0.2% in NFE2L2, most of the times similar to those identified in the corresponding tumour. CtDNA mutation rate increased with advanced tumour stages (p<0.001). In 103 patients treated by percutaneous ablation, the presence and number of mutations in the ctDNA before treatment were associated with higher risk of death (p=0.001) and recurrence (p<0.001). Interestingly, cfDNA concentration and detectable mutations increased 24 hours after a locoregional treatment. Among 356 plasmas collected in 53 patients treated by systemic treatments, we detected mutations at baseline in 60.4% of the cases. In patients treated by atezolizumab-bevacizumab, persistence of mutation in ctDNA was associated with radiological progression (63.6% vs 36.4% for disappearance, p=0.019). In two patients progressing under systemic treatments, we detected the occurrence of mutations in CTNNB1 in the plasma that was subclonal in the tumour for one patient and not detectable in the tumour for the other one. CONCLUSION: ctDNA offers dynamic information reflecting tumour biology. It represents a non-invasive tool useful to guide HCC clinical management.

Plasma circulating tumour DNA is a better source for diagnosis and mutational analysis of IVLBCL than tissue DNA.

Diagnosis of intravascular large B-cell lymphoma (IVLBCL) is a challenge due to its heterogeneous clinical presentation and lack of specific markers. This retrospective study investigated the utility of circulating tumour DNA (ctDNA) sequencing for diagnosing IVLBCL and analysing its mutation landscape. A cohort of 34 IVLBCL patients enrolled and underwent plasma ctDNA targeted sequencing. The median plasma ctDNA concentration was 135.0 ng/mL, significantly higher than that in diffuse large B-cell lymphoma (DLBCL) controls. Correlations were found between ctDNA concentration and disease severity indicators, LDH and SF. Mutation analysis revealed frequent mutations in B-cell receptor and NF-κB signalling pathways, including MYD88 (56%), CD79B (44%), TNFAIP3 (38%) and IRF4 (29%). CNS involvement was significantly related with BCL6 and CD58 mutation. Patients with complicated hemophagocytic lymphohistiocytosis had significantly higher mutation rates in B2M. Comparison with DLBCL subtypes showed distinctive mutation profiles in IVLBCL. Moreover, plasma ctDNA detected more mutations with higher variant allele fraction than tissue DNA, suggesting its superiority in sensitivity and accessibility. Dynamic monitoring of ctDNA during treatment correlated with therapeutic responses. This study revealed the role of ctDNA in IVLBCL diagnosis, mutation analysis, and treatment monitoring, offering a promising avenue for improving patient diagnosis in this rare lymphoma subtype.