Circulating Tumour DNA in Melanoma-Clinic Ready?

PURPOSE OF REVIEW: Liquid biopsies, including circulating tumour DNA (ctDNA), can inform a variety of clinical questions. This review examines the potential role of ctDNA as a clinical tool to inform clinical decision-making from early to late stage cutaneous melanoma. RECENT FINDINGS: In pre-clinical studies, ctDNA has been shown to detect minimal residual disease and molecular relapse; predict and monitor response to therapy; and identify key resistance mechanisms. Here, we examine the potential utility of ctDNA and discuss its limitations for use in patients with melanoma. We present novel clinical trials, which are testing its value as a tool to augment clinical decision-making. Finally, we discuss the steps that are needed to ensure that ctDNA is used optimally in order to improve outcomes for patients with melanoma. Preclinical studies have shown that ctDNA has huge potential to provide real-time information about disease status in patients with melanoma. It is now time to test it rigorously within clinical trials to assess how it can be optimally used to benefit patients in the clinic.

Patient engagement in melanoma research: from bench to bedside.

Advances in research have transformed the management of melanoma in the past decade. In parallel, patient advocacy has gained traction, and funders are increasingly prioritizing patient and public involvement. Here we discuss the ways in which patients and the public can be engaged in different stages of the research process, from developing, prioritizing and refining the research question to preclinical studies and clinical trials, then finally to ongoing research in the clinic. We discuss the challenges and opportunities that exist at each stage in order to ensure that a representative population of patients and the public contribute to melanoma research both now and in the future.

Mining nucleic acid "omics" to boost liquid biopsy in cancer.

Treatments for cancer patients are becoming increasingly complex, and there is a growing desire from clinicians and patients for biomarkers that can account for this complexity to support informed decisions about clinical care. To achieve precision medicine, the new generation of biomarkers must reflect the spatial and temporal heterogeneity of cancer biology both between patients and within an individual patient. Mining the different layers of 'omics in a multi-modal way from a minimally invasive, easily repeatable, liquid biopsy has increasing potential in a range of clinical applications, and for improving our understanding of treatment response and resistance. Here, we detail the recent developments and methods allowing exploration of genomic, epigenomic, transcriptomic, and fragmentomic layers of 'omics from liquid biopsy, and their integration in a range of applications. We also consider the specific challenges that are posed by the clinical implementation of multi-omic liquid biopsies.

Ibrutinib as first-line therapy for mantle cell lymphoma: a multicenter, real-world UK study.

ABSTRACT: During the COVID-19 pandemic, ibrutinib with or without rituximab was approved in England for initial treatment of mantle cell lymphoma (MCL) instead of immunochemotherapy. Because limited data are available in this setting, we conducted an observational cohort study evaluating safety and efficacy. Adults receiving ibrutinib with or without rituximab for untreated MCL were evaluated for treatment toxicity, response, and survival, including outcomes in high-risk MCL (TP53 mutation/deletion/p53 overexpression, blastoid/pleomorphic, or Ki67 ≥ 30%). A total of 149 patients from 43 participating centers were enrolled: 74.1% male, median age 75 years, 75.2% Eastern Cooperative Oncology Group status of 0 to 1, 36.2% high-risk, and 8.9% autologous transplant candidates. All patients received ≥1 cycle ibrutinib (median, 8 cycles), 39.0% with rituximab. Grade ≥3 toxicity occurred in 20.3%, and 33.8% required dose reductions/delays. At 15.6-month median follow-up, 41.6% discontinued ibrutinib, 8.1% due to toxicity. Of 104 response-assessed patients, overall (ORR) and complete response (CR) rates were 71.2% and 20.2%, respectively. ORR was 77.3% (low risk) vs 59.0% (high risk) (P = .05) and 78.7% (ibrutinib-rituximab) vs 64.9% (ibrutinib; P = .13). Median progression-free survival (PFS) was 26.0 months (all patients); 13.7 months (high risk) vs not reached (NR) (low risk; hazard ratio [HR], 2.19; P = .004). Median overall survival was NR (all); 14.8 months (high risk) vs NR (low risk; HR, 2.36; P = .005). Median post-ibrutinib survival was 1.4 months, longer in 41.9% patients receiving subsequent treatment (median, 8.6 vs 0.6 months; HR, 0.36; P = .002). Ibrutinib with or without rituximab was effective and well tolerated as first-line treatment of MCL, including older and transplant-ineligible patients. PFS and OS were significantly inferior in one-third of patients with high-risk disease and those unsuitable for post-ibrutinib treatment, highlighting the need for novel approaches in these groups.

Outlier detection of vital sign trajectories from COVID-19 patients.

In this work, we present a novel trajectory comparison algorithm to identify abnormal vital sign trends, with the aim of improving recognition of deteriorating health.There is growing interest in continuous wearable vital sign sensors for monitoring patients remotely at home. These monitors are usually coupled to an alerting system, which is triggered when vital sign measurements fall outside a predefined normal range. Trends in vital signs, such as increasing heart rate, are often indicative of deteriorating health, but are rarely incorporated into alerting systems.We introduce a dynamic time warp distance-based measure to compare time series trajectories. We split each multi-variable sign time series into 180 minute, non-overlapping epochs. We then calculate the distance between all pairs of epochs. Each epoch is characterized by its mean pairwise distance (average link distance) to all other epochs, with clusters forming with nearby epochs.We demonstrate in synthetically generated data that this method can identify abnormal epochs and cluster epochs with similar trajectories. We then apply this method to a real-world data set of vital signs from 8 patients who had recently been discharged from hospital after contracting COVID-19. We show how outlier epochs correspond well with the abnormal vital signs and identify patients who were subsequently readmitted to hospital.

Circulating tumour DNA - looking beyond the blood.

Over the past decade, various liquid biopsy techniques have emerged as viable alternatives to the analysis of traditional tissue biopsy samples. Such surrogate 'biopsies' offer numerous advantages, including the relative ease of obtaining serial samples and overcoming the issues of interpreting one or more small tissue samples that might not reflect the entire tumour burden. To date, the majority of research in the area of liquid biopsies has focused on blood-based biomarkers, predominantly using plasma-derived circulating tumour DNA (ctDNA). However, ctDNA can also be obtained from various non-blood sources and these might offer unique advantages over plasma ctDNA. In this Review, we discuss advances in the analysis of ctDNA from non-blood sources, focusing on urine, cerebrospinal fluid, and pleural or peritoneal fluid, but also consider other sources of ctDNA. We discuss how these alternative sources can have a distinct yet complementary role to that of blood ctDNA analysis and consider various technical aspects of non-blood ctDNA assay development. We also reflect on the settings in which non-blood ctDNA can offer distinct advantages over plasma ctDNA and explore some of the challenges associated with translating these alternative assays from academia into clinical use.

An International Comparison of Presentation, Outcomes and CORONET Predictive Score Performance in Patients with Cancer Presenting with COVID-19 across Different Pandemic Waves.

Patients with cancer have been shown to have increased risk of COVID-19 severity. We previously built and validated the COVID-19 Risk in Oncology Evaluation Tool (CORONET) to predict the likely severity of COVID-19 in patients with active cancer who present to hospital. We assessed the differences in presentation and outcomes of patients with cancer and COVID-19, depending on the wave of the pandemic. We examined differences in features at presentation and outcomes in patients worldwide, depending on the waves of the pandemic: wave 1 D614G (n = 1430), wave 2 Alpha (n = 475), and wave 4 Omicron variant (n = 63, UK and Spain only). The performance of CORONET was evaluated on 258, 48, and 54 patients for each wave, respectively. We found that mortality rates were reduced in subsequent waves. The majority of patients were vaccinated in wave 4, and 94% were treated with steroids if they required oxygen. The stages of cancer and the median ages of patients significantly differed, but features associated with worse COVID-19 outcomes remained predictive and did not differ between waves. The CORONET tool performed well in all waves, with scores in an area under the curve (AUC) of >0.72. We concluded that patients with cancer who present to hospital with COVID-19 have similar features of severity, which remain discriminatory despite differences in variants and vaccination status. Survival improved following the first wave of the pandemic, which may be associated with vaccination and the increased steroid use in those patients requiring oxygen. The CORONET model demonstrated good performance, independent of the SARS-CoV-2 variants.

Establishment of CORONET, COVID-19 Risk in Oncology Evaluation Tool, to Identify Patients With Cancer at Low Versus High Risk of Severe Complications of COVID-19 Disease On Presentation to Hospital.

PURPOSE: Patients with cancer are at increased risk of severe COVID-19 disease, but have heterogeneous presentations and outcomes. Decision-making tools for hospital admission, severity prediction, and increased monitoring for early intervention are critical. We sought to identify features of COVID-19 disease in patients with cancer predicting severe disease and build a decision support online tool, COVID-19 Risk in Oncology Evaluation Tool (CORONET). METHODS: Patients with active cancer (stage I-IV) and laboratory-confirmed COVID-19 disease presenting to hospitals worldwide were included. Discharge (within 24 hours), admission (≥ 24 hours inpatient), oxygen (O2) requirement, and death were combined in a 0-3 point severity scale. Association of features with outcomes were investigated using Lasso regression and Random Forest combined with Shapley Additive Explanations. The CORONET model was then examined in the entire cohort to build an online CORONET decision support tool. Admission and severe disease thresholds were established through pragmatically defined cost functions. Finally, the CORONET model was validated on an external cohort. RESULTS: The model development data set comprised 920 patients, with median age 70 (range 5-99) years, 56% males, 44% females, and 81% solid versus 19% hematologic cancers. In derivation, Random Forest demonstrated superior performance over Lasso with lower mean squared error (0.801 v 0.807) and was selected for development. During validation (n = 282 patients), the performance of CORONET varied depending on the country cohort. CORONET cutoffs for admission and mortality of 1.0 and 2.3 were established. The CORONET decision support tool recommended admission for 95% of patients eventually requiring oxygen and 97% of those who died (94% and 98% in validation, respectively). The specificity for mortality prediction was 92% and 83% in derivation and validation, respectively. Shapley Additive Explanations revealed that National Early Warning Score 2, C-reactive protein, and albumin were the most important features contributing to COVID-19 severity prediction in patients with cancer at time of hospital presentation. CONCLUSION: CORONET, a decision support tool validated in health care systems worldwide, can aid admission decisions and predict COVID-19 severity in patients with cancer.

Systemic ALCL Treated in Routine Clinical Practice: Outcomes Following First-Line Chemotherapy from a Multicentre Cohort.

INTRODUCTION: Brentuximab vedotin (BV)-CHP is the new standard regimen for first-line treatment of systemic anaplastic large cell lymphoma (sALCL). We undertook a retrospective analysis of consecutive patients diagnosed with sALCL, treated in routine practice, to serve as a benchmark analysis for comparison BV-CHP efficacy in routine practice. METHODS: Patients aged 16 years or older with sALCL treated in seven UK and Australian centres and from 14 additional centres from the UK Haematological Malignancy Research Network database (n = 214). Treatment allocation was clinician choice and included best supportive care (BSC). Main outcomes were time to treatment failure (TTF) and overall survival (OS). Multivariable analysis for predictors of both TTF and OS was also undertaken. RESULTS: The median age 52 years (range 16-93), 18% ECOG ≥ 3 and 40% of cases were ALK positive. CHOP (cyclophosphamide, adriamycin, vincristine, prednisolone) was employed in 152 (71%) of patients and CHOEP (CHOP + etoposide) in 4% of patients. For CHOP-treated patients overall response rate (ORR) was 65% and complete response (CR) 47%. Only 9% of patients underwent autologous stem cell transplant (ASCT). With 57 months median follow-up, 4-year TTF and OS were 41.2% (95% CI 33.1-49.1) and 58.9% (95% CI 50.3-66.5) respectively. Multivariable analysis showed ALK+ status was independently associated with superior TTF (HR 0.36, 95% CI 0.21-0.63) but not OS (0.44, 95% CI 0.18-1.07). DISCUSSION: We present a retrospective analysis with mature follow-up of one of the largest multicentre populations of sALCL available, comparable to similar large retrospective studies. ALK status remains a strong predictor of outcomes. CONCLUSION: These data serve as a robust benchmark for BV-CHP as the new standard of care for sALCL. Similar real-world evidence with BV-CHP will be desirable to confirm the findings of ECHELON-2.

Haematological malignancy and nosocomial transmission are associated with an increased risk of death from COVID-19: results of a multi-center UK cohort.

The COVID-19 pandemic has been a disruptive event for cancer patients, especially those with haematological malignancies (HM). They may experience a more severe clinical course due to impaired immune responses. This multi-center retrospective UK audit identified cancer patients who had SARS-CoV-2 infection between 1 March and 10 June 2020 and collected data pertaining to cancer history, COVID-19 presentation and outcomes. In total, 179 patients were identified with a median age of 72 (IQR 61, 81) and follow-up of 44 days (IQR 42, 45). Forty-one percent were female and the overall mortality was 37%. Twenty-nine percent had HM and of these, those treated with chemotherapy in the preceding 28 days to COVID-19 diagnosis had worse outcome compared with solid malignancy (SM): 62% versus 19% died [HR 8.33 (95% CI, 2.56-25), p < 0.001]. Definite or probable nosocomial SARS-CoV-2 transmission accounted for 16% of cases and was associated with increased risk of death (HR 2.47, 95% CI 1.43-4.29, p = 0.001). Patients with haematological malignancies and those who acquire nosocomial transmission are at increased risk of death. Therefore, there is an urgent need to reassess shielding advice, reinforce stringent infection control, and ensure regular patient and staff testing to prevent nosocomial transmission.