Serial biopsy of pancreatic ductal adenocarcinoma (PDAC), to chart tumour evolution presents a significant challenge. We examined the utility of circulating free DNA (cfDNA) as a minimally invasive approach across a cohort of 55 treatment-naïve patients with PDAC; 31 with metastatic and 24 with locally advanced disease. Somatic mutations in cfDNA were detected using next generation sequencing in 15/24 (62.5%) and 27/31 (87%) of patients with locally advanced and metastatic disease, respectively. Copy number changes were detected in cfDNA of 10 patients of whom 7 exhibited gain of chromosome 12p harbouring KRAS as well as a canonical KRAS codon 12 mutation. In multivariable Cox Regression analysis, we show for the first time that patients with KRAS copy number gain and KRAS mutation have significantly worse outcomes, suggesting that this may be linked to PDAC progression. The simple cfDNA assay we describe will enable determination of the presence of KRAS copy number gain and KRAS mutations in larger studies and clinical trials.

To assess efficacy and toxicity of combination immunotherapy with ipilimumab plus nivolumab in routine practice in a retrospective multicentre cohort of patients with advanced melanoma. This retrospective analysis included patients with advanced melanoma treated with ipilimumab and nivolumab between October 2015 and January 2020 at six centres in Australia, Europe and the United States of America. We describe efficacy outcomes (overall survival [OS], progression-free survival [PFS] and objective response rate [ORR]) in treatment-naïve and pre-treated patients, with and without brain metastases, plus treatment-related adverse events (trAEs) in all patients treated. A total of 697 patients were identified; 472 were treatment-naïve of which 138 (29.2%) had brain metastases, and 225 were previously treated of which 102 (45.3%) had brain metastases. At baseline, 32.3% had stage M1c and 34.4% stage M1d disease. Lactate dehydrogenase was high in 280 patients (40.2%). With a median follow-up of 25.9 months, median OS in the 334 treatment-naïve patients without brain metastases was 53.7 months (95% confidence interval [CI] 40.8-NR) and 38.7 months (95% CI 18.6-NR) for the 138 treatment-naïve patients with brain metastases. For the entire cohort the ORR was 48%, for treatment-naïve patients without brain metastases ORR was 56.6% with a median PFS of was 13.7 months (95% CI 9.6-26.5). Median PFS was 7.9 months (95% CI 5.8-10.4) and OS 38 months (95% CI 31-NR) for the entire cohort. Grade 3-4 trAE were reported in 44% of patients, and 4 (0.7%) treatment-related deaths (1 pneumonitis, 2 myocarditis and 1 colitis) were recorded. The outcome and toxicity of combination immunotherapy with ipilimumab and nivolumab in a real-world patient population are similar to those reported in pivotal trials.

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.

Extra-pulmonary neuroendocrine carcinomas (EP-NECs) are lethal cancers with limited treatment options. Identification of contributing factors to the observed heterogeneity of clinical outcomes within the EP-NEC family is warranted, to enable identification of effective treatments. A multicentre retrospective study investigated potential differences in “real-world” treatment/survival outcomes between small-cell (SC) versus (vs.) non-SC EP-NECs. One-hundred and seventy patients were included: 77 (45.3%) had SC EP-NECs and 93 (54.7%) had non-SC EP-NECs. Compared to the SC subgroup, the non-SC subgroup had the following features: (1) a lower mean Ki-67 index (69.3% vs. 78.7%; p = 0.002); (2) a lower proportion of cases with a Ki-67 index of ≥55% (73.9% vs. 88.7%; p = 0.025); (3) reduced sensitivity to first-line platinum/etoposide (objective response rate: 31.6% vs. 55.1%, p = 0.015; and disease control rate; 59.7% vs. 79.6%, p = 0.027); (4) worse progression-free survival (PFS) (adjusted-HR = 1.615, p = 0.016) and overall survival (OS) (adjusted-HR = 1.640, p = 0.015) in the advanced setting. Within the advanced EP-NEC cohort, subgroups according to morphological subtype and Ki-67 index (<55% vs. ≥55%) had significantly different PFS (adjusted-p = 0.021) and OS (adjusted-p = 0.051), with the non-SC subgroup with a Ki-67 index of <55% and non-SC subgroup with a Ki-67 index of ≥55% showing the best and worst outcomes, respectively. To conclude, the morphological subtype of EP-NEC provides complementary information to the Ki-67 index and may aid identification of patients who could benefit from alternative first-line treatment strategies to platinum/etoposide.

Background: The goal of our study is to investigate whether the methylation levels of AHCY and CBS promoters are related to the risk of cerebral infarction by detecting the methylation level of AHCY and CBS genes. Methods: We extracted peripheral venous blood from 152 patients with cerebral infarction and 152 gender- and age-matched healthy controls, and determined methylation levels of AHCY and CBS promoters using quantitative methylation-specific polymerase chain reaction. We used the percentage of methylation reference (PMR) to indicate gene methylation level. Results: We compared the promoter methylation levels of two genes (AHCY and CBS) in peripheral blood DNA between the cerebral infarction case group and the control group. Our study showed no significant difference in AHCY promoter methylation between case and control. Subgroup analysis by gender showed that the methylation level of AHCY in males in the case group was lower than that in the control group, but the difference was not statistically significant in females. In a subgroup analysis by age, there was no significant difference in the AHCY methylation level between the case and control in the young group (≤44 years old). However, the level of AHCY gene methylation in the middle-aged group (45–59 years old) was significantly higher and the aged group (≥60 years old) was significantly lower than that in the control groups. However, CBS promoter methylation levels were significantly lower in the case group than in the control group (median PMR: 70.20% vs 104.10%, P = 3.71E-10). In addition, the CBS methylation levels of males and females in the case group were significantly lower than those in the control group (male: 64.33% vs 105%, P = 2.667E-08; female: 78.05% vs 102.8%, P = 0.003). We also found that the CBS levels in the young (23–44), middle-aged (45–59), and older (60–90) groups were significantly lower than those in the control group (young group: 69.97% vs 114.71%; P = 0.015; middle-aged group: 56.04% vs 91.71%; P = 6.744E-06; older group: 81.6% vs 119.35%; P = 2.644E-04). Our ROC curve analysis of CBS hypomethylation showed an area under the curve of 0.713, a sensitivity of 67.4%, and a specificity of 74.0%. Conclusion: Our study suggests that hypomethylation of the CBS promoter may be closely related to the risk of cerebral infarction and may be used as a non-invasive diagnostic biomarker for cerebral infarction.

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.