Subject(s)
Complement Factor D/chemistry , Complement Factor D/deficiency , Complement Factor D/genetics , Complement Pathway, Alternative , Immunologic Deficiency Syndromes/genetics , Female , Hereditary Complement Deficiency Diseases , Humans , Male , Mutation , Pedigree , Protein Conformation , Young AdultABSTRACT
Background: Neoantigens, mutated tumour-specific antigens, are key targets of anti-tumour immunity during checkpoint inhibitor (CPI) treatment. Their identification is fundamental to designing neoantigen-directed therapy. Non-canonical neoantigens arising from the untranslated regions (UTR) of the genome are an overlooked source of immunogenic neoantigens. Here, we describe the landscape of UTR-derived neoantigens and release a computational tool, PrimeCUTR, to predict UTR neoantigens generated by start-gain and stop-loss mutations. Methods: We applied PrimeCUTR to a whole genome sequencing dataset of pre-treatment tumour samples from CPI-treated patients (n = 341). Cancer immunopeptidomic datasets were interrogated to identify MHC class I presentation of UTR neoantigens. Results: Start-gain neoantigens were predicted in 72.7% of patients, while stop-loss mutations were found in 19.3% of patients. While UTR neoantigens only accounted 2.6% of total predicted neoantigen burden, they contributed 12.4% of neoantigens with high dissimilarity to self-proteome. More start-gain neoantigens were found in CPI responders, but this relationship was not significant when correcting for tumour mutational burden. While most UTR neoantigens are private, we identified two recurrent start-gain mutations in melanoma. Using immunopeptidomic datasets, we identify two distinct MHC class I-presented UTR neoantigens: one from a recurrent start-gain mutation in melanoma, and one private to Jurkat cells. Conclusion: PrimeCUTR is a novel tool which complements existing neoantigen discovery approaches and has potential to increase the detection yield of neoantigens in personalised therapeutics, particularly for neoantigens with high dissimilarity to self. Further studies are warranted to confirm the expression and immunogenicity of UTR neoantigens.
Subject(s)
Melanoma , Humans , Antigens, Neoplasm/genetics , Genes, MHC Class I , Mutation , ImmunotherapyABSTRACT
BACKGROUND: Although SARS-CoV-2 vaccines immunogenicity in patients with cancer has been investigated, whether they can significantly improve the severity of COVID-19 in this specific population is undefined. METHODS: Capitalizing on OnCovid (NCT04393974) registry data we reported COVID-19 mortality and proxies of COVID-19 morbidity, including post-COVID-19 outcomes, according to the vaccination status of the included patients. RESULTS: 2090 eligible patients diagnosed with COVID-19 between 02/2020 and 11/2021 were included, of whom 1930 (92.3%) unvaccinated, 91 (4.4%) fully vaccinated and 69 (3.3%) partially vaccinated. With the exception of a higher prevalence of patients from the UK (p = 0.0003) and receiving systemic anticancer therapy at COVID-19 diagnosis (p = 0.0082) among fully vaccinated patients, no demographics/oncological features were associated with vaccination status. The 14-days case fatality rate (CFR) (5.5% vs 20.7%, p = 0.0004) and the 28-days CFR (13.2% vs 27.4%, p = 0.0028) demonstrated a significant improvement for fully vaccinated patients in comparison with unvaccinated patients. The receipt of prior full vaccination was also associated with reduced symptomatic COVID-19 (79.1% vs 88.5%, p = 0.0070), need of COVID-19 oriented therapy (34.9% vs 63.2%, p < 0.0001), complications from COVID-19 (28.6% vs 39.4%, p = 0.0379), hospitalizations due to COVID-19 (42.2% vs 52.5%, p = 0.0007) and oxygen therapy requirement (35.7% vs 52%, p = 0.0036). Following Inverse Probability Treatment Weighting (IPTW) procedure no statistically significant difference according to the vaccination status was confirmed; however, all COVID-19 related outcomes were concordantly in favour of full vaccination. Among the 1228 (58.8%) patients who underwent a formal reassessment at participating centres after COVID-19 resolution, fully vaccinated patients experienced less sequelae than unvaccinated patients (6.7% vs 17.2%, p = 0.0320). CONCLUSIONS: This analysis provides initial evidence in support of the beneficial effect of SARS-CoV-2 vaccines against morbidity and mortality from COVID-19 in patients with cancer.
Subject(s)
COVID-19 , Neoplasms , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Testing , COVID-19 Vaccines , Humans , Morbidity , Neoplasms/complications , Neoplasms/therapy , SARS-CoV-2 , VaccinationABSTRACT
An increased mortality risk was observed in patients with cancer during the first wave of COVID-19. Here, we describe determinants of mortality in patients with solid cancer comparing the first and second waves of COVID-19. A retrospective analysis encompassing two waves of COVID-19 (March-May 2020; December 2020-February 2021) was performed. 207 patients with cancer were matched to 452 patients without cancer. Patient demographics and oncological variables such as cancer subtype, staging and anti-cancer treatment were evaluated for association with COVID-19 mortality. Overall mortality was lower in wave two compared to wave one, HR 0.41 (95% CI: 0.30-0.56). In patients with cancer, mortality was 43.6% in wave one and 15.9% in wave two. In hospitalized patients, after adjusting for age, ethnicity and co-morbidities, a history of cancer was associated with increased mortality in wave one but not wave two. In summary, the second UK wave of COVID-19 is associated with lower mortality in hospitalized patients. A history of solid cancer was not associated with increased mortality despite the dominance of the more transmissible B.1.1.7 SARS-CoV-2 variant. In both waves, metastatic disease and systemic anti-cancer treatment appeared to be independent risk factors for death within the combined cancer cohort.
ABSTRACT
BACKGROUND: Despite high contagiousness and rapid spread, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to heterogeneous outcomes across affected nations. Within Europe (EU), the United Kingdom (UK) is the most severely affected country, with a death toll in excess of 100,000 as of January 2021. We aimed to compare the national impact of coronavirus disease 2019 (COVID-19) on the risk of death in UK patients with cancer versus those in continental EU. METHODS: We performed a retrospective analysis of the OnCovid study database, a European registry of patients with cancer consecutively diagnosed with COVID-19 in 27 centres from 27th February to 10th September 2020. We analysed case fatality rates and risk of death at 30 days and 6 months stratified by region of origin (UK versus EU). We compared patient characteristics at baseline including oncological and COVID-19-specific therapy across UK and EU cohorts and evaluated the association of these factors with the risk of adverse outcomes in multivariable Cox regression models. FINDINGS: Compared with EU (n = 924), UK patients (n = 468) were characterised by higher case fatality rates (40.38% versus 26.5%, p < 0.0001) and higher risk of death at 30 days (hazard ratio [HR], 1.64 [95% confidence interval {CI}, 1.36-1.99]) and 6 months after COVID-19 diagnosis (47.64% versus 33.33%; p < 0.0001; HR, 1.59 [95% CI, 1.33-1.88]). UK patients were more often men, were of older age and have more comorbidities than EU counterparts (p < 0.01). Receipt of anticancer therapy was lower in UK than in EU patients (p < 0.001). Despite equal proportions of complicated COVID-19, rates of intensive care admission and use of mechanical ventilation, UK patients with cancer were less likely to receive anti-COVID-19 therapies including corticosteroids, antivirals and interleukin-6 antagonists (p < 0.0001). Multivariable analyses adjusted for imbalanced prognostic factors confirmed the UK cohort to be characterised by worse risk of death at 30 days and 6 months, independent of the patient's age, gender, tumour stage and status; number of comorbidities; COVID-19 severity and receipt of anticancer and anti-COVID-19 therapy. Rates of permanent cessation of anticancer therapy after COVID-19 were similar in the UK and EU cohorts. INTERPRETATION: UK patients with cancer have been more severely impacted by the unfolding of the COVID-19 pandemic despite societal risk mitigation factors and rapid deferral of anticancer therapy. The increased frailty of UK patients with cancer highlights high-risk groups that should be prioritised for anti-SARS-CoV-2 vaccination. Continued evaluation of long-term outcomes is warranted.
Subject(s)
COVID-19/epidemiology , Neoplasms/complications , Aged , COVID-19/therapy , Comorbidity , Europe/epidemiology , Female , Humans , Male , Middle Aged , Registries , SARS-CoV-2 , United Kingdom/epidemiology , COVID-19 Drug TreatmentABSTRACT
BACKGROUND: Patients with cancer are particularly susceptible to SARS-CoV-2 infection. The systemic inflammatory response is a pathogenic mechanism shared by cancer progression and COVID-19. We investigated systemic inflammation as a driver of severity and mortality from COVID-19, evaluating the prognostic role of commonly used inflammatory indices in SARS-CoV-2-infected patients with cancer accrued to the OnCovid study. METHODS: In a multicenter cohort of SARS-CoV-2-infected patients with cancer in Europe, we evaluated dynamic changes in neutrophil:lymphocyte ratio (NLR); platelet:lymphocyte ratio (PLR); Prognostic Nutritional Index (PNI), renamed the OnCovid Inflammatory Score (OIS); modified Glasgow Prognostic Score (mGPS); and Prognostic Index (PI) in relation to oncological and COVID-19 infection features, testing their prognostic potential in independent training (n=529) and validation (n=542) sets. RESULTS: We evaluated 1071 eligible patients, of which 625 (58.3%) were men, and 420 were patients with malignancy in advanced stage (39.2%), most commonly genitourinary (n=216, 20.2%). 844 (78.8%) had ≥1 comorbidity and 754 (70.4%) had ≥1 COVID-19 complication. NLR, OIS, and mGPS worsened at COVID-19 diagnosis compared with pre-COVID-19 measurement (p<0.01), recovering in survivors to pre-COVID-19 levels. Patients in poorer risk categories for each index except the PLR exhibited higher mortality rates (p<0.001) and shorter median overall survival in the training and validation sets (p<0.01). Multivariable analyses revealed the OIS to be most independently predictive of survival (validation set HR 2.48, 95% CI 1.47 to 4.20, p=0.001; adjusted concordance index score 0.611). CONCLUSIONS: Systemic inflammation is a validated prognostic domain in SARS-CoV-2-infected patients with cancer and can be used as a bedside predictor of adverse outcome. Lymphocytopenia and hypoalbuminemia as computed by the OIS are independently predictive of severe COVID-19, supporting their use for risk stratification. Reversal of the COVID-19-induced proinflammatory state is a putative therapeutic strategy in patients with cancer.
Subject(s)
COVID-19 Drug Treatment , Neoplasms/virology , Systemic Inflammatory Response Syndrome/etiology , Adult , Aged , Aged, 80 and over , Blood Cell Count , COVID-19/complications , COVID-19/mortality , COVID-19 Testing , Comorbidity , Female , Humans , Male , Middle Aged , Multivariate Analysis , Neoplasms/epidemiology , Prognosis , Systemic Inflammatory Response Syndrome/virology , Young AdultABSTRACT
BACKGROUND: The COVID-19 pandemic remains a pressing concern to patients with cancer as countries enter the second peak of the pandemic and beyond. It remains unclear whether cancer and its treatment contribute an independent risk for mortality in COVID-19. METHODS: We included patients at a London tertiary hospital with laboratory confirmed SARS-CoV-2 infection. All patients with a history of solid cancer were included. Age- and sex-matched patients without cancer were randomly selected. Patients with hematological malignancies were excluded. RESULTS: We identified 94 patients with cancer, matched to 226 patients without cancer. After adjusting for age, ethnicity, and co-morbidities, patients with cancer had increased mortality following COVID-19 (HR 1.57, 95% CI:1.04-2.4, p = 0.03). Increasing age (HR 1.49 every 10 years, 95% CI:1.25-1.8, p < 0.001), South Asian ethnicity (HR 2.92, 95% CI:1.73-4.9, p < 0.001), and cerebrovascular disease (HR 1.93, 95% CI:1.18-3.2, p = 0.008) also predicted mortality. Within the cancer cohort, systemic anti-cancer therapy (SACT) within 60 days of COVID-19 diagnosis was an independent risk factor for mortality (HR 2.30, 95% CI: 1.16-4.6, p = 0.02). CONCLUSIONS: Along with known risk factors, cancer and SACT confer an independent risk for mortality following COVID-19. Further studies are needed to understand the socio-economic influences and pathophysiology of these associations.
ABSTRACT
We describe the outcomes in cancer patients during the initial outbreak of the COVID-19 in Europe from the retrospective, multi-center observational OnCovid study. We identified 204 cancer patients from eight centers in the United Kingdom, Italy, and Spain aged > 18 (mean = 69) and diagnosed with COVID-19 between February 26th and April 1st, 2020. A total of 127 (62%) were male, 184 (91%) had a diagnosis of solid malignancy, and 103 (51%) had non-metastatic disease. A total of 161 (79%) had > 1 co-morbidity. A total of 141 (69%) patients had > 1 COVID-19 complication. A total of 36 (19%) were escalated to high-dependency or intensive care. A total of 59 (29%) died, 53 (26%) were discharged, and 92 (45%) were in-hospital survivors. Mortality was higher in patients aged > 65 (36% versus 16%), in those with > 2 co-morbidities (40% versus 18%) and developing > 1 complication from COVID-19 (38% versus 4%, p = 0.004). Multi-variable analyses confirmed age > 65 and > 2 co-morbidities to predict for patient mortality independent of tumor stage, active malignancy, or anticancer therapy. During the early outbreak of SARS-CoV-2 infection in Europe co-morbid burden and advancing age predicted for adverse disease course in cancer patients. The ongoing OnCovid study will allow us to compare risks and outcomes in cancer patients between the initial and later stages of the COVID-19 pandemic.