Sir Peter MacCallum Department of Oncology - Research Publications

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    22. International Multicenter Study Comparing Cancer to Non-Cancer Patients with COVID-19: Impact of Risk Factors and Treatment Modalities on Outcome
    Hachem, RY ; Chaftari, A-M ; Masayuki, N ; Hamerschlak, N ; Dagher, H ; Jiang, Y ; Siddiqui, B ; Bayle, A ; Somer, R ; Cruz, AF ; Gorak, E ; Bhinder, A ; Mori, N ; Datoguia, T ; Shelanski, S ; Dragvich, T ; Kiat, YEV ; Fakhreddine, S ; Hanna, PA ; Chemaly, RF ; Mulanovich, VE ; Adachi, J ; Borjan, J ; Khawaja, F ; Granwehr, B ; John, T ; Guevara, EY ; Torres, HA ; Slavin, M ; Teh, B ; Subbiah, V ; Kontoyiannis, DP ; Malek, A ; Raad, II (Oxford University Press (OUP), 2021-12-04)
    Abstract Background Given the limited collaborative international studies that evaluated COVID-19 in patients with cancer in comparison to patients without cancer, we aimed to determine the independent risk factors associated with increased 30-day mortality and the impact of novel treatment modalities in a large group of cancer and non-cancer patients with COVID-19 from multiple countries. Methods We retrospectively collected de-identified data on cancer and non-cancer patients diagnosed with COVID-19 between January and November 2020, at 16 centers in Asia, Australia, Europe, North America, and South America. A logistic regression model was used to identify independent predictors of all-cause mortality within 30 days after COVID-19 diagnosis. Results Of the total 4015 COVID-19 confirmed patients entered, we analyzed 3966 patients, 1115 cancer and 2851 non-cancer patients. Cancer patients were older than non-cancer patients (median age, 61 vs 50 years; p< 0.0001); more likely to be pancytopenic , had pulmonary disorders, hypertension, diabetes mellitus. In addition, they were more likely to present with higher inflammatory biomarkers (D-dimer, ferritin and procalcitonin), but were less likely to present with clinical symptoms. By multivariable logistic regression analysis, cancer was an independent risk factor for 30-day mortality (OR 1.46; 95% CI 1.03 to 2.07; p=0.035). Older age (≥65 years) was the strongest predictor of 30-day mortality in all patients (OR 4.55; 95% CI 3.34 to 6.20; p< 0.0001). Remdesivir was the only therapeutic agent independently associated with decreased 30-day mortality (OR 0.58; CI 0.39-0.88; p=0.009). Among patients on low-flow oxygen at admission, patients who received remdesivir had a lower 30-day mortality rate than those who were on high flow oxygen (5.9% vs 17.6%; p=0.03). Patients transfused with convalescent plasma within 1 day of diagnosis had a lower 30-day mortality rate than those transfused later (1% vs 7%, p=0.04). Conclusion Cancer is an independent risk factor for increased 30-day all-cause mortality from COVID-19. Remdesivir, particularly in patients receiving low-flow oxygen, can reduce 30-day all-cause mortality, as well as convalescent plasma given early after COVID-19 diagnosis. Disclosures Roy F. Chemaly, MD, MPH, FACP, FIDSA, AiCuris (Grant/Research Support)Ansun Biopharma (Consultant, Grant/Research Support)Chimerix (Consultant, Grant/Research Support)Clinigen (Consultant)Genentech (Consultant, Grant/Research Support)Janssen (Consultant, Grant/Research Support)Karius (Grant/Research Support)Merck (Consultant, Grant/Research Support)Molecular Partners (Consultant, Advisor or Review Panel member)Novartis (Grant/Research Support)Oxford Immunotec (Consultant, Grant/Research Support)Partner Therapeutics (Consultant)Pulmotec (Consultant, Grant/Research Support)Shire/Takeda (Consultant, Grant/Research Support)Viracor (Grant/Research Support)Xenex (Grant/Research Support) Fareed Khawaja, MBBS, Eurofins Viracor (Research Grant or Support) Monica Slavin, MBBS,MD, F2G (Advisor or Review Panel member)Merck (Advisor or Review Panel member)Pfizer (Advisor or Review Panel member) Dimitrios P. Kontoyiannis, MD, Astellas (Consultant)Cidara Therapeutics (Advisor or Review Panel member)Gilead Sciences (Consultant, Grant/Research Support, Other Financial or Material Support, Honoraria)
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    Water or Medium: Dose Specification in Trials and Real Life
    Kron, T ; Hardcastle, N (IOP Publishing, 2020-10-16)
    Abstract Radiation dose is the therapeutic agent in radiotherapy where the objective is to maximise radiation dose to a target while minimising the dose to surrounding healthy tissues. Dose in this context is typically associated with the quantity “absorbed dose” as energy deposited per unit mass and measured in J/kg of tissue. However, even if high doses are delivered (no stochastic distribution considered) and photon or electron radiation is considered (no neutrons or heavy charged particles), there will be differences in the actual dose delivered to different tissue types as the stopping power for the electrons that deliver the vast majority of dose varies with elemental composition. Historically, radiation beam calibration and dose calculations were performed in water as a readily available, easily standardised material that closely matches the radiation properties of many human tissues. However, many superior dose calculation algorithms that have recently become available due to improved computer power (Monte Carlo Calculations, Acuros) calculate dose as deposited in the medium. The present paper examines arguments for both and proposes that based on the current scientific and political developments specification of dose as dose to medium would be the more robust and future proof choice.
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    Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing
    Cortes-Ciriano, I ; Lee, JJ-K ; Xi, R ; Jain, D ; Jung, YL ; Yang, L ; Gordenin, D ; Klimczak, LJ ; Zhang, C-Z ; Pellman, DS ; Park, PJ ; Akdemir, KC ; Alvarez, EG ; Baez-Ortega, A ; Beroukhim, R ; Boutros, PC ; Bowtell, DDL ; Brors, B ; Burns, KH ; Campbell, PJ ; Chan, K ; Chen, K ; Dueso-Barroso, A ; Dunford, AJ ; Edwards, PA ; Estivill, X ; Etemadmoghadam, D ; Feuerbach, L ; Fink, JL ; Frenkel-Morgenstern, M ; Garsed, DW ; Gerstein, M ; Gordenin, DA ; Haan, D ; Haber, JE ; Hess, JM ; Hutter, B ; Imielinski, M ; Jones, DTW ; Ju, YS ; Kazanov, MD ; Koh, Y ; Korbel, JO ; Kumar, K ; Lee, EA ; Li, Y ; Lynch, AG ; Macintyre, G ; Markowetz, F ; Martincorena, I ; Martinez-Fundichely, A ; Miyano, S ; Nakagawa, H ; Navarro, FCP ; Ossowski, S ; Pearson, J ; Puiggros, M ; Rippe, K ; Roberts, ND ; Roberts, SA ; Rodriguez-Martin, B ; Schumacher, SE ; Scully, R ; Shackleton, M ; Sidiropoulos, N ; Sieverling, L ; Stewart, C ; Torrents, D ; Tubio, JMC ; Villasante, I ; Waddell, N ; Wala, JA ; Weischenfeldt, J ; Yao, X ; Yoon, S-S ; Zamora, J (NATURE PORTFOLIO, 2020-03)
    Chromothripsis is a mutational phenomenon characterized by massive, clustered genomic rearrangements that occurs in cancer and other diseases. Recent studies in selected cancer types have suggested that chromothripsis may be more common than initially inferred from low-resolution copy-number data. Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), we analyze patterns of chromothripsis across 2,658 tumors from 38 cancer types using whole-genome sequencing data. We find that chromothripsis events are pervasive across cancers, with a frequency of more than 50% in several cancer types. Whereas canonical chromothripsis profiles display oscillations between two copy-number states, a considerable fraction of events involve multiple chromosomes and additional structural alterations. In addition to non-homologous end joining, we detect signatures of replication-associated processes and templated insertions. Chromothripsis contributes to oncogene amplification and to inactivation of genes such as mismatch-repair-related genes. These findings show that chromothripsis is a major process that drives genome evolution in human cancer.