ABSTRACT
Background: COVID-19 infection has poor outcomes for patients (pts) with cancer. Understanding vaccine response as a correlate of protection from severe infection is essential to advise pts regarding protective behaviours and optimal vaccine schedule. This Australian cohort is unique due to low rates of COVID-19 exposure at study entry (July-November 2021). and use of a 3 dose schedule. Pts initially received 2 doses of either BNT162b2 (Pf) at a 3 week interval, or ChadOx1-S (AZ) at a 6 week interval, all then received a 3rd dose, either mRNA-1273 (Mod) or Pf after 2-4 months, and finally a 4th dose at an interval of a further 3 months, for a subset. Methods: SerOzNET (ACTRN12621001004853) has enrolled pts with solid and haematological (haem) cancers prior to initial vaccination. Serial blood samples were processed for serum, PBMC and PMN at timepoints: 0, then 3-4 weeks post dose 1 then 2 then 3 then 4 (where administered). We report here neutralizing antibodies (nAb) against wild type (wt) and delta and omicron variants of concern (VOC);quantitative S-protein IgG antibody (Abbott);Tcell correlates measured by levels of interferon-g (IFN g), tumour necrosis factor-a, interleukins (IL-) 2/ 4/5/13;and epigenetic profiling of T cells. Results: The cohort consists of 401 pts with median age 58 (range 18-85);59% female;128 (32%) haem cancers. 377 (94%) are on current or recent (< 12 months) systemic therapy: 162 (43%) chemotherapy, 62 (16%) immunotherapy, 40 (10%) combined chemo/immunotherapy, 113 (29%) hormonal or targeted therapy. 42 (10%) received anti-CD20 therapy < 12 months, 6 (1.4%) had allogeneic stem cell transplant. NAb levels against wt are available for 256 pts post dose 1, 245 pts post dose 2 and 159 pts post dose 3 (will be updated). Response rates post dose were respectively 27%, 77% and 88%. Pts with haem cancer were less likely to respond to vaccination at any time compared to pts with solid cancer (p < 0.001, chi-squared test). After 3 doses, 3.8% of pts with solid cancer and 27.8% with haem cancer lacked NAb. NAb results to VOC delta are available for 92 pts post dose 2: 25/92 (27%) were negative, compared with a non-response rate to wt of 15% at same time in same pts. IFN-γ-Spike response was detectable in 18/31 (58%) and 24/30 (80%) pts post dose 1 and 2 respectively. 101 pts to date have received a 4th dose;data will be available at the meeting, as will epigenetic profiles and detailed clinicopathological correlations. Conclusions: This interim analysis shows that a significant proportion of pts with haem cancers (27.8%) lack protective Sars-CoV-2 antibodies following 3 vaccinations, whereas only 3.8% of solid cancer pts lack detectable response. Results from other B and T cell parameters may also be important in identifying pts less well protected by vaccination. Follow up is ongoing, response rate post 4th dose will be presented at the meeting.
ABSTRACT
Background: Defining cancer and treatment-related factors which influence protection against COVID-19 following vaccination are important given the worse outcomes following infection in this group. Sophisticated and detailed studies which go beyond a single measure are required particularly with correlation to multiple disease and treatment factors. This study cohort is unique due to (a) very low prior COVID-19 infection at time of sampling (July-Nov 2021), (b) vaccines studied were BNT162b2 (Pf) given 3 weeks apart or ChAdOx1 (AZ) spaced 12 weeks (dose 1, 2) (c) most participants then received a third dose 2 months later (heterologous for AZ). Methods: SerOzNET (ACTRN12621001004853) enrols Australian blood and solid cancer patients prior to vaccination, with serial blood analyses and qualitative measures. We measured neutralizing antibodies (nAb) against SARS-CoV-2 wild type (wt) and variants of concern delta and omicron, quantitative S-protein IgG antibody level (Abbott), and T-cell correlates (interferon-g, tumour necrosis factor-a, interleukins 2/4/5/13) and epigenetic profiling at baseline and 3-4 weeks post dose 1, 2 +/- 3.Results: 379 participants were included, median age 58 years (IQR 47-66) and 60% female. 30% participants had hematological malignancies with the remainder solid organ cancers. 90% patients were on current systemic cancer treatment (most commonly chemotherapy in 41%, chemoimmunotherapy or immunotherapy in 20%). In 331 patients where treatment intent was recorded, 47% was palliative. Only one patient had known prior COVID-19 infection. Of the initial 94 participants who received Pf vaccination, median (IQR) neutralizing antibody titre 4 weeks following dose 2 was 80 (40-160) for SARS-CoV-2 wt and 40 (0-80) for delta variant. Conclusion: Neutralizing antibody titres in this Australian cancer population following Pf vaccination appear lower than those reported elsewhere such as CAPTURE study (Fendler et al, 2021), possibly related to shorter interdose interval. Preliminary data highlights low nAb titres as expected in haematology patients but also in some cases with treatment not traditionally associated with immunosuppression such as hormonal therapy. These results will be updated in February 2022 with third dose, AZ and omicron variant data.
ABSTRACT
This article is intended to explore the behavior of complete genetic sequences of SARS-CoV 2 - P.1 variant, in comparison with the original sequence of SARS-CoV 2, accession number MN908947 (see López and Tasca (4open, 3:13, 2020) and Wu et al. (Nature 579:265–269, 2020)). The sequences are taken in FASTA format, they will be considered as samples of stochastic processes. Based on this interpretation, stochastic tools derived from Partition Markov Models Garc ı́a and González-López (Entropy 19(4):160, 2017) are applied, specifically from the G-model, introduced in Garc ı́a et al. (4open 3:13, 2020), to obtain the representation of the behavior of each sequence. From these models, it is confirmed that the structure of the P.1 variant of the virus shows similar traits to the original one. Moreover, by means of a BIC-based metric and the G-model, it is possible to determine that the original sequence of SARS-CoV 2 (MN908947) and the set of sequences of SARS-CoV 2 - P.1 variant differ in certain transition probabilities, which allows identifying exactly the state that produces the discrepancy. We also represent this discrepancy graphically. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
In this article, we investigate the existence of genetic variants of Covid-19 circulating in Brazil in the 2020 outbreak. We apply the findings of [1] about the Partition Markov Model (PMM) with gap in genetic sequences of Covid-19, see also [2]. Using a metric on those models, we define the proximity between complete genomic sequences of the NCBI base. We see that two groups can be identified among the five available sequences that come from Brazil. To verify our claims, we implement a more complete comparison consisting of fourteen sequences, including sequences from Spain and Italy. Such comparison indicates the existence of two groups, where each group includes one from the previously identified Brazilian groups. Then, we found at least two variants of Covid-19 circulating in Brazil during the 2020 outbreak. © 2022 American Institute of Physics Inc.. All rights reserved.