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Archive for the ‘COVID-19: Pandemic Surgery Guidance’ Category

Covid-19 and its implications on pregnancy

Reporter and Curator: Mr. Srinjoy Chakraborty (Junior Research Felllow) and Dr. Sudipta Saha, Ph.D.

Coronavirus disease 2019 (COVID-19), which is caused by the novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has emerged as a serious global health issue with high transmission rates affecting millions of people worldwide. The SARS-CoV-2 is known to damage cells in the respiratory system, thus causing viral pneumonia. The novel SARS-CoV-2 is a close relative to the previously identified severe acute respiratory syndrome-coronavirus (SARS-CoV) and Middle East respiratory syndrome-coronavirus (MERS-CoV) which affected several people in 2002 and 2012, respectively. Ever since the outbreak of covid-19, several reports have poured in about the impact of Covid-19 on pregnancy. A few studies have highlighted the impact of the viral infection in pregnant women and how they are more susceptible to the infection because of the various physiological changes of the cardiopulmonary and immune systems during pregnancy. It is known that SARS-CoV and MERS-CoV diseases have influenced the fatality rate among pregnant women. However, there are limited studies on the impact of the novel corona virus on the course and outcome of pregnancy.

Figure: commonly observed clinical symptoms of COVID-19 in the general population: Fever and cough, along with dyspnoea, diarrhoea, and malaise are the most commonly observed symptoms in pregnant women, which is similar to that observed in the normal population.

The WHO and the Indian Council of Medical Research (ICMR) have proposed detailed guidelines for treating pregnant women; these guidelines must be strictly followed by the pregnant individual and their families. According to the guidelines issued by the ICMR, the risk of pregnant women contracting the virus to that of the general population. However, the immune system and the body’s response to a viral infection is altered during pregnancy. This may result in the manifestation of more severe symptoms. The ICMR guidelines also state that the reported cases of COVID-19 pneumonia in pregnancy are milder and with good recovery. However, by observing the trends of the other coronavirus infection (SARS, MERS), the risks to the mother appear to increase in particular during the last trimester of pregnancy. Cases of preterm birth in women with COVID-19 have been mentioned in a few case report, but it is unclear whether the preterm birth was always iatrogenic, or whether some were spontaneous. Pregnant women with heart disease are at highest risk of acquiring the infection, which is similar to that observed in the normal population. Most importantly, the ICMR guidelines highlights the impact of the coronavirus epidemic on the mental health of pregnant women. It mentions that the since the pandemic has begun, there has been an increase in the risk of perinatal anxiety and depression, as well as domestic violence. It is critically important that support for women and families is strengthened as far as possible; that women are asked about mental health at every contact.

With the available literature available on the impact of SARS and MERS on reproductive outcome, it has been mentioned that SARS infection did increase the risk of miscarriage, preterm birth and, intrauterine foetal growth restriction. However, the same has not been demonstrated in early reports from COVID-19 infection in pregnancy. According to a study that included 8200 participants conducted by the centre for disease control and prevention, pregnant women may be at a higher risk of acquiring severe infection and need for ICU admissions as compared to their non-pregnant counterparts. However, a detailed and thorough study involving a larger proportion of the population is needed today.

References:

https://www.news-medical.net/news/20210614/COVID-19-in-pregnancy-could-be-less-severe-than-previously-thought-A-Danish-case-study.aspx

https://obgyn.onlinelibrary.wiley.com/doi/10.1111/jog.14696

https://www.nature.com/articles/s41577-021-00525-y

https://www.tandfonline.com/doi/full/10.1080/14767058.2020.1759541

https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/special-populations/pregnancy-data-on-covid-19/what-cdc-is-doing.html

https://economictimes.indiatimes.com/news/india/why-is-covid-19-killing-so-many-pregnant-women-in-india/articleshow/82902194.cms?from=mdr

https://content.iospress.com/download/international-journal-of-risk-and-safety-in-medicine/jrs200060?id=international-journal-of-risk-and-safety-in-medicine%2Fjrs200060

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Emergence of a new SARS-CoV-2 variant from GR clade with a novel S glycoprotein mutation V1230L in West Bengal, India

Authors: Rakesh Sarkar, Ritubrita Saha, Pratik Mallick, Ranjana Sharma, Amandeep Kaur, Shanta Dutta, Mamta Chawla-Sarkar

Reporter and Original Article Co-Author: Amandeep Kaur, B.Sc. , M.Sc.

Abstract
Since its inception in late 2019, SARS-CoV-2 has evolved resulting in emergence of various variants in different countries. These variants have spread worldwide resulting in devastating second wave of COVID-19 pandemic in many countries including India since the beginning of 2021. To control this pandemic continuous mutational surveillance and genomic epidemiology of circulating strains is very important. In this study, we performed mutational analysis of the protein coding genes of SARS-CoV-2 strains (n=2000) collected during January 2021 to March 2021. Our data revealed the emergence of a new variant in West Bengal, India, which is characterized by the presence of 11 co-existing mutations including D614G, P681H and V1230L in S-glycoprotein. This new variant was identified in 70 out of 412 sequences submitted from West Bengal. Interestingly, among these 70 sequences, 16 sequences also harbored E484K in the S glycoprotein. Phylogenetic analysis revealed strains of this new variant emerged from GR clade (B.1.1) and formed a new cluster. We propose to name this variant as GRL or lineage B.1.1/S:V1230L due to the presence of V1230L in S glycoprotein along with GR clade specific mutations. Co-occurrence of P681H, previously observed in UK variant, and E484K, previously observed in South African variant and California variant, demonstrates the convergent evolution of SARS-CoV-2 mutation. V1230L, present within the transmembrane domain of S2 subunit of S glycoprotein, has not yet been reported from any country. Substitution of valine with more hydrophobic amino acid leucine at position 1230 of the transmembrane domain, having role in S protein binding to the viral envelope, could strengthen the interaction of S protein with the viral envelope and also increase the deposition of S protein to the viral envelope, and thus positively regulate virus infection. P618H and E484K mutation have already been demonstrated in favor of increased infectivity and immune invasion respectively. Therefore, the new variant having G614G, P618H, P1230L and E484K is expected to have better infectivity, transmissibility and immune invasion characteristics, which may pose additional threat along with B.1.617 in the ongoing COVID-19 pandemic in India.

Reference: Sarkar, R. et al. (2021) Emergence of a new SARS-CoV-2 variant from GR clade with a novel S glycoprotein mutation V1230L in West Bengal, India. medRxiv. https://doi.org/10.1101/2021.05.24.21257705https://www.medrxiv.org/content/10.1101/2021.05.24.21257705v1

Other related articles were published in this Open Access Online Scientific Journal, including the following:

Fighting Chaos with Care, community trust, engagement must be cornerstones of pandemic response

Reporter: Amandeep Kaur

https://pharmaceuticalintelligence.com/2021/04/13/fighting-chaos-with-care/

T cells recognize recent SARS-CoV-2 variants

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2021/03/30/t-cells-recognize-recent-sars-cov-2-variants/

Need for Global Response to SARS-CoV-2 Viral Variants

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2021/02/12/need-for-global-response-to-sars-cov-2-viral-variants/

Identification of Novel genes in human that fight COVID-19 infection

Reporter: Amandeep Kaur, B.Sc., M.Sc.

https://pharmaceuticalintelligence.com/2021/04/19/identification-of-novel-genes-in-human-that-fight-covid-19-infection/

Mechanism of Thrombosis with AstraZeneca and J & J Vaccines: Expert Opinion by Kate Chander Chiang & Ajay Gupta, MD

Reporter & Curator: Dr. Ajay Gupta, MD

https://pharmaceuticalintelligence.com/2021/04/14/mechanism-of-thrombosis-with-astrazeneca-and-j-j-vaccines-expert-opinion-by-kate-chander-chiang-ajay-gupta-md/

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Fighting Chaos with care, community trust, engagement must be cornerstones of pandemic response

Reporter: Amandeep Kaur, BSc, MSc (Exp. 6/2021)

According to the Global Health Security Index released by Johns Hopkins University in October 2019 in collaboration with Nuclear Threat Initiative (NTI) and The Economist Intelligence Unit (EIU), the United States was announced to be the best developed country in the world to tackle any pandemic or health emergency in future.

The table turned within in one year of outbreak of the novel coronavirus COVID-19. By the end of March 2021, the country with highest COVID-19 cases and deaths in the world was United States. According to the latest numbers provided by World Health Organization (WHO), there were more than 540,000 deaths and more than 30 million confirmed cases in the United States.

Joia Mukherjee, associate professor of global health and social medicine in the Blavatnik Institute at Harvard Medical School said,

“When we think about how to balance control of an epidemic over chaos, we have to double down on care and concern for the people and communities who are hardest hit”.

She also added that U.S. possess all the necessary building blocks required for a health system to work, but it lacks trust, leadership, engagement and care to assemble it into a working system.

Mukherjee mentioned about the issues with the Index that it undervalued the organized and integrated system which is necessary to help public meet their needs for clinical care. Another necessary element for real health safety which was underestimated was conveying clear message and social support to make effective and sustainable efforts for preventive public health measures.

Mukherjee is a chief medical officer at Partners In Health, an organization focused on strengthening community-based health care delivery. She is also a core member of HMS community members who play important role in constructing a more comprehensive response to the pandemic in all over the U.S. With years of experience, they are training global health care workers, analyzing the results and constructing an integrated health system to fight against the widespread health emergency caused by coronavirus all around the world.

Mukherjee encouraged to strengthen the consensus among the community to constrain this infectious disease epidemic. She suggested that validation of the following steps are crucial such as testing of the people with symptoms of infection with coronavirus, isolation of infected individuals by providing them with necessary resources and providing clinical treatment and care to those people who are in need. Mukherjee said, that community engagement and material support are not just idealistic goal rather these are essential components for functioning of health care system during an outburst of coronavirus.

Continued alertness such as social distancing and personal contact with infected individual is important because it is not possible to rapidly replace the old-school public health approaches with new advanced technologies like smart phone applications or biomedical improvements.

Public health specialists emphasized that the infection limitation is the only and most vital strategy for controlling the outbreak in near future, even if the population is getting vaccinated. It is crucial to slowdown the spread of disease for restricting the natural modification of more dangerous variants as that could potentially escape the immune protection mechanism developed by recently generated vaccines as well as natural immune defense systems.

Making Crucial connections

The treatment is more expensive and complicated in areas with less health facilities, said Paul Farmer, the Kolokotrones University Professor at Harvard and chair of the HMS Department of Global Health and Social Medicine. He called this situation as treatment nihilism. Due to shortage of resources, the maximum energy is focused in public health care and prevention efforts. U.S. has resources to cope up with the increasing demand of hospital space and is developing vaccines, but there is a form of containment nihilism- which means prevention and infection containment are unattainable- said by many experts.

Farmer said, integration of necessary elements such as clinical care, therapies, vaccines, preventive measures and social support into a single comprehensive plan is the best approach for a better response to COVID-19 disease. He understands the importance of community trust and integrated health care system for fighting against this pandemic, as being one of the founders of Partners In Health and have years of experience along with his colleagues from HMS and PIH in fighting epidemics of HIV, Ebola, cholera, tuberculosis, other infectious and non-infectious diseases.

PIH launched the Massachusetts Community Tracing Collaborative (CTC), which is an initiative of contact tracing statewide in partnership with several other state bodies, local boards of Health system and PIH. The CTC was setup in April 2020 in U.S. by Governor Charlie Baker, with leadership from HMS faculty, to build a unified response to COVID-19 and create a foundation for a long-term movement towards a more integrated community-based health care system.

The contact tracing involves reaching out to individuals who are COVID-19 positive, then further detect people who came in close contact with infected individuals and screen out people with coronavirus symptoms and encourage them to seek testing and take necessary precautions to break the chain of infection into the community.

In the initial phase of outbreak, the CTC group comprises of contact tracers and health care coordinators who spoke 23 different languages, including social workers, public health practitioners, nurses and staff members from local board health agencies with deep links to the communities they are helping. The CTC worked with 339 out of 351 state municipalities with local public health agencies relied completely on CTC whereas some cities and towns depend occasionally on CTC backup. According to a report, CTC members reached up to 80 percent of contact tracking in hard-hit and resource deprived communities such as New Bedford.

Putting COVID-19 in context

Based on generations of experience helping people surviving some of the deadliest epidemic and endemic outbreaks in places like Haiti, Mexico, Rwanda and Peru, the staff was alert that people with bad social and economic condition have less space to get quarantined and follow other public health safety measures and are most vulnerable people at high risk in the pandemic situation.

Infected individuals or individuals at risk of getting infected by SARS-CoV-2 had many questions regarding when to seek doctor’s help and where to get tested, reported by contact tracers. People were worried about being evicted from work for two weeks and some immigrants worried about basic supplies as they were away from their family and friends.

The CTC team received more than 7,000 requests for social support assistance in the initial three months. The staff members and contact tracers were actively connecting the resourceful individuals with the needy people and filling up the gap when there was shortage in their own resources.

Farmer said, “COVID is a misery-seeking missile that has targeted the most vulnerable.”

The reality that infected individuals concerned about lacking primary household items, food items and access to childcare, emphasizes the urgency of rudimentary social care and community support in fighting against the pandemic. Farmer said, to break the chain of infection and resume society it is mandatory to meet all the elementary needs of people.

“What kinds of help are people asking for?” Farmer said and added “it’s important to listen to what your patients are telling you.”

An outbreak of care

The launch of Massachusetts CTC with the support from PIH, started receiving requests from all around the country to assist initiating contact tracing procedures. In May, 2020 the organization announced the launch of a U.S. public health accompaniment to cope up with the asked need.

The unit has included team members in nearly 24 states and municipal health departments in the country and work in collaboration with local organizations. The technical support on things like choosing and implementing the tools and software for contact tracing was provided by PIH. To create awareness and provide new understanding more rapidly, a learning collaboration was established with more than 200 team members from more than 100 different organizations. The team worked to meet the needs of population at higher risk of infection by advocating them for a stronger and more reliable public health response.

The PIH public health team helped to train contact trackers in the Navajo nation and operate to strengthen the coordination between SARS-CoV-2 testing, efforts for precaution, clinical health care delivery and social support in vulnerable communities around the U.S.

“For us to reopen our schools, our churches, our workplaces,” Mukherjee said, “we have to know where the virus is spreading so that we don’t just continue on this path.”

SOURCE:

https://hms.harvard.edu/news/fighting-chaos-care?utm_source=Silverpop&utm_medium=email&utm_term=field_news_item_1&utm_content=HMNews04052021

Other related articles were published in this Open Access Online Scientific Journal, including the following:

T cells recognize recent SARS-CoV-2 variants

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2021/03/30/t-cells-recognize-recent-sars-cov-2-variants/

The WHO team is expected to soon publish a 300-page final report on its investigation, after scrapping plans for an interim report on the origins of SARS-CoV-2 — the new coronavirus responsible for killing 2.7 million people globally

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2021/03/27/the-who-team-is-expected-to-soon-publish-a-300-page-final-report-on-its-investigation-after-scrapping-plans-for-an-interim-report-on-the-origins-of-sars-cov-2-the-new-coronavirus-responsibl/

Need for Global Response to SARS-CoV-2 Viral Variants

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2021/02/12/need-for-global-response-to-sars-cov-2-viral-variants/

Mechanistic link between SARS-CoV-2 infection and increased risk of stroke using 3D printed models and human endothelial cells

Reporter: Adina Hazan, PhD

https://pharmaceuticalintelligence.com/2020/12/28/mechanistic-link-between-sars-cov-2-infection-and-increased-risk-of-stroke-using-3d-printed-models-and-human-endothelial-cells/

Artificial intelligence predicts the immunogenic landscape of SARS-CoV-2

Reporter: Irina Robu, PhD

https://pharmaceuticalintelligence.com/2021/02/04/artificial-intelligence-predicts-the-immunogenic-landscape-of-sars-cov-2/

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From AAAS Science News on COVID19: New CRISPR based diagnostic may shorten testing time to 5 minutes

Reporter: Stephen J. Williams, Ph.D.

 

 

 

 

 

 

 

 

 

A new CRISPR-based diagnostic could shorten wait times for coronavirus tests.

 

 

New test detects coronavirus in just 5 minutes

By Robert F. ServiceOct. 8, 2020 , 3:45 PM

Science’s COVID-19 reporting is supported by the Pulitzer Center and the Heising-Simons Foundation.

 

Researchers have used CRISPR gene-editing technology to come up with a test that detects the pandemic coronavirus in just 5 minutes. The diagnostic doesn’t require expensive lab equipment to run and could potentially be deployed at doctor’s offices, schools, and office buildings.

“It looks like they have a really rock-solid test,” says Max Wilson, a molecular biologist at the University of California (UC), Santa Barbara. “It’s really quite elegant.”

CRISPR diagnostics are just one way researchers are trying to speed coronavirus testing. The new test is the fastest CRISPR-based diagnostic yet. In May, for example, two teams reported creating CRISPR-based coronavirus tests that could detect the virus in about an hour, much faster than the 24 hours needed for conventional coronavirus diagnostic tests.CRISPR tests work by identifying a sequence of RNA—about 20 RNA bases long—that is unique to SARS-CoV-2. They do so by creating a “guide” RNA that is complementary to the target RNA sequence and, thus, will bind to it in solution. When the guide binds to its target, the CRISPR tool’s Cas13 “scissors” enzyme turns on and cuts apart any nearby single-stranded RNA. These cuts release a separately introduced fluorescent particle in the test solution. When the sample is then hit with a burst of laser light, the released fluorescent particles light up, signaling the presence of the virus. These initial CRISPR tests, however, required researchers to first amplify any potential viral RNA before running it through the diagnostic to increase their odds of spotting a signal. That added complexity, cost, and time, and put a strain on scarce chemical reagents. Now, researchers led by Jennifer Doudna, who won a share of this year’s Nobel Prize in Chemistry yesterday for her co-discovery of CRISPR, report creating a novel CRISPR diagnostic that doesn’t amplify coronavirus RNA. Instead, Doudna and her colleagues spent months testing hundreds of guide RNAs to find multiple guides that work in tandem to increase the sensitivity of the test.

In a new preprint, the researchers report that with a single guide RNA, they could detect as few as 100,000 viruses per microliter of solution. And if they add a second guide RNA, they can detect as few as 100 viruses per microliter.

That’s still not as good as the conventional coronavirus diagnostic setup, which uses expensive lab-based machines to track the virus down to one virus per microliter, says Melanie Ott, a virologist at UC San Francisco who helped lead the project with Doudna. However, she says, the new setup was able to accurately identify a batch of five positive clinical samples with perfect accuracy in just 5 minutes per test, whereas the standard test can take 1 day or more to return results.

The new test has another key advantage, Wilson says: quantifying a sample’s amount of virus. When standard coronavirus tests amplify the virus’ genetic material in order to detect it, this changes the amount of genetic material present—and thus wipes out any chance of precisely quantifying just how much virus is in the sample.

By contrast, Ott’s and Doudna’s team found that the strength of the fluorescent signal was proportional to the amount of virus in their sample. That revealed not just whether a sample was positive, but also how much virus a patient had. That information can help doctors tailor treatment decisions to each patient’s condition, Wilson says.

Doudna and Ott say they and their colleagues are now working to validate their test setup and are looking into how to commercialize it.

Posted in:

doi:10.1126/science.abf1752

Robert F. Service

Bob is a news reporter for Science in Portland, Oregon, covering chemistry, materials science, and energy stories.

 

Source: https://www.sciencemag.org/news/2020/10/new-test-detects-coronavirus-just-5-minutes

Other articles on CRISPR and COVID19 can be found on our Coronavirus Portal and the following articles:

The Nobel Prize in Chemistry 2020: Emmanuelle Charpentier & Jennifer A. Doudna
The University of California has a proud legacy of winning Nobel Prizes, 68 faculty and staff have been awarded 69 Nobel Prizes.
Toaster Sized Machine Detects COVID-19
Study with important implications when considering widespread serological testing, Ab protection against re-infection with SARS-CoV-2 and the durability of vaccine protection

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Online Event: Vaccine matters: Can we cure coronavirus? An AAAS Webinar on COVID19: 8/12/2020

Reporter: Stephen J. Williams. PhD

Source: Online Event

Top on the world’s want list right now is a coronavirus vaccine. There is plenty of speculation about how and when this might become a reality, but clear answers are scarce.Science/AAAS, the world’s leading scientific organization and publisher of the Science family of journals, brings together experts in the field of coronavirus vaccine research to answer the public’s most pressing questions: What vaccines are being developed? When are we likely to get them? Are they safe? And most importantly, will they work?

link: https://view6.workcast.net/AuditoriumAuthenticator.aspx?cpak=1836435787247718&pak=8073702641735492

Presenters

Presenter
Speaker: Sarah Gilbert, Ph.D.

University of Oxford
Oxford, UK
View Bio

Presenter
Speaker: Kizzmekia Corbett, Ph.D.

National Institute of Allergy and Infectious Diseases, NIH
Bethesda, MD
View Bio

Presenter
Speaker: Kathryn M. Edwards, M.D.

Vanderbilt Vaccine Research Program
Nashville, TN
View Bio

Presenter
Speaker: Jon Cohen

Science/AAAS
San Diego, CA
View Bio

Presenter
Moderator: Sean Sanders, Ph.D.

Science/AAAS
Washington, DC
View Moderator Bio

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via Key Immune System Genes Identified to Explain High COVID Deaths and Spread in Northern Italy Versus Fewer Cases and Deaths in the South

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From Cell Press:  New Insights on the D614G Strain of COVID: Will a New Mutated Strain Delay Vaccine Development?

Reporter: Stephen J. Williams, PhD

Two recent articles in Cell Press, both peer reviewed, discuss the emergence and potential dominance of a new mutated strain of COVID-19, in which the spike protein harbors a D614G mutation.

In the first article “Making Sense of Mutation: What D614G means for the COVID-19 pandemic Remains Unclear”[1] , authors Drs. Nathan Grubaugh, William Hanage, and Angela Rasmussen discuss the recent findings by Korber et al. 2020 [2] which describe the potential increases in infectivity and mortality of this new mutant compared to the parent strain of SARS-CoV2.  For completeness sake I will post this article as to not defer from their interpretations of this important paper by Korber and to offer some counter opinion to some articles which have surfaced this morning in the news.

Making sense of mutation: what D614G means for the COVID-19 pandemic remains unclear

 

Nathan D. Grubaugh1 *, William P. Hanage2 *, Angela L. Rasmussen3 * 1Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA 2Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA 3Center for Infection and Immunity, Columbia Mailman School of Public Health, New York, NY 10032, USA Correspondence: grubaughlab@gmail.com

 

Abstract: Korber et al. (2020) found that a SARS-CoV-2 variant in the spike protein, D614G, rapidly became dominant around the world. While clinical and in vitro data suggest that D614G changes the virus phenotype, the impact of the mutation on transmission, disease, and vaccine and therapeutic development are largely unknown.

Introduction: Following the emergence of SARS-CoV-2 in China in late 2019, and the rapid expansion of the COVID19 pandemic in 2020, questions about viral evolution have come tumbling after. Did SARS-CoV-2 evolve to become better adapted to humans? More infectious or transmissible? More deadly? Virus mutations can rise in frequency due to natural selection, random genetic drift, or features of recent epidemiology. As these forces can work in tandem, it’s often hard to differentiate when a virus mutation becomes common through fitness or by chance. It is even harder to determine if a single mutation will change the outcome of an infection, or a pandemic. The new study by Korber et al. (2020) sits at the heart of this debate. They present compelling data that an amino acid change in the virus’ spike protein, D614G, emerged early during the pandemic, and viruses containing G614 are now dominant in many places around the world. The crucial questions are whether this is the result of natural selection, and what it means for the COVID-19 pandemic. For viruses like SARS-CoV-2 transmission really is everything – if they don’t get into another host their lineage ends. Korber et al. (2020) hypothesized that the rapid spread of G614 was because it is more infectious than D614. In support of their hypothesis, the authors provided evidence that clinical samples from G614 infections have a higher levels of viral RNA, and produced higher titers in pseudoviruses from in vitro experiments; results that now seem to be corroborated by others [e.g. (Hu et al., 2020; Wagner et al., 2020)]. Still, these data do not prove that G614 is more infectious or transmissible than viruses containing D614. And because of that, many questions remain on the potential impacts, if any, that D614G has on the COVID-19 pandemic.

The authors note that this new G614 variant has become the predominant form over the whole world however in China the predominant form is still the D614 form.  As they state

“over the period that G614 became the global majority variant, the number of introductions from China where D614 was still dominant were declining, while those from Europe climbed. This alone might explain the apparent success of G614.”

Grubaugh et al. feel there is not enough evidence that infection with this new variant will lead to higher mortality.  Both Korber et al. and the Seattle study (Wagner et al) did not find that the higher viral load of this variant led to a difference in hospitalizations so apparently each variant might be equally as morbid.

In addition, Grubaugh et al. believe this variant would not have much affect on vaccine development as, even though the mutation lies within the spike protein, D614G is not in the receptor binding domain of the spike protein.  Korber suggest that there may be changes in glycosylation however these experiments will need to be performed.  In addition, antibodies from either D614 or G614 variant infected patients could cross neutralize.

 

Conclusions: While there has already been much breathless commentary on what this mutation means for the COVID19 pandemic, the global expansion of G614 whether through natural selection or chance means that this variant now is the pandemic. As a result its properties matter. It is clear from the in vitro and clinical data that G614 has a distinct phenotype, but whether this is the result of bonafide adaptation to human ACE2, whether it increases transmissibility, or will have a notable effect, is not clear. The work by Korber et al. (2020) provides an early base for more extensive epidemiological, in vivo experimental, and diverse clinical investigations to fill in the many critical gaps in how D614G impacts the pandemic.

The link to the Korber Cell paper is here: https://www.cell.com/cell/fulltext/S0092-8674(20)30820-5

Tracking changes in SARS-CoV-2 Spike: evidence that D614G increases infectivity of the COVID-19 virus

DOI: https://doi.org/10.1016/j.cell.2020.06.043

Keypoints

  • The consistent increase of G614 at regional levels may indicate a fitness advantage

 

  • G614 is associated with lower RT PCR Ct’s, suggestive of higher viral loads in patients

 

  • The G614 variant grows to higher titers as pseudotyped virions

Summary

A SARS-CoV-2 variant carrying the Spike protein amino acid change D614G has become the most prevalent form in the global pandemic. Dynamic tracking of variant frequencies revealed a recurrent pattern of G614 increase at multiple geographic levels: national, regional and municipal. The shift occurred even in local epidemics where the original D614 form was well established prior to the introduction of the G614 variant. The consistency of this pattern was highly statistically significant, suggesting that the G614 variant may have a fitness advantage. We found that the G614 variant grows to higher titer as pseudotyped virions. In infected individuals G614 is associated with lower RT-PCR cycle thresholds, suggestive of higher upper respiratory tract viral loads, although not with increased disease severity. These findings illuminate changes important for a mechanistic understanding of the virus, and support continuing surveillance of Spike mutations to aid in the development of immunological interventions.

 

References

  1. Grubaugh, N.D., Hanage, W.P., Rasmussen, A.L., Making sense of mutation: what D614G means for the COVID-19 pandemic remains unclear, Cell (2020), doi: https:// doi.org/10.1016/j.cell.2020.06.040.
  2. Korber, B., Fischer, W.M., Gnanakaran, S., Yoon, H., Theiler, J., Abfalterer, W., Hengartner, N., Giorgi, E.E., Bhattacharya, T., Foley, B., et al. (2020). Tracking changes in SARS-CoV-2 Spike: evidence that D614G increases infectivity of the COVID-19 virus. Cell 182.
  3. Endo, A., Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group, Abbott, S., Kucharski, A.J., and Funk, S. (2020). Estimating the overdispersion in COVID-19 transmission using outbreak sizes outside China. Wellcome Open Res 5, 67.
  4. Hu, J., He, C.-L., Gao, Q.-Z., Zhang, G.-J., Cao, X.-X., Long, Q.-X., Deng, H.-J., Huang, L.-Y., Chen, J., Wang, K., et al. (2020). The D614G mutation of SARS-CoV-2 spike protein enhances viral infectivity and decreases neutralization sensitivity to individual convalescent sera. bioRxiv 2020.06.20.161323.
  5. Wagner, C., Roychoudhury, P., Hadfield, J., Hodcroft, E.B., Lee, J., Moncla, L.H., Müller, N.F., Behrens, C., Huang, M.-L., Mathias, P., et al. (2020). Comparing viral load and clinical outcomes in Washington State across D614G mutation in spike protein of SARS-CoV-2. Https://github.com/blab/ncov-D614G.

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National Cancer Institute Director Neil Sharpless says mortality from delays in cancer screenings due to COVID19 pandemic could result in tens of thousands of extra deaths in next decade

Reporter: Stephen J Williams, PhD

UPDATED: 10/11/2021

Source: https://cancerletter.com/articles/20200619_1/

NCI Director’s Report

Sharpless: COVID-19 expected to increase mortality by at least 10,000 deaths from breast and colorectal cancers over 10 years

By Matthew Bin Han Ong

This story is part of The Cancer Letter’s ongoing coverage of COVID-19’s impact on oncology. A full list of our coverage, as well as the latest meeting cancellations, is available here.

The COVID-19 pandemic will likely cause at least 10,000 excess deaths from breast cancer and colorectal cancer over the next 10 years in the United States.

Scenarios run by NCI and affiliated modeling groups predict that delays in screening for and diagnosis of breast and colorectal cancers will lead to a 1% increase in deaths through 2030. This translates into 10,000 additional deaths, on top of the expected one million deaths resulting from these two cancers.

“For both these cancer types, we believe the pandemic will influence cancer deaths for at least a decade,” NCI Director Ned Sharpless said in a virtual joint meeting of the Board of Scientific Advisors and the National Cancer Advisory Board June 15. “I find this worrisome as cancer mortality is common. Even a 1% increase every decade is a lot of cancer suffering.

“And this analysis, frankly, is pretty conservative. We do not consider cancers other than those of breast and colon, but there is every reason to believe the pandemic will affect other types of cancer, too. We did not account for the additional non-lethal morbidity from upstaging, but this could also be significant and burdensome.”

An editorial by Sharpless on this subject appears in the journal Science.

The early analyses, conducted by the institute’s Cancer Intervention and Surveillance Modeling Network, focused on breast and colorectal cancers, because these are common, with relatively high screening rates.

CISNET modelers created four scenarios to assess long-term increases in cancer mortality rates for these two diseases:

  1. The pandemic has no effect on cancer mortality
  1. Delayed screening—with 75% reduction in mammography and, colorectal screening and adenoma surveillance for six months
  1. Delayed diagnosis—with one-third of people delaying follow-up after a positive screening or diagnostic mammogram, positive FIT or clinical symptoms for six months during a six-month period
  1. Combination of scenarios two and three

Treatment scenarios after diagnosis were not included in the model. These would be: delays in treatment, cancellation of treatment, or modified treatment.

“What we did is show the impact of the number of excess deaths per year for 10 years for each year starting in 2020 for scenario four versus scenario one,” Eric “Rocky” Feuer, chief of the NCI’s Statistical Research and Applications Branch in the Surveillance Research Program, said to The Cancer Letter.

Feuer is the overall project scientist for CISNET, a collaborative group of investigators who use simulation modeling to guide public health research and priorities.

“The results for breast cancer were somewhat larger than for colorectal,” Feuer said. “And that’s because breast cancer has a longer preclinical natural history relative to colorectal cancer.”

Modelers in oncology are creating a global modeling consortium, COVID-19 and Cancer Taskforce, to “support decision-making in cancer control both during and after the crisis.” The consortium is supported by the Union for International Cancer Control, The International Agency for Research on Cancer, The International Cancer Screening Network, the Canadian Partnership Against Cancer, and Cancer Council NSW, Australia.

A spike in cancer mortality rates threatens to reverse or slow down—at least in the medium term—the steady trend of reduction of cancer deaths. On Jan. 8, the American Cancer Society published its annual estimates of new cancer cases and deaths, declaring that the latest data—from 2016 to 2017—show the “largest ever single-year drop in overall cancer mortality of 2.2%.” Experts say that innovation in lung cancer treatment and the success of smoking cessation programs are driving the sharp decrease (The Cancer LetterFeb. 7, 2020).

The pandemic is expected to have broader impact, including increases in mortality rates for other cancer types. Also, variations in severity of COVID-19 in different regions in the U.S. will influence mortality metrics.

“There’s some other cancers that might have delays in screening—for example cervical, prostate, and lung cancer, although lung cancer screening rates are still quite low and prostate cancer screening should only be conducted on those who determine that the benefits outweigh the harms,” Feuer said. “So, those are the major screening cancers, but impacts of delays in treatment, canceling treatment or alternative treatments—could impact a larger range of cancer sites.

“This model assumes a moderate disruption which resolves after six months, and doesn’t consider non-lethal morbidities associated with the delay. One thing I think probably is occurring is regional variation in these impacts,” Feuer said. “If you’re living in New York City where things were ground zero for some of the worst impact early on, probably delays were larger than other areas of the country. But now, as we’re seeing upticks in other areas of the country, there may be in impact in these areas as well”

How can health care providers mitigate some of these harms? For example, for people who delayed screening and diagnosis, are providers able to perform triage, so that those at highest risk are prioritized?

“From a strictly cancer control point of view, let’s get those people who delayed screening, or followup to a positive test, or treatment back on schedule as soon as possible,” Feuer said. “But it’s not a simple calculus, because in every situation, we have to weigh the harms and benefits. As we come out of the pandemic, it tips more and more to, ‘Let’s get back to business with respect to cancer control.’

“Telemedicine doesn’t completely substitute for seeing patients in person, but at least people could get the advice they need, and then are triaged through their health care providers to indicate if they really should prioritize coming in. That helps the individual and the health care provider  weigh the harms and benefits, and try to strategize about what’s best for any individual.”

If the pandemic continues to disrupt routine care, cancer-related mortality rates would rise beyond the predictions in this model.

“I think this analysis begins to help us understand the costs with regard to cancer outcomes of the pandemic,” Sharpless said. “Let’s all agree we will do everything in our power to minimize these adverse effects, to protect our patients from cancer suffering.”

UPDATED: 10/11/2021

Patients with Cancer Appear More Vulnerable to SARS-CoV-2: A Multicenter Study during the COVID-19 Outbreak

Source:

Mengyuan DaiDianbo LiuMiao LiuFuxiang ZhouGuiling LiZhen ChenZhian ZhangHua YouMeng WuQichao ZhengYong XiongHuihua XiongChun WangChangchun ChenFei XiongYan ZhangYaqin PengSiping GeBo ZhenTingting YuLing WangHua WangYu LiuYeshan ChenJunhua MeiXiaojia GaoZhuyan LiLijuan GanCan HeZhen LiYuying ShiYuwen QiJing YangDaniel G. TenenLi ChaiLorelei A. MucciMauricio Santillana and Hongbing Cai. Patients with Cancer Appear More Vulnerable to SARS-CoV-2: A Multicenter Study during the COVID-19 Outbreak

Abstract

The novel COVID-19 outbreak has affected more than 200 countries and territories as of March 2020. Given that patients with cancer are generally more vulnerable to infections, systematic analysis of diverse cohorts of patients with cancer affected by COVID-19 is needed. We performed a multicenter study including 105 patients with cancer and 536 age-matched noncancer patients confirmed with COVID-19. Our results showed COVID-19 patients with cancer had higher risks in all severe outcomes. Patients with hematologic cancer, lung cancer, or with metastatic cancer (stage IV) had the highest frequency of severe events. Patients with nonmetastatic cancer experienced similar frequencies of severe conditions to those observed in patients without cancer. Patients who received surgery had higher risks of having severe events, whereas patients who underwent only radiotherapy did not demonstrate significant differences in severe events when compared with patients without cancer. These findings indicate that patients with cancer appear more vulnerable to SARS-CoV-2 outbreak.

Significance: Because this is the first large cohort study on this topic, our report will provide much-needed information that will benefit patients with cancer globally. As such, we believe it is extremely important that our study be disseminated widely to alert clinicians and patients.

Introduction

A new acute respiratory syndrome coronavirus, named SARS-CoV-2 by the World Health Organization (WHO), has rapidly spread around the world since its first reported case in late December 2019 from Wuhan, China (1). As of March 2020, this virus has affected more than 200 countries and territories, infecting more than 800,000 individuals and causing more than 40,000 deaths (2).

With more than 18 million new cases per year globally, cancer affects a significant portion of the population. Individuals affected by cancer are more susceptible to infections due to coexisting chronic diseases, overall poor health status, and systemic immunosuppressive states caused by both cancer and anticancer treatments (3). As a consequence, patients with cancer who are infected by the SARS-CoV-2 coronavirus may experience more difficult outcomes than other populations. Until now, there is still no systematic evaluation of the effects that the SARS-CoV-2 coronavirus has of patients with cancer in a representative population. A recent study reported a higher risk of severe events in patients with cancer when compared with patients without cancer (4); however, the small sample size of SARS-CoV-2 patients with cancer used in the study limited how representative it was of the whole population and made it difficult to conduct more insightful analyses, such as comparing clinical characteristics of patients with different types of cancer, as well as anticancer treatments (5, 6).

Using patient information collected from 14 hospitals in Hubei Province, China, the epicenter of the 2019–2020 COVID-19 outbreak, we describe the clinical characteristics and outcomes [death, intensive care unit (ICU) admission, development of severe/critical symptoms, and utilization of invasive mechanical ventilation] of patients affected by the SARS-CoV-2 coronavirus for 105 hospitalized patients with cancer and 536 patients without cancer. We document our findings for different cancer types and stages, as well as different types of cancer treatments. We believe the information and insights provided in this study will help improve our understanding of the effects of SARS-CoV-2 in patients with cancer.

Results

Patients Characteristics

In total, 105 COVID-19 patients with cancer were enrolled in our study for the time period January 1, 2020, to February 24, 2020, from 14 hospitals in Wuhan, China. COVID-19 patients without cancer matched by the same hospital, hospitalization time, and age were randomly selected as our control group. Our patient population included 339 females and 302 males. Patients with cancer [median = 64.00, interquartile range (IQR) = 14.00], when compared with those without cancer (median = 63.50, IQR = 14.00) had similar age distributions (by design), experienced more in-hospital infections [20 (19.04%) of 105 patients vs. 8 (1.49%) of 536 patients;P < 0.01], and had more smoking history [36 (34.28%) of 105 patients vs. 46 (8.58%) of 536 patients; P < 0.01], but had no significant differences in sex, other baseline symptoms, and other comorbidities (Table 1). With respect to signs and symptoms upon admission, COVID-19 patients with cancer were similar to those without cancer except for a higher prevalence of chest distress [15 (14.29%) of 105 patients vs. 36 (6.16%) of 536 patients; P = 0.02].

Table 1.

Characteristics of COVID-19 patients with and without cancer

Clinical Outcomes

Compared with COVID-19 patients without cancer, patients with cancer had higher observed death rates [OR, 2.34; 95% confidence interval (CI), (1.15–4.77); P = 0.03], higher rates of ICU admission [OR, 2.84; 95% CI (1.59–5.08); P < 0.01], higher rates of having at least one severe or critical symptom [OR, 2.79; 95% CI, (1.74–4.41); P < 0.01], and higher chances of needing invasive mechanical ventilation (Fig. 1A). We also conducted survival analysis on occurrence of any severe condition which included death, ICU admission, having severe symptoms, and utilization of invasive mechanical ventilation (see cumulative incidence curves in Fig. 1B). In general, patients with cancer deteriorated more rapidly than those without cancer. These observations are consistent with logistic regression results (Supplementary Fig. S1), after adjusting for age, sex, smoking, and comorbidities including diabetes, hypertension, and chronic obstructive pulmonary disease (COPD). According to our multivariate logistic regression results, patients with cancer still had an excess OR of 2.17 (P = 0.06) for death (Supplementary Fig. S1A), 1.99 (P < 0.01) for experiencing any severe symptoms (Supplementary Fig. S1B), 3.13 (P < 0.01) for ICU admission (Supplementary Fig. S1C), and 2.71 (P = 0.04) for utilization of invasive mechanical ventilation (Supplementary Fig. S1D; Supplementary Table S1). The consistency of observed ORs between the multivariate regression model and unadjusted calculation reassures the association between cancer and severe events even in the presence of other factors such as age differences.

Figure 1.

Severe conditions in patients with and without cancer, and patients with different types, stages, and treatments of cancer. Severe conditions include death, ICU admission, having severe/critical symptoms, and usage of invasive mechanical ventilation. Incidence and survival analysis of severe conditions among COVID-19 patients with cancer and without cancer (A and B), among patients with different types of cancer (C and D), among patients with metastatic and nonmetastatic cancers (E and F), among patients with lung cancer, other cancers than lung with lung metastasis, and other cancers than lung without lung metastasis (G and H), and patients receiving different types of cancer treatments (I and J). P values indicate differences between cancer subgroups versus patients without cancer. For ACEGI, *, P < 0.05; **, P < 0.01. OR, 95% CI, and P values between different subgroups are listed in Supplementary Table S2. For BDFHJ, HR, 95% CI, and P values are listed in Supplementary Table S3.

Cancer Types

Information regarding potential risks of severe conditions in SARS-CoV-2 associated with each type of cancer was calculated. We compared different conditions among cancer types (Table 2). Lung cancer was the most frequent cancer type [22 (20.95%) of 105 patients], followed by gastrointestinal cancer [13 (12.38%) of 105 patients], breast cancer [11 (10.48%) of 105 patients], thyroid cancer [11 (10.48%) of 105 patients], and hematologic cancer [9 (8.57%) of 105 patients]. As shown in Fig. 1C and D and Supplementary Table S2, patients with hematologic cancer including leukemia, lymphoma, and myeloma have a relatively high death rate [3 (33.33%) of 9 patients], high ICU admission rate [4 (44.44%) of 9 patients], high risks of severe/critical symptoms [6 (66.67%) of 9 patients], and high chance of utilization of invasive mechanical ventilation [2 (22.22%) of 9 patients]. Patients with lung cancer had the second-highest risk levels, with death rate [4 (18.18%) of 22 patients], ICU admission rate [6 (27.27%) of 22 patients], risks of severe/critical symptoms [11 (50.00%) of 22 patients], and the chance of utilization of invasive mechanical ventilation [4 (18.18%) of 22 patients; Table 2].

Table 2.

Severe events in 105 patients with cancer for each type of cancer

Cancer Stage

We found that patients with metastatic cancer (stage IV) had even higher risks of death [OR, 5.58; 95% CI (1.71–18.23); P = 0.01], ICU admission [OR, 6.59; 95% CI (2.32–18.72); P < 0.01], having severe conditions [OR, 5.97; 95% CI (2.24–15.91); P < 0.01], and use of invasive mechanical ventilation [OR, 55.42; 95% CI (13.21–232.47); P < 0.01]. In contrast, patients with nonmetastatic cancer did not demonstrate statistically significant differences compared with patients without cancer, with all P > 0.05 (Fig. 1E and F; Supplementary Tables S2 and S3). In addition, when compared with patients without cancer, patients with lung cancer or other cancers with lung metastasis also showed higher risks of death, ICU admission rates, higher critical symptoms, and use of invasive mechanical ventilation, with all P values below 0.01, but other cancers without lung metastasis had no statistically significant differences (all P values > 0.05; Fig. 1G and H; Supplementary Table S3) when compared with patients without cancer.

Cancer Treatments

Among the 105 COVID-19 patients with cancer in our study, 13 (12.26%) had radiotherapy, 17 (14.15%) received chemotherapy, 8 (7.62%) received surgery, 4 (3.81%) had targeted therapy, and 6 (5.71%) had immunotherapy within 40 days before the onset of COVID-19 symptoms. All of the targeted therapeutic drugs were EGFR–tyrosine kinase inhibitors for treatment of lung cancer, and all of the immunotherapy drugs were PD-1 inhibitors for the treatment of lung cancer. A patient with cancer may have more than one type of therapy. Our observation suggested that patients who received immunotherapy tended to have high rates of death [2 (33.33%) of 6 patients] and high chances of developing critical symptoms [4 (66.67%) of 6 patients]. Patients who received surgery demonstrated higher rates of death [2 (25.00%) of 8 patients], higher chances of ICU admission [3 (37.50%) of 8 patients], higher chances of having severe or critical symptoms [5 (62.50%) of 8 patients], and higher use of invasive ventilation [2 (25.00%) of 8 patients] than other treatments excluding immunotherapy. However, patients with cancer who received radiotherapy did not show statistically significant differences in having any severe events when compared with patients without cancer, with all P values > 0.10 (Fig. 1I and J). Clinical details on the cancer diagnoses and cancer treatments are summarized in Supplementary Table S4.

Timeline of Severe Events

To evaluate the time-dependent evolution of the disease, we conducted the timeline of different events for COVID-19 patients with cancer (Fig. 2A) and COVID-19 patients without cancer (Fig. 2B) with death and other severe events marked in the figure. COVID-19 patients with cancer had a mean length of stay of 27.01 days (SD 9.52) and patients without cancer had a mean length of stay of 17.75 days (SD 8.64); the difference is significant (Wilcoxon test, P < 0.01). To better clarify the contributing factors that might influence outcomes, we also included logistic regression of COVID-19 patients with cancer adjusted by immunosuppression levels in Supplementary Table S5. However, no significant association between immunosuppression and severe outcomes was observed from the analysis (with all P > 0.05).

Figure 2.

Timeline of events for COVID-19 patients. A, Timeline of events in COVID-19 patients with cancer. B, Timeline of events in COVID-19 patients without cancer. For visualization purposes, patients without timeline information are excluded and only 105 COVID-19 patients without cancer are shown.

Discussion

The findings in this study suggest that patients with cancer infected with SARS-CoV-2 tend to have more severe outcomes when compared with patients without cancer. Patients with hematologic cancer, lung cancer, and cancers in metastatic stages demonstrated higher rates of severe events compared with patients without cancer. In addition, patients who underwent cancer surgery showed higher death rates and higher chances of having critical symptoms.

The SARS-CoV-2 virus has spread rapidly globally; thus, many countries have not been ready to handle the large volume of people affected by this outbreak due to a lack of knowledge about how this coronavirus affects the general population. To date, reports on the general population infected with SARS-CoV-2 suggest elderly males have a higher incidence and death rate (7, 8). Limited information is known about the outcome of patients with cancer who contract this highly communicable disease. Cancer is among the top causes of death. Asia, Europe, and North America have the highest incidence of cancer in the world (9), and at the moment of the writing of this study the SARS-CoV-2 virus is mainly spreading in these three areas (referred from https://www.cdc.gov/media/releases/2020/s0226-Covid-19-spread.htmlhttps://www.nytimes.com/2020/02/27/world/coronavirusnews.html). Although COVID-19 patients with cancer may share some epidemiologic features with the general population with this disease, they may also have additional clinical characteristics. Therefore, we conducted this study on patients with cancer with coexisting COVID-19 disease to evaluate the potential effect of COVID-19 on patients with cancer.

On the basis of our analysis, COVID-19 patients with cancer tend to have more severe outcomes when compared with the noncancer population. Although COVID-19 is reported to have a relatively low death rate of 2% to 3% in the general population (10), patients with cancer and COVID-19 not only have a nearly 3-fold increase in the death rate than that of COVID-19 patients without cancer, but also tend to have much higher severity of their illness. Altogether, these findings suggest that patients with cancer are a much more vulnerable population in the current COVID-19 outbreak. Our findings are consistent with those presented in a previous study based on 18 patients with cancer (4). Because of the limited number of patients with cancer in the previous study, the authors concluded that among patients with cancer, age is the only risk factor for the severity of the illness. On the basis of our data on 105 patients with cancer, we have discovered additional risk factors, including cancer types, cancer stage, and cancer treatments, which may contribute to the severity of the disease among patients with cancer.

Our data demonstrate that the severity of SARS-CoV-2 infection in patients is significantly affected by the types of tumors. From our analysis, patients with hematologic cancer have the highest severity and death rates among all patients with cancer, and lung cancer follows second. Patients with hematologic cancer in our study include patients with leukemia, myeloma, and lymphoma, who have a more compromised immune system than patients with solid tumors (11). These patients all had a rapidly deteriorating clinical course once infected with COVID-19. Because malignant or dysfunctional plasma cells, lymphocytes, or white blood cells in general in hematologic malignancies have decreased immunologic function (12–14), this could be the main reason why patients with hematologic cancer have very high severity and death rates. All patients with hematologic cancer are prone to the complications of serious infection (12–14), which can exacerbate the condition which could have worsened in patients with COVID-19. In our study, 55.56% of patients with hematologic cancer had severe immunosuppression, which may be the main reason for deteriorated outcomes. Although the small sample size limits representativity of the observation, we believe our finding can serve as an informative starting point for further investigation when a larger cohort from a wide range of healthcare providers becomes available. Among solid tumors, lung cancer is the highest risk category disease in patients with SARS-CoV-2 infection (Fig. 1C). Decreased lung function and severe infection in patients with lung cancer could contribute to the worse outcome in this subpopulation (15, 16).

In our analysis, we classified the SARS-CoV-2 infection–related high risk factors based on death, severe or critical illness, ICU admission, and the utilization of invasive mechanical ventilation. Using these parameters, we detected a multi-fold increase in risk in the cancer population, in contrast to the noncancer population. If there were primary or metastatic tumors in the lungs, patients were more prone to a deteriorated course in a short time. Intriguingly, when patients with cancer had only early-stage disease without metastasis, we did not observe any difference between the cancer and noncancer population in terms of COVID-19–related death rate or severity (Fig. 1E). The stage of cancer diagnosis seemed to play a significant role in the severity and death rate of COVID-19.

Patients with cancer received a wide range of treatments, and we also found that different types of treatments had different influences on severity and death when these patients contracted COVID-19. Recently, immunotherapy has assumed a very important role in treating tumors, which aids in treatment of cancer by blocking the immune escape of cancer cells. But in our study, in contrast to patients with cancer with other treatments, patients with immunotherapy had the highest death rate and the highest severity of illness, a very puzzling finding. According to pathologic studies on the patients with COVID-19, there were desquamation of pneumocytes and hyaline membrane formation, implying that these patients had acute respiratory distress syndrome (ARDS; ref. 17). ARDS induced by cytokine storm is reported to be the main reason for death of SARS-CoV-2–infected patients (18). It is possible that in this setting, immunotherapy induces the release of a large amount of cytokines, which can be toxic to normal cells, including lung epithelial cells (19–21), and therefore lead to a more severe illness. However, in this study the number of patients with immunotherapy was too small; further research with a large case population needs to be conducted in the future.

In addition, COVID-19 patients with cancer who are under active treatment or not under active treatment do not show differences in their outcomes, and there is a significant difference between COVID-19 patients with cancer but not with active treatment and patients without cancer (Supplementary Table S2). These results indicate that COVID-19 patients with both active treatment and just cancer history have a higher risk of developing severe events than noncancer COVID-19 patients. The possible reasons could be due to some known cancer-related complications, for example, anemia, hypoproteinaemia, or dyspnea in early phase of COVID-19 (22). We considered that cancer had a lifetime effect on patients and that cancer survivors always need routine follow-up after primary resection. Therefore, in clinical COVID-19 patient management, equivalent attention needs to be paid to those with cancer whether they are under active therapeutics or not during the outbreak of COVID-19.

This study has several limitations. Although the cohort of COVID-19 patients with cancer is one of the largest in Hubei province, China, the epicenter of the initial outbreak, a larger cohort from the whole country or even from multiple countries will be more representative. Large-scale national and international research collaboration will be necessary to achieve this. At the initial stage of the outbreak, data collection and research activities were not a priority of the hospitals. Therefore, it was not possible to record and collect some data that are potentially informative for our analysis in a timely manner. In addition, due to the urgency of clinical treatment, medical data used in this study were largely disconnected from the patients’ historical electronic medical records, which are mostly stored with a different healthcare provider than the medical center providing COVID-19 care. This left us with limited information about each patient.

Our study is the midsize cohort study on this topic and will provide much-needed information on risk factors of this population. We hope that our findings will help countries better protect patients with cancer affected by the ongoing COVID-19 pandemic.

Methods

Study Design and Patients

We conducted a multicenter study focusing on the clinical characteristics of confirmed cases of COVID-19 patients with cancer in 14 hospitals in Hubei province, China; all of the 14 hospitals served as government-designated hospitals for patients diagnosed with COVID-19. SARS-CoV-2–infected patients without cancer matched by the same hospital and hospitalization time were randomly selected as our control group. In addition, as age is one of the major predictors of severity of respiratory diseases like COVID-19 (4), we excluded from our analysis 117 younger COVID-19 patients without cancer so that median ages of patients with cancer (median = 64.0, IRQ = 14.00) and patients without cancers (median = 63.5, IQR = 14.00) would be comparable.

End Points and Assessments

There were four primary outcomes analyzed in this study: death, admission into the ICU, development of severe or critical symptoms, and utilization of invasive mechanical ventilation. The clinical definition of severe/critical symptoms follows the 5th edition of the 2019Novel Coronavirus Disease (COVID-19) Diagnostic Criteria published by the National Health Commission in China, including septic shock, ARDS, acute kidney injury, disseminated intravascular coagulation, and rhabdomyolysis.

Case Fatality Rate of Cancer Patients with COVID-19 in a New York Hospital System

Source:

Vikas MehtaSanjay GoelRafi KabarritiDaniel ColeMendel GoldfingerAna Acuna-VillaordunaKith PradhanRaja ThotaStan ReissmanJoseph A. SparanoBenjamin A. GartrellRichard V. SmithNitin OhriMadhur GargAndrew D. RacineShalom KalnickiRoman Perez-SolerBalazs Halmos and Amit Verma. Case Fatality Rate of Cancer Patients with COVID-19 in a New York Hospital System

Abstract

Patients with cancer are presumed to be at increased risk from COVID-19 infection–related fatality due to underlying malignancy, treatment-related immunosuppression, or increased comorbidities. A total of 218 COVID-19–positive patients from March 18, 2020, to April 8, 2020, with a malignant diagnosis were identified. A total of 61 (28%) patients with cancer died from COVID-19 with a case fatality rate (CFR) of 37% (20/54) for hematologic malignancies and 25% (41/164) for solid malignancies. Six of 11 (55%) patients with lung cancer died from COVID-19 disease. Increased mortality was significantly associated with older age, multiple comorbidities, need for ICU support, and elevated levels of D-dimer, lactate dehydrogenase, and lactate in multivariate analysis. Age-adjusted CFRs in patients with cancer compared with noncancer patients at our institution and New York City reported a significant increase in case fatality for patients with cancer. These data suggest the need for proactive strategies to reduce likelihood of infection and improve early identification in this vulnerable patient population.

Significance: COVID-19 in patients with cancer is associated with a significantly increased risk of case fatality, suggesting the need for proactive strategies to reduce likelihood of infection and improve early identification in this vulnerable patient population.

Introduction

The novel coronavirus COVID-19, or severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has spread rapidly throughout the world since its emergence in December 2019 (1). The virus has infected approximately 2.9 million people in more than 200 countries with more than 200,000 deaths at the time of writing (2). Most recently, the United States has become the epicenter of this pandemic, reporting an estimated 956,000 cases of COVID-19 infection, with the largest concentration in New York City (NYC) and its surrounding areas (approximately >203,000 cases or 35% of all U.S. infections; ref. 3).

Early data suggests that 14% to 19% of infected patients will develop significant sequelae with acute respiratory distress syndrome, septic shock, and/or multiorgan failure (1, 4, 5), and approximately 1% to 4% will die from the disease (2). Recent meta-analyses have demonstrated an almost 6-fold increase in the odds of mortality for patients with chronic obstructive pulmonary disease (COPD) and a 2.5-fold increase for those with diabetes, possibly due to the underlying pulmonary and immune dysfunction (6, 7). Given these findings, patients with cancer would ostensibly be at a higher risk of developing and succumbing to COVID-19 due to immunosuppression, increased coexisting medical conditions, and, in cases of lung malignancy, underlying pulmonary compromise. Patients with hematologic cancer, or those who are receiving active chemotherapy or immunotherapy, may be particularly susceptible because of increased immunosuppression and/or dysfunction.

According the NCI, there were approximately 15.5 million cancer survivors and an estimated 1,762,450 new cases of cancer diagnosed in the United States in 2019 (8). Early case series from China and Italy have suggested that patients with malignancy are more susceptible to severe infection and mortality from COVID-19 (9–12), a phenomenon that has been noted in other pandemics (13). Many of these descriptive studies have included small patient cohorts and have lacked cancer site–specific mortality data or information regarding active cancer treatment. As New York has emerged as the current epicenter of the pandemic, we sought to investigate the risk posed by COVID-19 to our cancer population with more granular data regarding cancer type and active treatment, and identify factors that placed patients with cancer at highest risk of fatality from COVID-19.

Results

Outcomes of 218 Cancer Patients with COVID-19 Show High Overall Mortality with Tumor-Specific Patterns

A total of 218 patients with cancer and COVID-19 were treated in Montefiore Health System (New York, NY) from March 18, 2020, to April 8, 2020. These included 164 (75%) patients with solid tumors and 54 (25%) with hematologic malignancies. This cohort included 127 (58%) males and 91 (42%) females. The cohort was predominantly composed of adult patients (215/218, 98.6%) with a median age of 69 years (range 10–92 years).

Sixty-one (28%) patients expired as a result of COVID-19disease at the time of analysis (Table 1). The mortality was 25% among all patients with solid tumors and was seen to occur at higher rates in patients with lung cancers (55%), gastrointestinal (GI) cancers [colorectal (38%), pancreatic (67%), upper GI (38%)], and gynecologic malignancies (38%). Genitourinary (15%) and breast (14%) cancers were associated with relatively lower mortality with COVID-19 infection.

Table 1.

Outcomes in patients with cancer and COVID-19

Hematologic malignancies were associated with higher rate of mortality with COVID-19 (37%). Myeloid malignancies [myelodysplastic syndromes (MDS)/acute myeloid leukemia (AML)/myeloproliferative neoplasm (MPN)] showed a trend for higher mortality compared with lymphoid neoplasms [non-Hodgkin lymphoma (NHL)/chronic lymphoid leukemia (CLL)/acute lymphoblastic leukemia (ALL)/multiple myeloma (MM)/Hodgkin lymphoma; Table 1]. Rates of ICU admission and ventilator use were slightly higher for hematologic malignancies than solid tumors (26% vs. 19% and 11% vs. 10%, respectively), but this did not achieve statistical significance.

Disease Characteristics of Cancer Patients with COVID-19 Demonstrate the Effect of Age, Comorbidities, and Laboratory Biomarkers on Mortality

Analysis of patient characteristics with mortality did not show any gender bias (Table 2). Older age was significantly associated with increased mortality, with median age of deceased cohort at 76 years when compared with 66 years for the nondeceased group (P = 0.0006; Cochran-Armitage test). No significant associations between race and mortality were seen.

Table 2.

Disease characteristics of patients with cancer with COVID-19 and association with mortality

COVID-19 disease severity, as evident from patients who needed ICU care and ventilator support, was significantly associated with increased mortality. Interestingly, active disease (<1 year) and advanced metastatic disease showed a trend for increased mortality, but the association did not achieve statistical significance (P = 0.09 and 0.06, respectively). Active chemotherapy and radiotherapy treatment were not associated with increased case fatality. Very few patients in this cohort were on immunotherapy, and this did not show any associations with mortality.

Analysis of comorbidities demonstrated increased risk of dying from COVID-19 in patients with cancer with concomitant heart disease [hypertension (HTN), coronary artery disease (CAD), and congestive heart failure (CHF)] and chronic lung disease (Table 2). Diabetes and chronic kidney disease were not associated with increased mortality in univariate analysis (Table 2).

We also analyzed laboratory values obtained prior to diagnosis of COVID-19 and during the time of nadir after COVID-19 positivity in our cancer cohort. Relative anemia pre–COVID-19 was associated with increased mortality, whereas pre-COVID platelet and lymphocyte counts were not (Table 3).Post–COVID-19 infection, lower hemoglobin levels, higher total white blood cell (WBC) counts, and higher absolute neutrophil counts were associated with increased mortality (Table 3). Analysis of other serologic biomarkers demonstrated that elevated D-dimer, lactate, and lactate dehydrogenase (LDH) in patients were significantly correlated with dying (Table 3).

Table 3.

Laboratory values of cancer patients with COVID-19 and association with mortality

Next, we conducted multivariate analyses and used variables that showed a significant association with mortality in univariate analysis (P < 0.05 in univariate was seen with age, ICU admission, hypertension, chronic lung disease, CAD, CHF, baseline hemoglobin, nadir hemoglobin, WBC counts, D-dimer, lactate, and LDH). Gender was forced in the model and we used a composite score of comorbidities from the sum of indicators for diabetes mellitus (DM), HTN, chronic lung disease, chronic kidney disease, CAD, and CHF capped at a maximum of 3. In the multivariate model (Supplementary Table S1), we observed that older age [age < 65; OR, 0.23; 95% confidence interval (CI), 0.07–0.6], higher composite comorbidity score (OR, 1.52; 95% CI, 1.02–2.33), ICU admission (OR, 4.83; 95% CI, 1.46–17.15), and elevated inflammatory markers (D-dimer, lactate, and LDH) were significantly associated with mortality after multivariate comparison in patients with cancer and COVID-19.

Interaction with the Healthcare Environment was a Prominent Source of Exposure for Patients with Cancer

A detailed analysis of deceased patients (N = 61; Supplementary Table S2) demonstrated that many were either nursing-home or shelter (n = 22) residents, and/or admitted as an inpatient or presented to the emergency room within the 30 days prior to their COVID-19 positive test (21/61). Altogether, 37/61 (61%) of the deceased cohort were exposed to the healthcare environment at the outset of the COVID-19 epidemic. Few of the patients in the cohort were on active oncologic therapy. The vast majority had a poor Eastern Cooperative Oncology Group performance status (ECOG PS; 51/61 with an ECOG PS of 2 or higher) and carried multiple comorbidities.

Patients with Cancer Demonstrate a Markedly Increased COVID-19 Mortality Rate Compared with Noncancer and All NYC COVID-19 Patients

An age- and sex-matched cohort of 1,090 patients at a 5:1 ratio of noncancer to cancer COVID-19 patients from the same time period and from the same hospital system was also obtained after propensity matching and used as control to estimate the increased risk posed to our cancer population (Table 4). We observed case fatality rates (CFR) were elevated in all age cohorts in patients with cancer and achieved statistical significance in the age groups 45–64 and in patients older than 75 years of age.

Table 4.

Comparison of cancer and COVID-19 mortality with all NYC cases (official NYC numbers up to 5 p.m., April 12, 2020) and a control group from the same healthcare facility

To also compare our CFRs with a larger dataset from the greater NYC region, we obtained official case numbers from New York State (current up to April 12, 2020; ref. 3). In all cohorts, the percentage of deceased patients was found to rise sharply with increasing age (Table 4). Strikingly, CFRs in cancer patients with COVID-19 were significantly, many-fold higher in all age groups when compared with all NYC cases (Table 4).

Discussion

To our knowledge, this is the first large report of COVID-19 CFRs among patients with cancer in the United States. The overall case fatality among COVID-19–infected patients with cancer in an academic center located within the current epicenter of the global pandemic exceeded 25%. In addition, striking tumor-specific discrepancies were seen, with marked increased susceptibility for those with hematologic malignancies and lung cancer. CFRs were 2 to 3 times the age-specific percentages seen in our noncancer population and the greater NYC area for all COVID-19 patients.

Our results seem to mirror the typical prognosis of the various cancer types. Among the most common malignancies within the U.S. population (lung, breast, prostate, and colorectal), there was 55% mortality among patients with lung cancer, 14% for breast cancer, 20% for prostate cancer, and 38% for colorectal cancer. This pattern reflects the overall known lethality of these cancers. The percent annual mortality (ratio of annual deaths/new diagnosis) is 59.3% for lung cancer, 15.2% for breast cancer, 17.4% for prostate cancer, and 36% for colorectal cancer (8). This suggests that COVID-19 infection amplifies the risk of death regardless of the cancer type.

Patients with hematologic malignancies demonstrate a higher mortality than those with solid tumors. These patients tend to be treated with more myelosuppressive therapy, and are often severely immunocompromised because of underlying disease. There is accumulating evidence that one major mechanism of injury may be a cytokine-storm syndrome secondary to hyperinflammation, which results in pulmonary damage. Patients with hematologic malignancy may potentially be more susceptible to cytokine-mediated inflammation due to perturbations in myeloid and lymphocyte cell compartments (14).

Many of the predictive risk factors for mortality in our cancer cohort were similar to published data among all COVID-19 patients. A recent meta-analysis highlighted the association of chronic diseases including hypertension (OR, 2.29), diabetes (OR, 2.47), COPD (OR, 5.97), cardiovascular disease (OR, 2.93), and cerebrovascular disease (OR, 3.89) with a risk for developing severe COVID-19 infection among all patients (15). In our cancer patient dataset, a large proportion of patients had at least one of these concurrent risk factors. In a univariate model, we observed significant associations of death from COVID-19 infection in patients with hypertension, chronic lung disease, coronary heart disease, and congestive heart failure. Serologic predictors in our dataset predictive for mortality included anemia at time of infection, and elevated LDH, D-dimer, and lactic acid, which correlate with available data from all COVID-19 patients.

Rapidly accumulating reports suggest that age and race may play a role in the severity of COVID-19 infection. In our cancer cohort, the median age of the patients succumbing to COVID-19 was 76 years, which was 10 years older than patients who have remained alive. The CDC has reported a disproportionate number of African Americans are affected by COVID-19 in the United States, accounting for 33% of all hospitalized patients while constituting only 13% of the U.S. population (15). However, the racial breakdown of our patients was proportional to the Bronx population as a whole, and race was not a significant predictor of mortality in our univariate or multivariate models. Our data might argue that the increased mortality noted in the larger NYC populations might also likely be driven by socioeconomic and health disparities in addition to underlying biological factors. Overall mortality with COVID-19 has been higher in the Bronx, which is a socioeconomically disadvantaged community with a mean per capita income of $19,721 (16, 17). Our patients with cancer were predominantly from the Bronx and potentially had increased mortality in part due to socioeconomic factors and comorbidities. Even after accounting for the increased mortality seen in COVID-19 in the Bronx, the many-fold magnitude increase in death rates within our cancer cohort can potentially be attributed to the vulnerability of oncology patients. This was evident in the comparison with a control group from the same hospital system that demonstrated a significant association of cancer with mortality in patients between 45 and 64 years of age and older than 75 years of age.

Interaction with the healthcare environment prior to widespread knowledge of the epidemic within NYC was a prominent source of exposure for our patients with cancer. Many of those who succumbed to COVID-19 infection were older and frail with significant impairment of pulmonary and/or immunologic function. These findings could be utilized to risk-stratify patients with cancer during this pandemic, or in future viral airborne outbreaks, and inform mitigation practices for high-risk individuals. These strategies could include early and aggressive social distancing, resource allocation toward more outpatient-based care and telemedicine, testing of asymptomatic high-risk patients, and institution of strict infection-control measures. Indeed, such strategies were implemented early in the pandemic at our center, possibly explaining the relatively low number of infected patients on active therapy.

There were several limitations to our study. Data regarding do not resuscitate or intubate orders were not included in the analysis and could have significantly affected the decision-making and mortality surrounding these patients. Although an attempt was made to control for those receiving active cancer treatment or with additional comorbidities, we could not fully account for the patients’ preexisting health conditions prior to COVID-19 infection. Differential treatment paradigms for COVID-19 infection and sequelae were not controlled for in our analysis. Because of the limited follow-up, the full clinical course of these patients may not be included. Future comparative studies to noncancer patients will be needed to fully ascertain the risk posed to oncology patients. Finally, though our data does include those who were tested and discharged within our health system, we cannot fully account for those who were tested in nonaffiliated outpatient settings, which may potentially bias our study to more severe cases. We also acknowledge that the mortality rate is highly dependent on the breadth of testing, and therefore understand that more widespread detection of viral infection would likely alter the results.

Our data suggest significant risk posed to patients with cancer infected with COVID-19, with an observed significant increase in mortality. The highest susceptibility appears to be in hematologic or lung malignancies, suggesting that proactive strategies to reduce likelihood of infection and improve early identification of COVID-19 positivity in the cancer patient population are clearly warranted. Overall, we hope and expect that our data from the current epicenter of the COVID-19 epidemic will help inform other healthcare systems, patients with cancer, and the public about the particular vulnerability of patients with cancer to this disease.

For more Articles on COVID-19 please see our Coronavirus Portal at

https://pharmaceuticalintelligence.com/coronavirus-portal/

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COVID-19: Pandemic Surgery Guidance published by a Global Consortium initiated effort by Björn L.D.M. Brücher, MD, PhD, Prof. Of Surgery, Carl-Thiem-Klinikum, Cottbus, Germany

Reporter: Aviva Lev-Ari, PhD, RN

This video interview with the corresponding author, Björn L.D.M. Brücher, considers the changing landscape of surgery as a result of COVID-19, and explores the process of creating this guidance in an innovative and collaborative way. A ‘Key Summary’ has also been produced in an easy to understand Q&A format.

Watch the full video: https://bit.ly/2AkEgLm
Read the ‘Key Summary’: https://bit.ly/2MNtK20

 

Issue
4open
Volume 3, 2020
Article Number 1
Number of page(s) 19
DOI https://doi.org/10.1051/fopen/2020002
Published online 10 April 2020

© B.L.M.D. Brücher et al., Published by EDP Sciences, 2020

Licence Creative Commons
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

SOURCE

https://www.4open-sciences.org/articles/fopen/full_html/2020/01/fopen200002s/fopen200002s.html

 

Other related articles published on this Open Access Online Scientific Journal include the following:

EIGHT pages on the Coronavirus Portal:

https://pharmaceuticalintelligence.com/coronavirus-portal/

Coronavirus Pandemic: RESEARCH CATEGORIES in JOURNAL ONTOLOGY

  • Population genetics
  •  Population Health Management
    •  U.S. Employment-to-Population Ratio

OPEN TO GUEST AUTHORS

on Seven Selected Topics & Lead Curator for Contact:

BREAKING NEWS CORNER

June 2020

 

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A Series of Recently Published Papers Report the Development of SARS-CoV2 Neutralizing Antibodies and Passive Immunity toward COVID19

Curator: Stephen J. Williams, Ph.D.

 

Passive Immunity and Treatment of Infectious Diseases

The ability of one person to pass on immunity to another person (passive immunity) is one of the chief methods we develop immunity to many antigens.  For instance, maternal antibodies are passed to the offspring in the neonatal setting as well as in a mother’s milk during breast feeding.  In the clinical setting this is achieved by transferring antibodies from one patient who has been exposed to an antigen (like a virus) to the another individual.   However, the process of purifying the most efficacious antibody as well as its mass production is limiting due to its complexity and cost and can be prohibitively long delay during a pandemic outbreak, when therapies are few and needed immediately.  Regardless, the benefits of developing neutralizing antibodies to confer passive immunity versus development of a vaccine are evident, as the former takes considerable less time than development of a safe and effective vaccine.  For a good review on the development and use of neutralizing antibodies and the use of passive immunity to treat infectious diseases please read the following review:

Margaret A. Keller1,* and E. Richard Stiehm. Passive Immunity in Prevention and Treatment of Infectious Diseases. Clin Microbiol Rev. 2000 Oct; 13(4): 602–614. doi: 10.1128/cmr.13.4.602-614.2000

ABSTRACT

Antibodies have been used for over a century in the prevention and treatment of infectious disease. They are used most commonly for the prevention of measles, hepatitis A, hepatitis B, tetanus, varicella, rabies, and vaccinia. Although their use in the treatment of bacterial infection has largely been supplanted by antibiotics, antibodies remain a critical component of the treatment of diptheria, tetanus, and botulism. High-dose intravenous immunoglobulin can be used to treat certain viral infections in immunocompromised patients (e.g., cytomegalovirus, parvovirus B19, and enterovirus infections). Antibodies may also be of value in toxic shock syndrome, Ebola virus, and refractory staphylococcal infections. Palivizumab, the first monoclonal antibody licensed (in 1998) for an infectious disease, can prevent respiratory syncytial virus infection in high-risk infants. The development and use of additional monoclonal antibodies to key epitopes of microbial pathogens may further define protective humoral responses and lead to new approaches for the prevention and treatment of infectious diseases.

TABLE 1

Summary of the efficacy of antibody in the prevention and treatment of infectious diseases

Infection
Bacterial infections
 Respiratory infections (streptococcus, Streptococcus pneumoniaeNeisseria meningitisHaemophilus influenzae)
 Diphtheria
 Pertussis
 Tetanus
 Other clostridial infections
  C. botulinum
  C. difficile
 Staphylococcal infections
  Toxic shock syndrome
  Antibiotic resistance
  S. epidermidis in newborns
 Invasive streptococcal disease (toxic shock syndrome)
 High-risk newborns
 Shock, intensive care, and trauma
Pseudomonas infection
  Cystic Fibrosis
  Burns
Viral diseases
 Hepatitis A
 Hepatitis B
 Hepatitis C
 HIV infection
 RSV infection
 Herpesvirus infections
  CMV
  EBV
  HSV
  VZV
 Parvovirus infection
 Enterovirus infection
  In newborns
 Ebola
 Rabies
 Measles
 Rubella
 Mumps
 Tick-borne encephalitis
 Vaccinia

Go to:

A Great Explanation of Active versus Passive Immunity by Dr. John Campbell, one of the pioneers in the field of immunology:Antibodies have been used for over a century in the prevention and treatment of infectious disease. They are used most commonly for the prevention of measles, hepatitis A, hepatitis B, tetanus, varicella, rabies, and vaccinia. Although their use in the treatment of bacterial infection has largely been supplanted by antibiotics, antibodies remain a critical component of the treatment of diptheria, tetanus, and botulism. High-dose intravenous immunoglobulin can be used to treat certain viral infections in immunocompromised patients (e.g., cytomegalovirus, parvovirus B19, and enterovirus infections). Antibodies may also be of value in toxic shock syndrome, Ebola virus, and refractory staphylococcal infections. Palivizumab, the first monoclonal antibody licensed (in 1998) for an infectious disease, can prevent respiratory syncytial virus infection in high-risk infants. The development and use of additional monoclonal antibodies to key epitopes of microbial pathogens may further define protective humoral responses and lead to new approaches for the prevention and treatment of infectious diseases.

 

However, developing successful neutralizing antibodies can still be difficult but with the latest monoclonal antibody technology, as highlighted by the following papers, this process has made much more efficient.  In addition, it is not feasable to isolate antibodies from the plasma of covalescent patients in a scale that is needed for a worldwide outbreak.

A good explanation of the need can be found is Dr. Irina Robu’s post Race to develop antibody drugs for COVID-19 where:

When fighting off foreign invaders, our bodies make antibodies precisely produced for the task. The reason vaccines offer such long-lasting protection is they train the immune system to identify a pathogen, so immune cells remember and are ready to attack the virus when it appears. Monoclonal antibodies for coronavirus would take the place of the ones our bodies might produce to fight the disease. The manufactured antibodies would be infused into the body to either tamp down an existing infection, or to protect someone who has been exposed to the virus. However, these drugs are synthetic versions of the convalescent plasma treatments that rely on antibodies from people who have recovered from infection. But the engineered versions are easier to scale because they’re manufactured in rats, rather than from plasma donors.

The following papers represent the latest published work on development of therapeutic and prophylactic neutralizing antibodies to the coronavirus SARS-CoV2

1.  Cross-neutralization of SARS-CoV-2 by a human monoclonal SARS-CoV antibody.

Pinto, D., Park, Y., Beltramello, M. et al. Cross-neutralization of SARS-CoV-2 by a human monoclonal SARS-CoV antibody. Nature (2020).                                                                            https://doi.org/10.1038/s41586-020-2349-y

Abstract

SARS-CoV-2 is a newly emerged coronavirus responsible for the current COVID-19 pandemic that has resulted in more than 3.7 million infections and 260,000 deaths as of 6 May 20201,2. Vaccine and therapeutic discovery efforts are paramount to curb the pandemic spread of this zoonotic virus. The SARS-CoV-2 spike (S) glycoprotein promotes entry into host cells and is the main target of neutralizing antibodies. Here we describe multiple monoclonal antibodies targeting SARS-CoV-2 S identified from memory B cells of an individual who was infected with SARS-CoV in 2003. One antibody, named S309, potently neutralizes SARS-CoV-2 and SARS-CoV pseudoviruses as well as authentic SARS-CoV-2 by engaging the S receptor-binding domain. Using cryo-electron microscopy and binding assays, we show that S309 recognizes a glycan-containing epitope that is conserved within the sarbecovirus subgenus, without competing with receptor attachment. Antibody cocktails including S309 along with other antibodies identified here further enhanced SARS-CoV-2 neutralization and may limit the emergence of neutralization-escape mutants. These results pave the way for using S309- and S309-containing antibody cocktails for prophylaxis in individuals at high risk of exposure or as a post-exposure therapy to limit or treat severe disease.

 

2.  Potent neutralizing antibodies against SARS-CoV-2 identified by high-throughput single-cell sequencing of convalescent patients’ B cells

Yunlong Cao et al.  Potent neutralizing antibodies against SARS-CoV-2 identified by high-throughput single-cell sequencing of convalescent patients’ B cells. Cell (2020).

https://doi.org/10.1016/j.cell.2020.05.025

Summary

The COVID-19 pandemic urgently needs therapeutic and prophylactic interventions. Here we report the rapid identification of SARS-CoV-2 neutralizing antibodies by high-throughput single-cell RNA and VDJ sequencing of antigen-enriched B cells from 60 convalescent patients. From 8,558 antigen-binding IgG1+ clonotypes, 14 potent neutralizing antibodies were identified with the most potent one, BD-368-2, exhibiting an IC50 of 1.2 ng/mL and 15 ng/mL against pseudotyped and authentic SARS-CoV-2, respectively. BD-368-2 also displayed strong therapeutic and prophylactic efficacy in SARS-CoV-2-infected hACE2-transgenic mice. Additionally, the 3.8Å Cryo-EM structure of a neutralizing antibody in complex with the spike-ectodomain trimer revealed the antibody’s epitope overlaps with the ACE2 binding site. Moreover, we demonstrated that SARS-CoV-2 neutralizing antibodies could be directly selected based on similarities of their predicted CDR3H structures to those of SARS-CoV neutralizing antibodies. Altogether, we showed that human neutralizing antibodies could be efficiently discovered by high-throughput single B-cell sequencing in response to pandemic infectious diseases.

3. A human monoclonal antibody blocking SARS-CoV-2 infection

Wang, C., Li, W., Drabek, D. et al. A human monoclonal antibody blocking SARS-CoV-2 infection. Nat Commun 11, 2251 (2020). https://doi.org/10.1038/s41467-020-16256-y

Abstract

The emergence of the novel human coronavirus SARS-CoV-2 in Wuhan, China has caused a worldwide epidemic of respiratory disease (COVID-19). Vaccines and targeted therapeutics for treatment of this disease are currently lacking. Here we report a human monoclonal antibody that neutralizes SARS-CoV-2 (and SARS-CoV) in cell culture. This cross-neutralizing antibody targets a communal epitope on these viruses and may offer potential for prevention and treatment of COVID-19.

Extra References on Development of Neutralizing antibodies for COVID19 {Sars-CoV2} published this year (2020)  [1-4]

  1. Fan P, Chi X, Liu G, Zhang G, Chen Z, Liu Y, Fang T, Li J, Banadyga L, He S et al: Potent neutralizing monoclonal antibodies against Ebola virus isolated from vaccinated donors. mAbs 2020, 12(1):1742457.
  2. Dussupt V, Sankhala RS, Gromowski GD, Donofrio G, De La Barrera RA, Larocca RA, Zaky W, Mendez-Rivera L, Choe M, Davidson E et al: Potent Zika and dengue cross-neutralizing antibodies induced by Zika vaccination in a dengue-experienced donor. Nature medicine 2020, 26(2):228-235.
  3. Young CL, Lyons AC, Hsu WW, Vanlandingham DL, Park SL, Bilyeu AN, Ayers VB, Hettenbach SM, Zelenka AM, Cool KR et al: Protection of swine by potent neutralizing anti-Japanese encephalitis virus monoclonal antibodies derived from vaccination. Antiviral research 2020, 174:104675.
  4. Sautto GA, Kirchenbaum GA, Abreu RB, Ecker JW, Pierce SR, Kleanthous H, Ross TM: A Computationally Optimized Broadly Reactive Antigen Subtype-Specific Influenza Vaccine Strategy Elicits Unique Potent Broadly Neutralizing Antibodies against Hemagglutinin. J Immunol 2020, 204(2):375-385.

 

For More Articles on COVID-19 Please see Our Coronavirus Portal on this Open Access Scientific Journal at:

https://pharmaceuticalintelligence.com/coronavirus-portal/

and the following Articles on  Immunity at

Race to develop antibody drugs for COVID-19
Bispecific and Trispecific Engagers: NK-T Cells and Cancer Therapy
Issues Need to be Resolved With ImmunoModulatory Therapies: NK cells, mAbs, and adoptive T cells
Antibody-bound Viral Antigens

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