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Clinical & Translational Immunology logoLink to Clinical & Translational Immunology
. 2024 Feb 14;13(2):e1491. doi: 10.1002/cti2.1491

Fighting flu: novel CD8+ T‐cell targets are required for future influenza vaccines

Samuel Liwei Leong 1, Stephanie Gras 1,2, Emma J Grant 1,2,
PMCID: PMC10867544  PMID: 38362528

Abstract

Seasonal influenza viruses continue to cause severe medical and financial complications annually. Although there are many licenced influenza vaccines, there are billions of cases of influenza infection every year, resulting in the death of over half a million individuals. Furthermore, these figures can rise in the event of a pandemic, as seen throughout history, like the 1918 Spanish influenza pandemic (50 million deaths) and the 1968 Hong Kong influenza pandemic (~4 million deaths). In this review, we have summarised many of the currently licenced influenza vaccines available across the world and current vaccines in clinical trials. We then briefly discuss the important role of CD8+ T cells during influenza infection and why future influenza vaccines should consider targeting CD8+ T cells. Finally, we assess the current landscape of known immunogenic CD8+ T‐cell epitopes and highlight the knowledge gaps required to be filled for the design of rational future influenza vaccines that incorporate CD8+ T cells.

Keywords: CD8+ T cells, epitopes, HLA‐I, influenza, vaccines


Seasonal influenza viruses continue to cause severe medical and financial complications annually despite vaccines being available. As such, there is a need for updated vaccines that provide long‐lasting protection to global populations. In this review, we summarise licenced influenza vaccines and those currently in clinical trials, highlighting their key advantages and limitations. Furthermore, we discuss activating CD8+ T cells for future influenza vaccinations, highlighting the current gaps in knowledge for rational vaccine design.

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Influenza viruses

In the 21st century, just over 100 years since the outbreak of the pandemic A/H1N1 influenza virus which caused the devastating 1918–1919 Spanish Flu pandemic, influenza remains an ongoing threat to humans. 1 Epidemiological studies from the World Health Organization (WHO) estimate that roughly 650 000 deaths are attributed to seasonal influenza infections annually. 2 Influenza viruses are single‐stranded RNA viruses with segmented genomes which encode for a range of structural and non‐structural proteins. There are several influenza virus subtypes, three of which are known to infect humans, the influenza A virus (IAV), the influenza B virus (IBV) and the influenza C virus (ICV). 3

Generally, influenza symptoms may vary from mild to severe, requiring hospitalisation. 4 Mild cases of influenza are typically present with cough, feverish symptoms, diaphoresis (cold sweats) and headaches. 4 Conversely, severe cases of influenza can lead to acute respiratory distress syndrome (ARDS). 5 ARDS is described as a hyperactive immune reaction resulting in severe damage to the lungs, without neutralisation of the virus. 5 This leads to pulmonary oedema, organ failure and eventually death, if left untreated. 5

Of the influenza viruses that circulate and infect humans, IAV is the most characterised and is the only influenza virus that has caused a pandemic so far. The IAV contains eight gene segments known as polymerase basic proteins 1 and 2 (PB1 and PB2), non‐structural protein (NS), nucleoprotein (NP), the matrix protein (M), polymerase acidic protein (PA), haemagglutinin (HA) and neuraminidase (NA). 6 , 7 These genes encode for 18 known proteins, of which 10 are functionally critical (PB1, PB2, PA, NP, HA, M1, M2, NA, NS1 and NS2). 7 The nomenclature of IAVs is characterised by the expression of surface glycoproteins, haemagglutinin and neuraminidase. 8 , 9 , 10 For example, the A/H3N2 IAV strain expresses the HA subtype 3 and NA subtype 2. 8 Currently, 18 different HA and 11 NA subtypes have been described. Uniquely, IAV can also infect several animals (e.g. birds, pigs and horses), and phylogenetic evidence suggests that all mammal‐derived IAVs are derived initially from avian sources. 11 The ability to infect several animal species creates a viral reservoir that can subsequently infect humans, making it fundamentally impossible to eradicate. 8 , 12

Influenza B viruses primarily contribute to seasonal infections only and are the leading cause of influenza virus infection every few years. 13 Influenza B viruses are differentiated by their lineages, namely the Yamagata and Victoria lineages. 14 IBVs correspondingly spread between humans and are typically not known to infect any animal reservoirs. 15 The IBVs are also known to share the same genes and proteins as IAVs. 16

The ICV typically affects younger children and is thought to be highly underreported as it typically induces a mild disease which can be overlooked as various other respiratory illnesses. 17 According to some reports, it has been stated that many young children will be infected with the ICV at some point during their childhood. 17 What distinguishes the ICV from the other family of influenza viruses is that they have one less gene segment (totalling seven gene segments). 17 Furthermore, ICV also encodes for the haemagglutinin esterase fusion glycoprotein which is important for viral entry. 17

Typically, there are four influenza virus strains (2 IAV and 2 IBV) that continually and simultaneously circulate between hemispheres within humans that contribute to seasonal infections. 2 These are the A/H1N1 and A/H3N2 strains of influenza A, and the Yamagata and Victoria lineages of influenza B. 18 Moreover these are the targets of the majority of the licenced vaccines administered around the world. 18 The ICV is not a priority of the WHO and thus is not a target of influenza vaccines. 2 , 19

One important characteristic of all influenza viruses is that they lack the molecular mechanisms to proofread genomic RNA, which can lead to point mutations. 20 These point mutations result in antigenic drift, which can decrease protection from pre‐existing immunity and is typically responsible for seasonal epidemics. This is the catalyst for annual influenza vaccine updates. 20 This occurs particularly with IAV, as the IAV can circulate in many animal reservoirs, under unique circumstances the IAV can undergo antigenic shift. 21 , 22 Antigenic shift generally occurs when two unique IAV strains co‐infect a host, and through genetic reassortment a new strain emerges. 22 , 23 If the new strain is significantly different to previously circulating strains, there is a potential to evade pre‐existing immunity. 23 If the reassorted virus is efficient in replication and transmission, it may also result in a pandemic. 23 Thus, the total expected mortalities can significantly exceed seasonal influenza epidemics. 23 , 24 In other instances, the effect of antigenic shift may contribute to seasonal epidemics, as well as pandemic‐like strains of previous years. 25 , 26

So far, vaccines are the most used therapeutic worldwide to prevent severe influenza disease, particularly in vulnerable individuals such as children (< 5 years of age), the elderly (> 65 years of age), pregnant women, the immunosuppressed and individuals with co‐morbidities. 27 While antivirals are used is select circumstances, influenza infections continue to cause significant morbidity and mortality annually. 27 , 28 , 29 According to the Centers for Disease Control and Prevention (CDC), the 2019–2020 season had a high‐end estimate of more than 30 million symptomatic cases (~9% of the US population as of 2023) reported in the United States. 30 , 31 It has been estimated that roughly 50 million individuals will be infected with the influenza virus (~14.7% of the US population) and more than 650 000 hospitalisations will occur in the 2022–2023 season. 32

Apart from morbidity and mortality, influenza virus infections also cause a significant financial liability. 33 In a recent systematic review, Courville et al. categorised the cost of influenza burden into two groups: direct and indirect costs. Direct cost encompasses the medical intervention of outpatient and inpatient expenses, while indirect costs are dependent on approved sick leave and workplace inefficiency caused by sicknesses. 33 Unsurprisingly, this study observed that the annual indirect cost of influenza amounted to roughly US$8 billion in the United States alone. 33 Thus, new and broadly protective influenza vaccines are a topic of great interest and research.

Current influenza vaccines

When considering the development of novel influenza virus vaccines of the future, it is important to understand the advantages and disadvantages of current vaccines for the generation of novel therapeutics. Currently there are 19 influenza virus vaccines (not including variations of same vaccine) licenced for use by the Food and Drug Administration (FDA) (USA), the Therapeutics Goods Administration (TGA) (Australia) and the European Medicines Agency (Europe) (Table 1). The available vaccines include subunit vaccines, live attenuated vaccines and surface protein inactivated vaccines (Table 1). Influenza vaccines are typically designed to simultaneously protect against two antigenic strains of IAV and one (trivalent vaccines) or two (quadrivalent vaccines) lineages from IBV. 34 , 35 Most of these vaccines generally induce a strong neutralising antibody (nAb) response against the surface HA glycoprotein. 35 , 36 The advantage of inducing a strong nAb response via vaccination is to neutralise the virus before its entry into host cells, thereby preventing infection and viral replication. 37 It is important to note that these vaccines may induce other non‐neutralising antibodies with antibody‐dependent cellular cytotoxicity (ADCC), complement‐dependent cytotoxicity or dependent cell‐mediated phagocytosis. 38 However, nAbs are traditionally measured to assess vaccine efficacy, as they are considered the ‘correlate of protection’. Interestingly, there are now several additional proposed ‘correlates of protection’ that, once verified, could be used to assess the efficacy of future influenza vaccines. 39 Importantly, antibody‐based vaccines are very well characterised, generally well tolerated and therefore deemed safe. 37

Table 1.

Currently licenced influenza vaccines

Name of vaccine Type of vaccine Protein immunogen Manufacturer Targeted population Authorised use (country/union)
Vaxigrip Tetra Surface antigen inactivated influenza vaccine (egg‐based) 4× HA Sanofi‐Aventis (Australia)
  • ≥ 6 months

  • TGA

Fluquadri Surface antigen inactivated influenza vaccine (egg‐based) 4× HA Sanofi‐Aventis
  • ≥ 6 months

  • TGA

Fluzone (quadrivalent), Fluzone high‐dose (quadrivalent) and Fluzone intradermal (quadrivalent) Split virion/inactivated influenza vaccine (egg‐based) 4× HA Sanofi Pasteur (USA)
  • ≥ 6 months (Fluzone quadrivalent USA)

  • ≥ 60 years (Fluzone high‐dose Australia)

  • ≥ 65 years (Fluzone high‐dose USA)

  • 18–64 years (Fluzone intradermal USA)

  • FDA

  • TGA

Fluzone (trivalent), Fluzone intradermal (trivalent), Fluzone high‐dose (trivalent) Split virion/inactivated influenza vaccine (egg‐based) 3× HA Sanofi Pasteur (USA)
  • ≥ 6 months (Fluzone quadrivalent USA)

  • 18–64 years (Fluzone Intradermal USA)

  • ≥ 65 years (Fluzone high‐dose USA)

  • FDA

Fluarix Quad and Fluarix (trivalent) Split virion/inactivated influenza vaccine (egg‐based) 3× or 4× HA GlaxoSmithKline Biologicals (USA)
  • ≥ 6 months

  • FDA

Fluarix Tetra Split virion/inactivated influenza vaccine (egg‐based) 4× HA GlaxoSmithKline
  • ≥ 6 months

  • TGA

Flublok quadrivalent and Flublok trivalent Recombinant influenza vaccine 3× or 4× HA Protein Sciences Corporation
  • ≥ 18 years

  • FDA

Flulaval quadrivalent and Flulaval (trivalent) Split virion/inactivated influenza vaccine (egg‐based) 3× or 4× HA ID Biomedical Corporation of Quebec
  • ≥ 6 months

  • FDA

Fluad quadrivalent and Fluad (trivalent) Surface antigen/inactivated influenza vaccine (egg‐based) 3× or 4× HA Seqirus
  • ≥ 65 years (Fluad quadrivalent Australia)

  • ≥ 65 years (Fluad quadrivalent and trivalent USA)

  • TGA

  • FDA

Fluad Tetra Surface antigen/inactivated influenza vaccine (egg‐based) 4× HA + NA (only HA quantity reported) Seqirus, the Netherlands
  • ≥ 65 years

  • European Medicines Agency

Flumist Quad and Flumist Live attenuated vaccine Various influenza proteins MedImmune, LLC
  • 2–49 years

  • FDA

Afluria Quad and Afluria Trivalent Split virion/inactivated influenza vaccine (egg‐based) 4× HA Seqirus (Australia and USA)
  • ≥ 5 years (Alfuria quad Australia)
  • ≥ 18 years (Alfuria quad and trivalent USA)
  • TGA

  • FDA

Flucelvax quad and Flucelvax trivalent Surface antigen/inactivated influenza vaccine (cell‐based) 3× or 4× HA Seqirus
  • ≥ 2 years (Flucelvax quad Australia)

  • ≥ 6 months Flucelvax quad and trivalent (USA)

  • TGA

  • FDA

Flucelvax Tetra Surface antigen/inactivated influenza vaccine (cell‐based) 4× HA + NA (only HA quantity reported) Seqirus
  • ≥ 2 years

  • European Medicines Agency

Influvac Tetra Surface antigen/inactivated influenza vaccine (egg‐based) 4× HA Viatris (Australia)
  • ≥ 6 months (Australia)
  • TGA

Fluenz Tetra Live attenuated vaccine Various influenza proteins AstraZeneca
  • 2–18 years

  • European Medicines Agency

Agriflu Surface antigen/inactivated influenza vaccine (egg‐based) 3× HA + NA (only HA quantity reported) Seqirus
  • ≥ 18 years

  • FDA

Supemtek Recombinant influenza vaccine (cell‐based) 4× HA Sanofi Pasteur
  • ≥ 18 years

  • European Medicines Agency

Fluvirin Subunit/inactivated influenza vaccine (egg‐based) 4× HA + NA (only HA quantity reported) Seqirus
  • ≥ 4 years

  • FDA

Food and Drug Administration, Therapeutic and Goods Administration and European Medicines Agency approved influenza vaccines. Lists of approved vaccines were gathered from their respective governmental administrative databases (February 2023) including FDA at https://www.fda.gov/vaccines‐blood‐biologics/vaccines/vaccines‐licensed‐use‐united‐states, TGA at https://www.ebs.tga.gov.au/ebs/picmi/picmirepository.nsf/PICMI?OpenForm&t=PI&q=Afluria&r=/ and European medicines agency vaccines at https://www.ecdc.europa.eu/en/seasonal‐influenza/prevention‐and‐control/vaccines/types‐of‐seasonal‐influenza‐vaccine and https://www.ema.europa.eu/en. Age, composition and target population information was gathered directly from the manufacturer's websites, the Australian Government Australian Immunisation Handbook https://immunisationhandbook.health.gov.au/ and the FDA and European medicines agency websites as earlier.

Limitation of current influenza vaccines

One major disadvantage of current antibody‐based influenza vaccines is that the majority target the HA viral glycoproteins that are highly susceptible to mutations. 20 This is a significant issue, as nAbs are unable to neutralise antigenically differentiated strains, and as such, the previous year's vaccine may not provide cross‐protection to current circulating strains. 37 For this reason, influenza vaccines require yearly reformulations as per the WHO's recommendations. 2

Another significant disadvantage of current influenza vaccines is the lengthy manufacturing process. Influenza virus proteins are typically grown in embryonated hens' eggs which can take in excess of 6 months, and therefore relies on prediction of upcoming antigenic strains more than 6 months into the future. 40 Moreover, the use of chicken eggs may also not be suitable for all individuals. 41 For example, egg allergies are the second most common leading food allergy besides milk in children and may pose a problem during vaccinations. 41 , 42 Additionally, the WHO gathers information from the WHO Global Influenza Surveillance and Response System (GISRS) that monitors and predicts upcoming antigenic strains by surveying influenza data collected. 2 With this information, a recommendation is made for the upcoming influenza virus season. 2 Given predictions are required so far in advance, recommendations occasionally result in a mismatch between the predicted vaccine strain and the actual circulating strain. 43 This was seen in the 2014–2015 season in the United States which resulted in a 6% overall vaccine efficacy against the A/H3N2 strain. 44 Furthermore, the growth of influenza viruses have been known to introduce mutations which can lead to further variations in vaccine efficacy. 45 Even when the predicted strains do match the circulating strains, vaccine efficacy can be highly variable. Several studies that have systematically reviewed databases such as PubMed and Embase, 46 , 47 reported an overall vaccine efficacy of 33% against the A/H3N2 influenza strain (pooled) from the years 2004–2015. 46 , 47 Although currently licenced influenza vaccines have been effective, novel vaccines are required to counteract the disadvantages of currently licenced vaccines and provide long‐lived, broader protection against distinct influenza virus strains, preventing the need for annual vaccination.

Novel technologies and upcoming influenza vaccines

The need for an updated influenza vaccine to address the above‐mentioned disadvantages is a topic of high activity in the scientific community, with many new influenza vaccines currently undergoing clinical trials. 48 , 49 , 50 Many of these have been recently reviewed in depth by Hu et al. 34 and as such, we make note the type of vaccine and their key advantages and disadvantageous. Novel technologies for influenza virus vaccines include genetically modified influenza virus vaccines, virus‐like particle (VLP) vaccines, nanoparticle vaccines, viral vector vaccines, mRNA vaccines and recombinant protein‐based vaccines (Table 2). 34 Interestingly, these novel technologies make use of different molecular mechanisms and different routes of vaccination to deliver the antigen to their target locations within the body, and this has been reviewed by Hu et al. 34

Table 2.

An overview of selected clinical trial vaccines for influenza

Vaccine technology and example Typical influenza protein target Immune‐targeted response Advantages Reference
Genetically modified influenza vaccines – RedeeFlu M2SR Haemagglutinin and neuraminidase Neutralising antibody response Stimulate a natural infection with lower risk of adverse events 44
Nanoparticle vaccines – NANOFLU Haemagglutinin Neutralising antibody response and CD4+ T‐cell activation Nanoparticles can deliver specific proteins, peptides or mRNA material intracellularly 57
Virus‐like particles – quadrivalent VLP Haemagglutinin Neutralising antibody response and CD4+ T‐cell activation Do not contain viral genetic material, can express target proteins and VLP vaccines have been used successfully in the past against HPV 63
Viral vector vaccine – NasoVAx Haemagglutinin Neutralising antibody response and T‐cell activation Can deliver specific genetic influenza genes via an unrelated virus and can stimulate T cells 67
mRNA vaccine – Pfizer‐bionTech Haemagglutinin Activation unknown/undisclosed The technology has been proven to be successful against SARS‐CoV‐2 71, 104
Protein based vaccine – FLU‐V Matrix 1, matrix 2 and nucleoprotein Neutralising antibody response, CD4+ and CD8+ T‐cell activation Can target more conserved internal proteins that are less likely to be mutated 72

Clinical trial vaccines and their respective examples are listed against the influenza virus. Genetically modified influenza vaccines, nanoparticle vaccine, virus‐like particles, vector‐based vaccines, mRNA‐based vaccine and protein‐based vaccine are listed with their targeted antigen and immune response.

Genetically modified influenza vaccines are analogous to the conventional live attenuated influenza vaccines (LAIV), which are, as their name suggests, live and mimic natural infection, but are designed to have decreased viral virulence to prevent the establishment of disease (i.e. mutated to be replication deficient at body temperature). 51 Conversely, genetically modified virus vaccines utilise other methods to decrease viral virulence or pathogenicity, namely de‐optimising or removing influenza proteins or generating chimeric influenza strains. 34 , 51 These vaccines are typically delivered intramuscularly or intranasally. 34 An advantage of genetically modified influenza vaccines is that they simulate a natural influenza infection like LAIVs, with reduced risk of adverse reactions. 34 , 44 , 52 The RedeeFlu M2SR vaccine is a genetically modified A/Brisbane/10/2007(H3N2) influenza virus vaccine currently in phase II clinical trials. 44 The virus used in this vaccine is M2 deficient. 44 The M2 gene is necessary for viral entry, viral assembly and viral egress and as such, the M2‐deficient virus can only replicate once. 44 , 53 , 54 The RedeeFlu M2SR vaccine displayed promising nAb response efficacy towards the antigenically similar A/Belgium/4217/2015(H3N2) strain, while having minor adverse reactions compared to the placebo. 44

Nanoparticles are another technology being utilised for influenza vaccine design, acting as a delivery vehicle for proteins, peptides or mRNA. As the name implies, these vaccines contain small particles made up of either organic or inorganic materials. 55 , 56 These vaccines are injected intramuscularly and are appealing for vaccine development as they can deliver specific proteins internally via cell‐mediated endocytosis or externally. 55 NanoFlu is a nanoparticle vehicle vaccine that is currently in phase III clinical trials targeting adults ≥ 65 years. 57 The vaccine incorporates four separate HA proteins as advised by the WHO (2019–2020 season). 57 Compared to a conventional quadrivalent inactivated vaccine, NanoFlu showed similar vaccine efficacies (via haemagglutination nAb titre response) and additionally induced a large multifunctional CD4+ T‐cell response. 57 It was noted, however, that it had a higher occurrence of adverse reactions than the control quadrivalent inactivated influenza vaccine. 57

Virus‐like particles are a specific type of nanoparticle which are also being utilised for influenza vaccines. 34 VLPs are generated by expressing viral proteins derived from structural proteins. 58 , 59 When expressed, a phenomenon occurs where viral proteins fold and form an outer structure of a virus. 58 , 59 From there, viral antigens, like HA and NA proteins, can be expressed and bound to the surface of the viral architecture. 58 , 59 , 60 An advantage of VLP is that they do not contain viral genetic material, which makes them relatively safe as they cannot undergo viral replication. 58 VLP can be administered intramuscularly and have made highly successful vaccines against viruses in the past such as human papillomaviruses (HPV). 61 , 62 Against influenza, the quadrivalent VLP vaccine made by Medicago recently underwent phase III clinical trials. 63 The quadrivalent VLP vaccine is expressed in plants and contains four separate HA proteins (recommended by the WHO), aimed at inducing a nAb and CD4+ T‐cell response. 63 Although deemed safe, unfortunately the vaccine did not meet its primary efficacious endpoint, and a lot‐to‐lot consistency trial commenced, which supported their initial endpoint. 63 , 64

Viral vector vaccines comprise whole replicative‐deficient unrelated viruses, typically adenoviruses, as vectors for the delivery through several vaccination routes 65 , 66 of specific genetic material (e.g. DNA plasmids, mRNA) and stimulate the production of the viral proteins of interest. An advantage of viral vectors is that they can induce humoral and T‐cell‐mediated immunity. 65 The NasoVAX vaccine utilises a genetically engineered replication‐deficient vector expressing an intact HA gene from the A/California/04/2009(H1N1)‐like influenza strain. 67 The completed phase II clinical trial concluded that NasoVAX accomplished a 100% seroprotection rate [a measurement of the proportion of participants with a haemagglutination inhibition (HAI) titre of ≥ 1:40], similar to the registered quadrivalent inactivated control vaccine. 67 NasoVAX also recorded an ELISPOT assay measuring IFNγ production in T cells which indicated a higher production of cytokines than control. 67

Influenza vaccines utilising mRNA technology typically encased in a nanoparticle delivery vector are also in clinical trials. 34 mRNA technology was brought into the public eye by the COVID‐19 pandemic, as many of the vaccines that were available were mRNA based. 68 mRNA vaccines utilise messenger RNA sequences of the viral protein of interest encapsulated in a lipid nanoparticle (LNP), which when delivered intramuscularly can facilitate viral protein translation. 69 Vaccines utilising mRNA technology have been successful in combating SARS‐CoV‐2 infection, the causative agent of COVID‐19, and are now being trialled for the influenza virus. 34 , 70 Both Moderna and Pfizer‐BioNTech vaccines are using mRNA technology to encode four separate HA glycoproteins and are currently in phase III clinical trials. 34 , 71

Finally, protein‐based vaccines are also being used in the fight against influenza viruses. 34 , 72 Protein‐based vaccines typically incorporate large peptides or segments of whole protein (typically 20–35 amino acids) that stimulate humoral and cellular‐mediated immunity (CMI) following subcutaneous or intramuscular vaccination. 34 , 72 Some examples of protein‐based vaccines that are ongoing in clinical trials are the M‐001 vaccine from BiondVax Pharmaceuticals (Phase III), the FP‐01.1 vaccine from Immune Targeting Systems (Phase I) and the FLU‐v vaccine from ConserV Bioscience (Phase II). 34 In the case of the M‐001 vaccine, a single protein consisting of B‐cell, CD4+ and CD8+ T‐cell epitopes from the NP, HA and M1 proteins is expressed in an Escherichia coli bacterial system. 73 , 74 For FLU‐v, a different approach is used, where four peptides of the conserved M1 (32‐mer), M2 (24‐mer) and NP (flu A: 20‐mer and flu B: 19‐mer) were synthetically generated. 72 While the FP‐01.1 vaccine incorporates six different 35‐mer peptides from the PB1, PB2, NP and the matrix proteins, which together are joined using fluorocarbons. 75 What is comparable between the M‐001, FP‐01.1 and FLU‐v vaccines is that they utilise proteins or protein‐derived peptides from proteins more conserved than the surface glycoproteins counterpart. 72 , 73 , 75 , 76 This is advantageous as the GISRS recommendations are not necessarily required for this vaccine.

Regardless of the different vaccine approaches, further research, clinical trial safety and vaccine efficacy endpoints must be met before the approval of vaccine can be used for administration. Of note, many of these clinical trials evaluate only nAb as a measure of efficacy, without considering other types of immune responses that may be being induced.

Exploiting CD8+ T cells for future influenza virus vaccines

The numerous vaccines that are currently ongoing in clinical trials have many advantages and disadvantages when protecting against future influenza strains. However, it would be of benefit to design and manufacture vaccines that are independent of predictions and can protect against several influenza viral subtypes. Targeting more conserved sections of the influenza virus that can induce CD8+ T‐cell responses towards antigenically distinct strains, along with B‐cell and antibody responses, may be one way to achieve this. 21 , 77

Following activation by a pathogen‐derived peptide, CD8+ T cells can produce cytolytic molecules such as granzymes and perforins that can directly destroy infected cells. 78 , 79 Furthermore, CD8+ T cells also produce cytokines such as IFNγ and TNF, which recruit neighbouring immune cells to the site of infection to assist in viral clearance. 78 , 79 , 80 , 81 CD8+ T cells have been well studied in the context of influenza virus and are known to be protective, 82 and this has been recently reviewed in detail. 16 For example, in 1983, an article published by McMichael et al. demonstrated that CD8+ T cells played a crucial role in viral clearance and more importantly demonstrated the ability to recognise antigenically distinct strains via cross‐reactivity. 82 Furthermore, CD8+ T cells have also been shown to decrease the severity of influenza disease. Indeed, functional CD8+ T cells decreased influenza‐like illnesses in a cohort infected with the A/H1N1‐pdm‐09 virus. 83 Others showed that individuals with cross‐reactive memory CD8+ T cells were observed to recover more swiftly than those lacking memory CD8+ T cells. 84 , 85 Additionally, memory CD8+ T cells specific to influenza are known to be long‐lived and have been identified directly ex vivo over a 13‐year time course. 86 This evidently demonstrates the potential effectiveness of targeting CD8+ T cells in future influenza vaccines. 87 , 88 Finally, the necessity to provide protection to those in high‐risk populations, such as Indigenous populations, are of high priority, and a CD8+ T‐cell mediated vaccine may bridge this gap and thus reduce the severity of disease in these individuals. 89 According to some reports, Indigenous populations (especially Indigenous Australians) are 6 times more likely to be hospitalised than non‐Indigenous populations and can be attributed to chronic diseases, lack of or limited access to medical service and lower socio‐economic status. 89 , 90

Designing CD8+ T‐cell‐based vaccines for broad population coverage: The challenges of HLA‐I polymorphism

Targeting a CD8+ T‐cell response in conjunction with B‐cell and antibody responses via vaccination is clearly of benefit, and some of the previously described vaccine technologies are clearly capable of inducing these responses. CD8+ T cells recognise short peptides, typically 8–10 amino acids long, that are presented by the human leukocyte antigens class I (HLA‐I). 91 These HLA‐I molecules are genetically encoded and are highly polymorphic, 92 and it is a significant challenge when selecting influenza derived targets that can induce CD8+ T‐cell responses (epitopes) and also provide protection to the global population. 93 More than 25 000 distinctive HLA‐I alleles have been identified to date. 94 , 95 , 96 Moreover, HLA‐I molecules have distinct motif preferences for peptides [preferences based on different residues at position 2 (P2) and the last position (PΩ)]. 97 , 98 Interestingly, several HLA‐I are grouped into superfamilies based on shared peptide motif preferences. 97 The polymorphism and peptide motif preferences of HLA‐I presents a profound challenge in selecting the targets to be included in a CD8+ T‐cell‐mediated vaccine. 94 , 96 , 99 Furthermore, because of the genetic nature of inheritance, distinct HLA profiles can be linked to certain geographical locations and ethnicities. 21 , 92 , 95 Despite this apparent bottleneck, 21 , 94 , 95 including within a vaccine, several immunogenic CD8+ T‐cell targets presented by prevalent HLA‐I molecules, and perhaps even multiple HLA‐I molecules in the same superfamily, may provide a solution to provide broad population coverage for a future T‐cell‐mediated vaccine that could limit viral escape and provide long‐term protection.

Many highly prevalent HLA‐I molecules have no known influenza‐derived epitopes

Although there have been many studies identifying and characterising immunogenic influenza‐derived peptides restricted to different HLA molecules, 3 , 16 , 85 , 87 , 100 , 101 , 102 we are not aware of any published systematic review of known immunogenic epitopes restricted to the most prevalent HLA‐I molecules expressed worldwide. Using the database created by Solberg et al., we noted the top 10 most prevalent HLA‐A, ‐B and ‐C molecules expressed worldwide (Table 3). Interestingly, the cumulative frequency (which does not account for the co‐expression of HLA‐I molecules within a single individual) of the top 10 HLA‐A, HLA‐B and HLA‐C molecules exceeds 100% population coverage. This suggests that including a single conserved and immunogenic epitope (n = 30 epitopes) or a segment(s) of protein(s) containing multiple immunogenic epitopes could provide significant CD8+ T‐cell‐mediated protection via vaccination for most if not all individuals worldwide (Table 3).

Table 3.

Top 10 HLA‐A, HLA‐B and HLA‐C alleles and their global prevalence

HLA prevalence HLA‐A HLA‐B HLA‐C
Allele Frequency (%) Allele Frequency (%) Allele Frequency (%)
1 A*24:02 18.82 B*35:01 5.47 C*07:02 13.10
2 A*02:01 15.28 B*51:01 5.22 C*04:01 11.18
3 A*11:01 11.66 B*40:01 5.12 C*03:04 9.13
4 A*01:01 4.84 B*44:03 4.47 C*01:02 8.48
5 A*03:01 4.27 B*40:02 4.18 C*07:01 6.89
6 A*31:01 4.09 B*07:02 4.11 C*06:02 6.16
7 A*33:03 4.08 B*15:01 3.43 C*03:03 5.58
8 A*02:06 3.47 B*07:04 3.12 C*08:01 4.52
9 A*26:01 3.35 B*08:01 2.96 C*15:02 3.36
10 A*30:01 2.51 B*58:01 2.89 C*12:02 3.19

The top 10 HLA‐A, B and C alleles were acquired in February 2023. The global frequency of each HLA‐A, B and C alleles were obtained from the http://pypop.org/popdata/2008/byfreq‐A.php.html database. 95 Each HLA allele is ranked from 1 to 10, with 1 being the highest global frequency and 10 the lowest frequency.

Subsequently, we reviewed how many known IAV‐, IBV‐ and ICV‐derived epitopes have been reported for the top 10 most prevalent HLA‐A, ‐B and ‐C molecules using the immune epitope database (IEDB) 100 (Figure 1, Table 4 and Supplementary table 1). We limited the search results to positive T‐cell responses as indicative of epitopes. These positive responses were identified using a range of assays including intracellular cytokine staining, ELISPOT, tetramer staining and 51 chromium release assays. For our analysis, epitopes with an identical sequence and the same HLA‐I restriction were considered a single epitope. Epitopes with an identical sequence but different HLA‐I restriction are considered separate epitopes. Note that these epitopes are of variable immunogenicity, ranging from highly to weakly immunogenic. Since future vaccines should predominately include highly immunogenic epitopes, it would be important to consider the minimal epitope and level of immunogenicity of these epitopes, which is outside of the scope of this review, before considering their potential as vaccine candidates.

Figure 1.

Figure 1

Top 10 most prevalent HLA‐A, B and C molecules and their known influenza‐derived epitopes. Known immunogenic IAV‐, IBV‐ and ICV‐derived epitopes restricted by the top 10 HLA‐A, B and C molecules were gathered from the Immune Epitope database in March and October 2023 (https://www.iedb.org/). 100 The defined search result was restricted to linear peptides only, the influenza A virus, human hosts, positive T‐cell‐based assays only and the HLA‐I molecule of interest. Summary of the frequency of published epitopes per HLA molecule.

Table 4.

Number of published T‐cell epitopes for the top 10 HLA‐A, ‐B and ‐C molecules

HLA‐A Number of epitopes Number of epitopes Number of epitopes
IAV IBV ICV HLA‐B IAV IBV ICV HLA‐C IAV IBV ICV
A*24:02 25 16 0 B*35:01 19 0 0 C*07:02 0 0 0
A*02:01 60 7 0 B*51:01 0 0 0 C*04:01 0 0 0
A*11:01 33 3 0 B*40:01 3 0 0 C*03:04 0 0 0
A*01:01 8 0 0 B*44:03 16 0 0 C*01:02 0 0 0
A*03:01 10 1 1 B*40:02 6 0 0 C*07:01 0 0 0
A*31:01 9 0 0 B*07:02 14 0 0 C*06:02 0 0 0
A*33:03 2 0 0 B*15:01 11 0 0 C*03:03 0 0 0
A*02:06 7 0 0 B*07:04 0 0 0 C*08:01 1 0 0
A*26:01 3 0 0 B*08:01 3 0 0 C*15:02 0 0 0
A*30:01 0 0 0 B*58:01 1 0 0 C*12:02 0 0 0

Top 10 HLA‐A, B and C molecules were gathered from the Immune Epitope database (https://www.iedb.org/) in March and October 2023. 100 The defined search result was restricted to linear peptides, influenza A, B or C virus (separately), human hosts, positive T‐cell‐based assays only and the HLA‐I molecule of interest. Note that some epitopes were restricted to more than one HLA molecule, as described by their respective publications.

Interestingly, the current landscape of known IAV‐derived T‐cell epitopes is highly focused on only 4 of the top 30 HLA‐I molecules (HLA‐A*24:02, ‐A*02:01, ‐A*11:01 and ‐B*35:01), with ~60% of the IAV‐derived epitopes identified binding to one of these 4 HLA‐I molecules (n = 137/231). From the 231 IAV‐derived epitopes assessed, 157 were restricted to HLA‐A molecules (68%), 73 to HLA‐B molecules (32%) and one to HLA‐C (< 0.1%) (Figure 1, Table 4). The HLA molecule with the most known epitopes is HLA‐A*02:01 (n = 60 epitopes), which is the second most prevalent HLA‐A molecule with a global expression of 15.2% (Figure 1, Tables 3 and 4). Other HLA molecules with similar (HLA‐A*11:01 at 11.6%, HLA‐C*04:01 at 11.17%) or higher (HLA‐A*24:01 at 18.80%) global prevalence, have fewer to no known IAV‐derived epitopes (Tables 3 and 4).

Like IAV, the majority (16/27 or 60%) of the IBV epitopes are restricted to a single HLA‐I molecule, namely HLA‐A*24:02 (Figure 1, Table 4). In contrast to IAV, HLA‐A*02:01 exclusively has seven IBV epitopes published, while HLA‐A*11:01 and HLA‐A*03:01 have a combined total of four peptides published (HLA‐A*11:01; n = 3, ‐A*03:01; n = 1). No IBV epitopes have so far been published for HLA‐B or HLA‐C. Strikingly, only a single weakly immunogenic ICV‐derived epitope has been reported according to the IEDB and is restricted to HLA‐A*03:01 from a single paper published in 2022. 3

Together, this analysis suggests that most HLA‐I molecules have no known influenza‐derived epitopes, making them significantly understudied. Thus, these HLA‐I molecules should be a focus for future epitope identification studies to prove new knowledge and permit the selection of the best epitopes for inclusion in future influenza vaccines to provide broad population coverage.

Current landscape of known epitopes and their proteins

Future influenza vaccines could induce CD8+ T‐cell responses by including individual epitopes, overlapping epitopes or conserved epitope‐rich regions of different influenza proteins. As such, we briefly looked at the known influenza‐derived epitopes, despite being focused on select HLA‐I molecules, to see where they mapped against the influenza proteins (Figures 2 and 3).

Figure 2.

Figure 2

Top 10 most prevalent HLA‐A, ‐B and ‐C‐restricted influenza‐derived epitopes and their protein of origin. Access to the immune epitope database https://www.iedb.org/ 100 was used to identify influenza‐derived epitopes (IAV, IBV and ICV) restricted to the top 10 most prevalent HLA‐A, ‐B and ‐C‐restricted peptides and their protein of origin as per this figure. Data are shown as stacked bar graphs representing the frequency of epitopes per influenza protein, where n is the number of epitopes published for each HLA‐A, ‐B and ‐C molecule.

Figure 3.

Figure 3

Epitope mapping of known immunogenic IAV‐, IBV‐ and ICV‐derived epitopes restricted by the top 10 HLA‐A, ‐B and ‐C molecules to NP and M1. NP‐ and M1‐derived immunogenic epitopes were mapped to their respective protein to visualise the cluster of sequences along a given protein. Each protein sequence length is directly proportional to the A/Puerto Rico/8/1934 H1N1 influenza A strain (UniProt ID: P03485 and P03466), downloaded from https://www.uniprot.org/. 105 Each line represents a specific peptide sequence, name and length. The green line represents epitopes restricted to HLA‐A, pink for HLA‐B and red for HLA‐C. All sequences that contained a single amino acid change were included as the same epitope distance/length. NP511–520 was not included as the epitope position extended past the A/Puerto Rico/8/1934 H1N1 protein sequence (P03466).

The known immunogenic IAV‐derived epitopes originated from a range of influenza proteins (Figure 2). Of note, epitopes derived from the nucleoprotein (NP) and matrix 1 (M1) were well represented across the HLA‐A and HLA‐B molecules, and the single IAV‐derived epitope restricted to the HLA‐C molecule was also M1 derived. For IBV and ICV, most epitopes were also derived from NP and M1 proteins, with a small proportion of HA and NS1 proteins observed for HLA‐A*02:01. The NP‐ and M1‐derived epitopes were also spread across the entire length of their respective proteins, with several sets of overlapping epitopes, some of which are likely to contain shared core epitopes (Figure 3).

These data collectively suggest that M1 and NP contain most of the known epitopes so far. This is consistent with reports of NP and M1 being a major target of CD8+ T‐cell responses across donors with distinct HLA‐I profiles. 88 , 103 Importantly, these proteins are known to be conserved, and a set of IAV‐derived epitopes, from NP and M1 were deemed ‘universally conserved’ across several IAV strains including an avian‐derived H7N9 strain. 85 It will be interesting to find out whether these proteins also contain novel epitopes restricted to the understudied, yet prevalent HLA molecules, which might make them ideal proteins for future influenza vaccines. Indeed, Muraduzzaman et al. 16 recently also eluted to the idea of targeting NP‐ and M1‐derived epitopes for universal CD8+ T‐cell flu vaccine.

Conclusion

The influenza virus continues to cause severe respiratory illnesses and mortalities annually and remains a threat to human health with the potential to be responsible for future global pandemics. Although the CDC, TGA and the European medicines agency have approved influenza vaccines for administration, their efficacies fluctuate yearly depending on the circulating strains. Predicting which influenza strains will be circulating 6 months in the future can lead to mismatching vaccines with poorer efficacies. Thus, if a global pandemic were to arise, current strategies may not suffice. Fortunately, as time progresses, new vaccine technologies are made available. Currently, the main clinical trial vaccines for the influenza virus fall into one of several technologies including genetically modified influenza vaccine, VLP vaccines, nanoparticle vaccines, viral vector vaccines, mRNA vaccines or recombinant protein‐based vaccines. Many of these vaccines induce a neutralising antibody response to the surface glycoproteins. However, a select few vaccines also induce a T‐cell‐mediated response that may offer better and longer lasting protection. CD8+ T cells typically recognise peptides of more conserved protein origins. However, HLA‐I polymorphism poses a significant challenge in designing CD8+ T‐cell targets for inclusion in future vaccines.

In this review, we assessed the known immunogenic epitopes for the most prevalent HLA‐A, ‐B and ‐C molecules worldwide, showing that most HLA‐I molecules have no known influenza‐derived epitopes, with the majority of those published focused on a select few well‐studied HLA molecules. Thus, the rationale for future vaccine design is imperative to fill this gap in knowledge and identify novel epitopes restricted to these understudied but prevalent HLA‐I molecules.

Conflict of interest

The authors declare no conflict of interest.

Author contributions

Samuel Liwei Leong: Data curation; formal analysis; funding acquisition; investigation; project administration; writing – original draft; writing – review and editing. Stephanie Gras: Conceptualization; formal analysis; funding acquisition; project administration; supervision; writing – review and editing. Emma J Grant: Conceptualization; formal analysis; funding acquisition; project administration; supervision; validation; writing – original draft; writing – review and editing.

Supporting information

Supplementary table 1

Acknowledgments

We thank the Immune Epitope Database (IEDB) and PyPOP.org HLA‐I database for providing these wonderful resources for researchers, as well as our colleagues who have contributed to the scientific knowledge contained within these databases. We also thank Miss Emily Curtis for advice on figures. SLL is supported by a La Trobe University RTP Scholarship, SG is supported by an NHMRC Senior Research Fellowship (#1159272) and EJG is supported by an Australian Research Council DECRA Fellowship (DE210101479) and an AINSE Early Career Research Grant. Open access publishing facilitated by La Trobe University, as part of the Wiley ‐ La Trobe University agreement via the Council of Australian University Librarians.

References

  • 1. Lycett SJ, Duchatel F, Digard P. A brief history of bird flu. Philos Trans R Soc Lond Ser B Biol Sci 2019; 374: 20180257. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2. Hay AJ, McCauley JW. The WHO global influenza surveillance and response system (GISRS) – a future perspective. Influenza Other Respir Viruses 2018; 12: 551–557. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3. Nguyen AT, Lau HMP, Sloane H et al. Homologous peptides derived from influenza A, B and C viruses induce variable CD8+ T cell responses with cross‐reactive potential. Clin Transl Immunology 2022; 11: e1422. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. Gaitonde DY, Moore FC, Morgan MK. Influenza: Diagnosis and treatment. Am Fam Physician 2019; 100: 751–758. [PubMed] [Google Scholar]
  • 5. Short KR, Kroeze EJBV, Fouchier RAM, Kuiken T. Pathogenesis of influenza‐induced acute respiratory distress syndrome. Lancet Infect Dis 2014; 14: 57–69. [DOI] [PubMed] [Google Scholar]
  • 6. Chou Y‐Y, Vafabakhsh R, Doğanay S, Gao Q, Ha T, Palese P. One influenza virus particle packages eight unique viral RNAs as shown by FISH analysis. Proc Natl Acad Sci USA 2012; 109: 9101–9106. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7. Jiang L, Chen H, Li C. Advances in deciphering the interactions between viral proteins of influenza A virus and host cellular proteins. Cell Insight 2023; 2: 100079. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Monto AS, Fukuda K. Lessons from influenza pandemics of the last 100 years. Clin Infect Dis 2019; 70: 951–957. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9. Bouvier NM, Palese P. The biology of influenza viruses. Vaccine 2008; 26 Suppl 4: D49–D53. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10. Kosik I, Yewdell JW. Influenza hemagglutinin and neuraminidase: YinYang proteins coevolving to thwart immunity. Viruses 2019; 11: 346. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11. Wright PF, G Neumann G, Kawaoka Y. Orthomyxoviruses. In: Knipe DM, Howley PM, Griffin DE et al., eds. Fields Virology. Philadelphia: Lippincott Williams & Wilkins; 2007:1691–1740. [Google Scholar]
  • 12. Parrish CR, Murcia PR, Holmes EC. Influenza virus reservoirs and intermediate hosts: Dogs, horses, and new possibilities for influenza virus exposure of humans. J Virol 2015; 89: 2990–2994. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13. Chang D, Lin M, Song N et al. The emergence of influenza B as a major respiratory pathogen in the absence of COVID‐19 during the 2021–2022 flu season in China. Virol J 2023; 20: 189. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Xu C, Chan KH, Tsang TK et al. Comparative epidemiology of influenza B Yamagata‐ and Victoria‐lineage viruses in households. Am J Epidemiol 2015; 182: 705–713. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15. Webby RJ, Webster RG, Richt JA. Influenza viruses in animal wildlife populations. Curr Top Microbiol Immunol 2007; 315: 67–83. [DOI] [PubMed] [Google Scholar]
  • 16. Muraduzzaman AKM, Illing PT, Mifsud NA, Purcell AW. Understanding the role of HLA class I molecules in the immune response to influenza infection and rational design of a peptide‐based vaccine. Viruses 2022; 14: 2578. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17. Sederdahl BK, Williams JV. Epidemiology and clinical characteristics of influenza C virus. Viruses 2020; 12: 89. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. Krammer F. The human antibody response to influenza A virus infection and vaccination. Nat Rev Immunol 2019; 19: 383–397. [DOI] [PubMed] [Google Scholar]
  • 19. Soema PC, Kompier R, Amorij J‐P, Kersten GFA. Current and next generation influenza vaccines: Formulation and production strategies. Eur J Pharm Biopharm 2015; 94: 251–263. [DOI] [PubMed] [Google Scholar]
  • 20. Shao W, Li X, Goraya M, Wang S, Chen J‐L. Evolution of influenza A virus by mutation and re‐assortment. Int J Mol Sci 2017; 18: 1650. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21. Grant EJ, Quiñones‐Parra SM, Clemens EB, Kedzierska K. Human influenza viruses and CD8+ T cell responses. Curr Opin Virol 2016; 16: 132–142. [DOI] [PubMed] [Google Scholar]
  • 22. Webster RG, Laver WG, Air GM, Schild GC. Molecular mechanisms of variation in influenza viruses. Nature 1982; 296: 115–121. [DOI] [PubMed] [Google Scholar]
  • 23. Kim H, Webster RG, Webby RJ. Influenza virus: Dealing with a drifting and shifting pathogen. Viral Immunol 2018; 31: 174–183. [DOI] [PubMed] [Google Scholar]
  • 24. van de Wall S, Badovinac VP, Harty JT. Influenza‐specific lung‐resident memory CD8+ T cells. Cold Spring Harb Perspect Biol 2021; 13: a037978. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25. Treanor J. Influenza vaccine – Outmaneuvering antigenic shift and drift. N Engl J Med 2004; 350: 218–220. [DOI] [PubMed] [Google Scholar]
  • 26. Webster RG, Govorkova EA. Continuing challenges in influenza. Ann N Y Acad Sci 2014; 1323: 115–139. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Doherty M, Schmidt‐Ott R, Santos JI et al. Vaccination of special populations: Protecting the vulnerable. Vaccine 2016; 34: 6681–6690. [DOI] [PubMed] [Google Scholar]
  • 28. Grant EJ, Chen L, Quiñones‐Parra S et al. T‐cell immunity to influenza A viruses. Crit Rev Immunol 2014; 34: 15–39. [DOI] [PubMed] [Google Scholar]
  • 29. Fiers W, De Filette M, Birkett A, Neirynck S, Min Jou W. A “universal” human influenza A vaccine. Virus Res 2004; 103: 173–176. [DOI] [PubMed] [Google Scholar]
  • 30. Reed C, Chaves SS, Daily Kirley P et al. Estimating influenza disease burden from population‐based surveillance data in the United States. PLoS One 2015; 10: e0118369. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31. Centers for Disease Control and Prevention . Estimated Flu‐Related Illnesses, Medical Visits, Hospitalizations, and Deaths in the United States – 2019–2020 Flu Season. Atlanta, GA: Centers for Disease Control and Prevention; 2023. https://www.cdc.gov/flu/about/burden/2019‐2020.html [Google Scholar]
  • 32. Centers for Disease Control and Prevention . 2022–2023 U.S. Flu Season: Preliminary In‐Season Burden Estimates. Atlanta, GA: Centers for Disease Control and Prevention; 2023. https://www.cdc.gov/flu/about/burden/preliminary‐in‐season‐estimates.htm [Google Scholar]
  • 33. Courville C, Cadarette SM, Wissinger E, Alvarez FP. The economic burden of influenza among adults aged 18 to 64: A systematic literature review. Influenza Other Respir Viruses 2022; 16: 376–385. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34. Hu L, Lao G, Liu R, Feng J, Long F, Peng T. The race toward a universal influenza vaccine: Front runners and the future directions. Antivir Res 2023; 210: 105505. [DOI] [PubMed] [Google Scholar]
  • 35. Boyoglu‐Barnum S, Ellis D, Gillespie RA et al. Quadrivalent influenza nanoparticle vaccines induce broad protection. Nature 2021; 592: 623–628. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36. Guthmiller JJ, Utset HA, Wilson PC. B cell responses against influenza viruses: Short‐lived humoral immunity against a life‐long threat. Viruses 2021; 13: 965. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37. Thomas PG, Keating R, Hulse‐Post DJ, Doherty PC. Cell‐mediated protection in influenza infection. Emerg Infect Dis 2006; 12: 48–54. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38. Gao R, Sheng Z, Sreenivasan CC, Wang D, Li F. Influenza A virus antibodies with antibody‐dependent cellular cytotoxicity function. Viruses 2020; 12: 276. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39. Krammer F, Weir JP, Engelhardt O, Katz JM, Cox RJ. Meeting report and review: Immunological assays and correlates of protection for next‐generation influenza vaccines. Influenza Other Respir Viruses 2020; 14: 237–243. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40. Rajaram S, Boikos C, Gelone DK, Gandhi A. Influenza vaccines: The potential benefits of cell‐culture isolation and manufacturing. Ther Adv Vaccines Immunother 2020; 8: 2515135520908121. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41. McNeil MM, DeStefano F. Vaccine‐associated hypersensitivity. J Allergy Clin Immunol 2018; 141: 463–472. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42. Dhanapala P, De Silva C, Doran T, Suphioglu C. Cracking the egg: An insight into egg hypersensitivity. Mol Immunol 2015; 66: 375–383. [DOI] [PubMed] [Google Scholar]
  • 43. Agor JK, Özaltın OY. Models for predicting the evolution of influenza to inform vaccine strain selection. Hum Vaccin Immunother 2018; 14: 678–683. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44. Eiden J, Volckaert B, Rudenko O et al. M2‐deficient single‐replication influenza vaccine‐induced immune responses associated with protection against human challenge with highly drifted H3N2 influenza strain. J Infect Dis 2022; 226: 83–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45. Urueña A, Micone P, Magneres MC et al. Cost‐effectiveness analysis of cell versus egg‐based seasonal influenza vaccination in children and adults in Argentina. Vaccine 2022; 10: 1627. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46. Belongia EA, Simpson MD, King JP et al. Variable influenza vaccine effectiveness by subtype: A systematic review and meta‐analysis of test‐negative design studies. Lancet Infect Dis 2016; 16: 942–951. [DOI] [PubMed] [Google Scholar]
  • 47. Flannery B, Chung JR, Belongia EA et al. Interim estimates of 2017–18 seasonal influenza vaccine effectiveness – United States, February 2018. MMWR Morb Mortal Wkly Rep 2018; 67: 180–185. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48. Clinicaltrials.gov . National Library of Medicine. Available from: https://clinicaltrials.gov/
  • 49. Estrada LD, Schultz‐Cherry S. Development of a universal influenza vaccine. J Immunol 2019; 202: 392–398. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50. Feranmi F. Universal flu vaccine protects against influenza A and B. Lancet Microbe 2022; 3: e902. [DOI] [PubMed] [Google Scholar]
  • 51. Si L, Shen Q, Li J et al. Generation of a live attenuated influenza A vaccine by proteolysis targeting. Nat Biotechnol 2022; 40: 1370–1377. [DOI] [PubMed] [Google Scholar]
  • 52. Rathnasinghe R, Salvatore M, Zheng H et al. Interferon mediated prophylactic protection against respiratory viruses conferred by a prototype live attenuated influenza virus vaccine lacking non‐structural protein 1. Sci Rep 2021; 11: 22164. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53. Alvarado‐Facundo E, Gao Y, Ribas‐Aparicio RM, Jiménez‐Alberto A, Weiss CD, Wang W. Influenza virus M2 protein ion channel activity helps to maintain pandemic 2009 H1N1 virus hemagglutinin fusion competence during transport to the cell surface. J Virol 2015; 89: 1975–1985. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54. Rossman JS, Lamb RA. Influenza virus assembly and budding. Virology 2011; 411: 229–236. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55. Zhao L, Seth A, Wibowo N et al. Nanoparticle vaccines. Vaccine 2014; 32: 327–337. [DOI] [PubMed] [Google Scholar]
  • 56. Al‐Halifa S, Gauthier L, Arpin D, Bourgault S, Archambault D. Nanoparticle‐based vaccines against respiratory viruses. Front Immunol 2019; 10: 22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57. Shinde V, Cho I, Plested JS et al. Comparison of the safety and immunogenicity of a novel matrix‐M‐adjuvanted nanoparticle influenza vaccine with a quadrivalent seasonal influenza vaccine in older adults: A phase 3 randomised controlled trial. Lancet Infect Dis 2022; 22: 73–84. [DOI] [PubMed] [Google Scholar]
  • 58. Mohsen MO, Bachmann MF. Virus‐like particle vaccinology, from bench to bedside. Cell Mol Immunol 2022; 19: 993–1011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59. Park BR, Bommireddy R, Chung DH et al. Hemagglutinin virus‐like particles incorporated with membrane‐bound cytokine adjuvants provide protection against homologous and heterologous influenza virus challenge in aged mice. Immun Ageing 2023; 20: 20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60. Buffin S, Peubez I, Barrière F et al. Influenza A and B virus‐like particles produced in mammalian cells are highly immunogenic and induce functional antibodies. Vaccine 2019; 37: 6857–6867. [DOI] [PubMed] [Google Scholar]
  • 61. Srivastava V, Nand KN, Ahmad A, Kumar R. Yeast‐based virus‐like particles as an emerging platform for vaccine development and delivery. Vaccines (Basel) 2023; 11: 479. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62. Crawford NW, Hodgson K, Gold M, Buttery J, Wood N, AEFI‐CAN network . Adverse events following HPV immunization in Australia: Establishment of a clinical network. Hum Vaccin Immunother 2016; 12: 2662–2665. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63. Ward BJ, Makarkov A, Séguin A et al. Efficacy, immunogenicity, and safety of a plant‐derived, quadrivalent, virus‐like particle influenza vaccine in adults (18–64 years) and older adults (≥65 years): Two multicentre, randomised phase 3 trials. Lancet 2020; 396: 1491–1503. [DOI] [PubMed] [Google Scholar]
  • 64. Ward BJ, Séguin A, Couillard J, Trépanier S, Landry N. Phase III: Randomized observer‐blind trial to evaluate lot‐to‐lot consistency of a new plant‐derived quadrivalent virus like particle influenza vaccine in adults 18–49 years of age. Vaccine 2021; 39: 1528–1533. [DOI] [PubMed] [Google Scholar]
  • 65. De Vries RD, Rimmelzwaan GF. Viral vector‐based influenza vaccines. Hum Vaccin Immunother 2016; 12: 2881–2901. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66. Travieso T, Li J, Mahesh S, Mello JDFRE, Blasi M. The use of viral vectors in vaccine development. NPJ Vaccines 2022; 7: 75. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67. Tasker S, Wight O'Rourke A, Suyundikov A et al. Safety and immunogenicity of a novel intranasal influenza vaccine (NasoVAX): A phase 2 randomized, controlled trial. Vaccines 2021; 9: 224. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 68. Wilson B, Geetha KM. Lipid nanoparticles in the development of mRNA vaccines for COVID‐19. J Drug Deliv Sci Technol 2022; 74: 103553. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 69. Wang Y, Zhang Z, Luo J, Han X, Wei Y, Wei X. mRNA vaccine: A potential therapeutic strategy. Mol Cancer 2021; 20: 33. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 70. Corbett KS, Edwards DK, Leist SR et al. SARS‐CoV‐2 mRNA vaccine design enabled by prototype pathogen preparedness. Nature 2020; 586: 567–571. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 71. Li C, Lee A, Grigoryan L et al. Mechanisms of innate and adaptive immunity to the Pfizer‐BioNTech BNT162b2 vaccine. Nat Immunol 2022; 23: 543–555. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 72. Oftung F, Næss LM, Laake I, Stoloff G, Pleguezuelos O. FLU‐v, a broad‐Spectrum influenza vaccine, induces cross‐reactive cellular immune responses in humans measured by dual IFN‐γ and granzyme B ELISpot assay. Vaccines (Basel) 2022; 10: 1528. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 73. van Doorn E, Liu H, Ben‐Yedidia T et al. Evaluating the immunogenicity and safety of a BiondVax‐developed universal influenza vaccine (Multimeric‐001) either as a standalone vaccine or as a primer to H5N1 influenza vaccine: Phase IIb study protocol. Medicine (Baltimore) 2017; 96: e6339. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 74. Atmar RL, Bernstein DI, Winokur P et al. Safety and immunogenicity of Multimeric‐001 (M‐001) followed by seasonal quadrivalent inactivated influenza vaccine in young adults – A randomized clinical trial. Vaccine 2023; 41: 2716–2722. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 75. Francis JN, Bunce CJ, Horlock C et al. A novel peptide‐based pan‐influenza A vaccine: A double blind, randomised clinical trial of immunogenicity and safety. Vaccine 2015; 33: 396–402. [DOI] [PubMed] [Google Scholar]
  • 76. Lowell GH, Ziv S, Bruzil S, Babecoff R, Ben‐Yedidia T. Back to the future: Immunization with M‐001 prior to trivalent influenza vaccine in 2011/12 enhanced protective immune responses against 2014/15 epidemic strain. Vaccine 2017; 35: 713–715. [DOI] [PubMed] [Google Scholar]
  • 77. Kreijtz JHCM, De Mutsert G, Van Baalen CA et al. Cross‐recognition of avian H5N1 influenza virus by human cytotoxic T‐lymphocyte populations directed to human influenza A virus. J Virol 2008; 82: 5161–5166. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 78. Bem RA, Bos AP, Bots M et al. Activation of the granzyme pathway in children with severe respiratory syncytial virus infection. Pediatr Res 2008; 63: 650–655. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 79. Topham DJ, Tripp RA, Doherty PC. CD8+ T cells clear influenza virus by perforin or Fas‐dependent processes. J Immunol 1997; 159: 5197–5200. [PubMed] [Google Scholar]
  • 80. Bhat P, Leggatt G, Waterhouse N, Frazer IH. Interferon‐γ derived from cytotoxic lymphocytes directly enhances their motility and cytotoxicity. Cell Death Dis 2017; 8: e2836. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 81. Mehta AK, Gracias DT, Croft M. TNF activity and T cells. Cytokine 2018; 101: 14–18. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 82. McMichael AJ, Gotch FM, Noble GR, Beare PAS. Cytotoxic T‐cell immunity to influenza. N Engl J Med 1983; 309: 13–17. [DOI] [PubMed] [Google Scholar]
  • 83. Sridhar S, Begom S, Bermingham A et al. Cellular immune correlates of protection against symptomatic pandemic influenza. Nat Med 2013; 19: 1305–1312. [DOI] [PubMed] [Google Scholar]
  • 84. Wang Z, Wan Y, Qiu C et al. Recovery from severe H7N9 disease is associated with diverse response mechanisms dominated by CD8+ T cells. Nat Commun 2015; 6: 6833. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 85. Quiñones‐Parra S, Grant E, Loh L et al. Preexisting CD8+ T‐cell immunity to the H7N9 influenza A virus varies across ethnicities. Proc Natl Acad Sci USA 2014; 111: 1049–1054. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 86. van de Sandt CE, Hillaire ML, Geelhoed‐Mieras MM et al. Human influenza A virus‐specific CD8+ T‐cell response is long‐lived. J Infect Dis 2015; 212: 81–85. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 87. Nguyen THO, Sant S, Bird NL et al. Perturbed CD8+ T cell immunity across universal influenza epitopes in the elderly. J Leukoc Biol 2018; 103: 321–339. [DOI] [PubMed] [Google Scholar]
  • 88. Grant E, Wu C, Chan KF et al. Nucleoprotein of influenza A virus is a major target of immunodominant CD8+ T‐cell responses. Immunol Cell Biol 2013; 91: 184–194. [DOI] [PubMed] [Google Scholar]
  • 89. Hensen L, Illing PT, Bridie Clemens E et al. CD8+ T cell landscape in indigenous and non‐indigenous people restricted by influenza mortality‐associated HLA‐A*24:02 allomorph. Nat Commun 2021; 12: 2931. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 90. Dixit R, Webster F, Booy R, Menzies R. The role of chronic disease in the disparity of influenza incidence and severity between indigenous and non‐indigenous Australian peoples during the 2009 influenza pandemic. BMC Public Health 2022; 22: 1295. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 91. Wieczorek M, Abualrous ET, Sticht J et al. Major histocompatibility complex (MHC) class I and MHC class II proteins: Conformational plasticity in antigen presentation. Front Immunol 2017; 8: 292. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 92. Shiina T, Hosomichi K, Inoko H, Kulski JK. The HLA genomic loci map: Expression, interaction, diversity and disease. J Hum Genet 2009; 54: 15–39. [DOI] [PubMed] [Google Scholar]
  • 93. Grant EJ, Josephs TM, Loh L et al. Broad CD8+ T cell cross‐recognition of distinct influenza A strains in humans. Nat Commun 2018; 9: 5427. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 94. Gonzalez‐Galarza FF, McCabe A, Santos E et al. Allele frequency net database (AFND) 2020 update: Gold‐standard data classification, open access genotype data and new query tools. Nucleic Acids Res 2020; 48: D783–D788. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 95. Solberg OD, Mack SJ, Lancaster AK et al. Balancing selection and heterogeneity across the classical human leukocyte antigen loci: A meta‐analytic review of 497 population studies. Hum Immunol 2008; 69: 443–464. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 96. Barker DJ, Maccari G, Georgiou X et al. The IPD‐IMGT/HLA database. Nucleic Acids Res 2023; 51: D1053–D1060. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 97. Szeto C, Lobos CA, Nguyen AT, Gras S. TCR recognition of peptide‐MHC‐I: Rule makers and breakers. Int J Mol Sci 2020; 22: 68. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 98. Hoof I, Peters B, Sidney J et al. NetMHCpan, a method for MHC class I binding prediction beyond humans. Immunogenetics 2009; 61: 1–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 99. Robinson J, Halliwell JA, Hayhurst JD, Flicek P, Parham P, Marsh SGE. The IPD and IMGT/HLA database: Allele variant databases. Nucleic Acids Res 2015; 43: D423–D431. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 100. Vita R, Mahajan S, Overton JA et al. The immune epitope database (IEDB): 2018 update. Nucleic Acids Res 2019; 47: D339–D343. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 101. Habel JR, Nguyen AT, Rowntree LC et al. HLA‐A*11:01‐restricted CD8+ T cell immunity against influenza A and influenza B viruses in indigenous and non‐indigenous people. PLoS Pathog 2022; 18: e1010337. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 102. Sant S, Quiñones‐Parra SM, Koutsakos M et al. HLA‐B*27:05 alters immunodominance hierarchy of universal influenza‐specific CD8+ T cells. PLoS Pathog 2020; 16: e1008714. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 103. Wu C, Zanker D, Valkenburg S et al. Systematic identification of immunodominant CD8+ T‐cell responses to influenza A virus in HLA‐A2 individuals. Proc Natl Acad Sci USA 2011; 108: 9178–9183. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 104. Pecetta S, Rappuoli R. mRNA, the beginning of a new influenza vaccine game. Proc Natl Acad Sci USA 2022; 119: e2217533119. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 105. UniProt Consortium . UniProt: The universal protein knowledgebase in 2023. Nucleic Acids Res 2022; 51: D523–D531. [DOI] [PMC free article] [PubMed] [Google Scholar]

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Supplementary Materials

Supplementary table 1


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