It has been over a decade since the completion of the Human Genome Project (HGP), genomic sequencing technologies have yet to become parts of standard of care in Canada. This study investigates medical oncologists’ (MOs) genomic literacy and their experiences based on their participation in a cancer genomics trial in British Columbia, Canada.n = 31, 52.5% response rate), who are actively involved in a clinical genomics trial called Personalized Onco-Genomics (POG). The authors also measured MOs’ level of genomic knowledge and attitudes about clinical genomics in cancer medicine.The authors conducted a survey of MOs from British Columbia, Canada . Forty-two percent of all MOs thought medical training programs do not offer enough genomic training. The majority of the respondents thought genomics will have major impact on drug discovery (67.7%), and treatment selection (58%) in the next 5 years. They also thought the major challenges are cost (61.3%), patient genomic literacy (48.3%), and clinical utility of genomics (42%).The findings show a low to moderate level of genomic literacy among MOs. MOs located outside the Vancouver area (the major urban center) reported less knowledge about new genetics technologies compared to those located in the major metropolitan area  contains supplementary material, which is available to authorized users. Physicians are increasingly working with genomic big data in their research and clinical work. Genomic sequence data helps scientists understand the molecular causes of diseases such as cancer , 2. SincThere are a number of challenges to the adoption of genome sequencing into routine practice such as doctors’ attitudes toward genomics, their level of genomic literacy, and experiences working with clinical genomic trials. One of the main challenges is a lack of familiarity and understanding of cancer genomics among healthcare professionals. Physicians often report their level of genomic knowledge is inadequate in order to make treatment decisions based on a patient’s genome sequencing information –8. The cThis is an early stage of adoption as genomics moves from scientist stakeholders to medical practitioners and the public . Put anoWe conducted a web-based survey from Nov 2015 to April 2016 with a sample of Canadian physicians who are medical oncologists. The Department of Research Ethics Review Board (DORE) at Simon Fraser University approved the study .We surveyed medical oncologists (MOs) involved in an experimental clinical genomics trial in the province of British Columbia, Canada. These specific MOs were chosen for the survey because they are investigators in a precision medicine clinical trial called Personalized Onco-Genomics (POG), led by clinicians and scientists at the British Columbia Cancer Agency (BCCA) in Canada . Therefore, our study sample is a relatively select group of oncologists who have experience working with clinical genomics and a higher exposure than other physicians. The cancer clinical trial enrols patients from across the province with incurable cancers that is primarily based on stages such as incurable stage II and IV advanced cancers, who have limited or no standard treatment options available . Each pn = 103) and almost 48% of the MOs in the region of British Columbia (n = 123). The response rate was 53%. Some MOs did not participate in the survey because they only had one patient enrolled in the program. Hence, they did not have enough experience working with POG to provide any useful inputs for the survey. Complex clinical genomics is not widely adopted at this historical point, so this survey captures a high number relative to the actual amount of doctor early adopters in Western Canada.We surveyed 59 MOs who enrolled patients in POG. This represents over 60% of MOs in the BCCA network  of MOs at POG. We gave the MOs in the pilot survey an opportunity to provide feedback into improving the survey. We incorporated the feedback from our pilot survey respondents and revised the survey protocol. We then validated the survey protocol with a clinician who is an expert in clinical genomics. We relied on her expertise to build content and scientific validity of the instruments and to ensure the instruments would make sense to their communicative cultural context. Overall, this survey is a co-construction between social scientists and medical experts including a genome scientist, a bioinfomatician, and three clinicians.After we developed the protocol, we piloted the survey with a small sample  to compare the differences of their mean scores. We also performed inferential statistics between gender, location, years of practicing oncology, and number of cancer patients as independent variables with the level of genomic knowledge and POG values as dependent variables. Due to the relatively small sample, instead of using n = 15) and male (n = 16) MOs (Table n = 13) work in Vancouver and the rest work outside Vancouver.The results showed almost equal gender distribution between female n = 5 and malF = 30.7, P < 0.0001).In the first section of the survey, we explored MOs’ perceptions and level of knowledge about genomics. We asked our participants to rate their level of knowledge based on a scale of 1 = “little knowledge”, 2 = “knowledgeable”, 3 = “very knowledgeable”, and 4 = “expert” on three different topics of genomic science and technologies: (1) basic genetic principles , (2) newer genetic/genomic technologies , and (3) the process of whole genome sequencing or WGS . The results showed the majority of the MOs ranked themselves as knowledgeable 57%) or very knowledgeable (33%)  about the topic of basic genetics principles  or think medical training (4–5 years) program did not sufficiently (42%) prepare students with enough genomic materials or training. Likewise, the majority of the MOs also thought there was not enough genomic training during their specialized medical training (54.8%), residency or fellowship (67.8%), or postgraduate medical training (58%).n = 14) considered it very important to improve their genomic knowledge. Another majority of our respondents (39%) only thought it was “important” to improve genomic knowledge. Even though none of MOs consider updating their genomic knowledge unimportant, 16% of the respondents (n = 5) considered improving genomic knowledge only somewhat important. In sum, the majority of MOs felt improving their genomic knowledge was highly important but this activity was not urgent.We also explored how important it is for MOs to improve their knowledge of clinical applications of genomic science and technologies by asking them to rate on a scale of 1 = “unimportant”, 2 = “somewhat important”, 3 = “important”, and 4 = “very important”. The data showed that 45% of our respondents . The MOs considered themselves to bear the primary responsibility for updating genomic knowledge (84%) followed by medical training and research institutions . Likewise, no respondents who work outside of Vancouver reported being very knowledgeable or expert in whole genome sequencing compared with those who work in Vancouver . The data showed the domain experts who reported the highest levels of knowledge about genomic technologies are located in Vancouver. Those located outside greater Vancouver, the major urban center in BC, reported lower levels of genomic knowledge on average.We found geographic location plays a role in levels of genomic knowledge in BC. MOs who work in Vancouver reported a higher level of knowledge about genomics on average than those who work outside Vancouver. More respondents who work outside Vancouver reported little knowledge about new genetics technologies compared to those who work in Vancouver  = 5.1, P < 0.0001).We asked the respondents to envision the impact of genomic technologies on their practice in the near future. The respondents rated seven items on a scale from 1 = “no impact”, 2 = “minor impact”, 3 = “major impact”. We found 67.7% Table . HoweverF = 8.03, P < 0.0001).We also asked the respondents about concerns they may have about expanding genomic science and technology into their practices on a scale of 1 = “unconcerned”, 2 = “somewhat unconcerned”, 3 = “somewhat concerned”, 4 = “very concerned.” The three most concerning issues our respondents have when applying genomic science and technologies into their clinical practices are cost (61.3%) , patient comprehension of genomic science and technologies (48.3%) , and clinical usefulness of genetic data (42%) -accredited events are potential tools that can help MOs update their knowledge of genomic sciences and technologies. Furthermore, health information technology systems and other online, point-of-care tools are innovative and effective educational resources for physicians, which thereby results in better utilization of genetic information in clinical practices. For example, social media platforms such as Twitter and YouTube are low-cost and wide-reaching platforms for interactive educational tools.The results suggested MOs are looking for alternative sources to learn about genomics. MO thought that a local government funding agency, Genome British Columbia, should spend more funding on research and projects that can enhance their genomic knowledge and alleviate their genomic educational needs. Educating professionals and the public is a goal of Genome BC, so this would be a strategic opportunity to focus on. Furthermore, the data also indicated MOs collaborated with POG to find effective treatment options and develop clinical genomic technologies at the population level. On the basis of the educational deficiencies identified in this survey, the POG team has initiated applied cancer genomics symposiums for the physicians of BC to address some of these educational gaps.The MOs in our sample showed a mix of attitudes toward the use of genomic technologies in clinical practices. The findings on the impact of genomics on oncology practices Table  and concIn the global era of rapid information movement on the Internet, there is a tendency to think geography is not a particularly important challenge in information gathering and learning. However, sociologists of globalization find geography matters because a central hub of innovation can attract capital, experts, and infrastructures for the development and diffusion of innovation. Consistent with this research we found geography plays an important role in variations in MOs genomic literacy. Respondents who work outside Vancouver reported lower levels of genomic knowledge than those who work in the metropolitan center. Vancouver is the central hub and a milieu of innovation for professional and educational networks connecting different medical stakeholders with medical skills and expertise. POG is an interdisciplinary group of oncologists, pathologists, bioinformaticians, bioethicists, and health economists. One of the ten principles for good interdisciplinary team work is communications strategies and structures . ProximiThe main potential limitations of this study are the raw numbers of participants and reliance on some self-report item, namely the instruments for measuring levels of genomic literacy. The sample size limited our ability to apply more inferential analyses such as logistic regression models to identify more associations between our variables. Other studies have employed tests to measure genomic literacy. We considered this option but did not pursue it because of the other goals of the survey and the limited time respondents would most likely spare to complete it. However, a strength of the study is the response rate. We surveyed 54% of all MOs in POG, which represents almost 30% of all working MOs in BC in the survey population. Fifty-four percent is a very good response rate for a survey and generalizable to the study population. Both the response rate and the sample population relative to the overall population provide a solid foundation to build on for future studies. Other strengths of the study include the rigorous, multi-step process to construct and validate the questionnaire. We consider this survey a co-production between social scientists and medical domain experts. We adapted existing items and measures from other questionnaires examining genomic knowledge of physicians , 21. We A recent report from the Secretary’s Advisory Committee on Genetics, Health, and Society (SACGHS) also pointed out a lack of basic genetic understanding among many health professionals, which in turn limited the adoption of genomic technologies into clinical practices . We suggAs POG is a self-funded clinical trial through BCCA, we did not examine the impact of the pharmaceutical and biotechnology industry on the clinical practices at POG. Future research could investigate the impact of the pharmaceutical industry on cancer clinical trials and any ethical issues including transparency that could be derived from this conflict of interests. Finally, our findings shed light on the current level of genomic literacy among physicians in Western Canada. Physicians who locate outside metropolitan areas tend to have lower genomic knowledge than those who work in the city. More genomic training and workshop should be offered in regional areas to physicians who need more educational interventions. Initiatives like POG play a critical role in the education of MOs and the integration of big data clinical genomics into cancer care.


EDUFLUVAC consortium, a European Union funded project coordinated by the European Vaccine Initiative, and the National Institutes of Health/National Institute of Allergy and Infectious Diseases, USA. The workshop audience agreed that it was not possible to establish a single immunoassay for “universal” influenza vaccines because the current approaches differ in the vaccines' nature and immunogenicity properties. Therefore, different scientific rationales for the immunoassay selection are required. To avoid dilution of efforts, the choice of the primary evaluation criteria  should drive the effort of harmonisation. However, at an early phase of clinical development, more efforts on exploratory assessments should be undertaken to better define the immune profile in response to immunisation with new vaccines. The workshop concluded that each laboratory should aim towards validation of the appropriate immunoassays used during the entire process of vaccine development from antigen discovery up to establishment of correlates of protection, including the different steps of quality control (eg potency assays), animal studies and human clinical development. Standardisation of the immunoassays is the ultimate goal, and there is a long way to go.The development of broadly reactive influenza vaccines raises the need to identify the most appropriate immunoassays that can be used for the evaluation of so‐called universal influenza vaccines and to explore a path towards the standardisation of such assays. More than fifty experts from the global influenza vaccine research and development field met to initiate such discussion at a workshop co‐organised by the  Because of continuous antigenic changes of circulating influenza viruses, the seasonal influenza vaccine composition has to be updated regularly.A significant advance in human infectious disease research would be the development of a new generation of influenza vaccines that induce a robust, broadly protective immune response, not only to drifted variants of seasonal influenza viruses, but preferably also to potential pandemic strains. Consequently, the development of such “universal” influenza vaccines has become a worldwide public health priority in both industrialised and low‐ and middle‐income countries.A large number of academic, public or private organisations applying different approaches are developing such vaccines that are currently at various stages of development, from pre‐clinical evaluation to clinical trials.The European Union funded EDUFLUVAC consortium, coordinated by the European Vaccine Initiative, co‐organised a workshop on the standardisation of immunoassays for “universal” influenza vaccines together with the National Institutes of Health/National Institute of Allergy and Infectious Diseases, USA. The main objectives of the workshop, held on 18‐19 June 2015, were (i) to review the immunoassays used to assess broadly reactive influenza vaccines; (ii) to explore a path towards standardisation of these assays; and (iii) to enhance networking and collaboration between the different actors interested in the development of novel influenza vaccines.http://www.edufluvac.eu/node/1117.The workshop agenda, list of participants and presentations are published on the EDUFLUVAC website: 22.1The immune response induced by influenza vaccines has been measured traditionally by three classical immunoassays: haemagglutination inhibition (HI), single‐radial haemolysis (SRH) and virus neutralisation (VN) assays. The HI assay detects antibodies that bind to the viral haemagglutinin and prevent the virus‐mediated agglutination of erythrocytes. There is a consensus, although not universally accepted, that an HI antibody titre of 40 correlates with a 50% reduction in the risk of contracting influenza2The SRH assay measures antibodies that bind to the influenza virus and fix complement 2.2Neutralising antibodies are generally accepted as primary mediators of immunity against influenza virusCollaborative studies have shown that interlaboratory variability of VN assays can be considerable; the use of antibody standards can reduce itAs opposed to the HI assay, no correlate of protection has been established for the VN assay. In a recent household transmission study, microneutralisation titres ≥ 40 were associated with 49% protection against H3N2 infectionAs the three main serologic assays HI, VN and SRH detect different populations of antibodies, different degrees of correlation between these assays can be observed.2.3™ was shown to achieve good correlation with expected titres in validation experiments. Moreover, there was good agreement between expert human readers and the automated reader. A high‐throughput machine is currently under development.Reading of haemagglutination and HI plates by operators is one cause of the variability of the HI assay. Different automated imaging analysis systems are currently under development and could standardise the reading of HI plates. The plate reader Cypher One3Although antistalk antibodies can be produced after seasonal influenza vaccination, they comprise only a small proportion of total anti‐HA antibodies and are not efficiently boosted even after routine annual seasonal vaccination. However, anti‐HA stalk antibodies that have been isolated from humans (and mice) have been found to be cross‐reactive and neutralising between different subtypes and occasionally between group 1 and group 2 haemagglutininsELISAs can be used to detect total antistalk antibodies as well as heterosubtypic cross‐reactivity. The laboratory at Icahn School of Medicine at Mount Sinai has developed ELISAs using chimeric haemagglutininsViruses generated via reverse genetics, containing chimeric haemagglutinins with mismatched neuraminidase genes, can also be used in anti‐HA‐stalk‐specific neutralisation assays. Plaque reduction neutralisation assays are the preferred format currently. Other microneutralisation assays are carried out in 96‐well format using nucleoprotein (NP) staining, haemagglutination assay and cytopathic effect end point read‐outs.3.1An advantage of the ELISA is that a wide range of antigen preparations can be used as target antigens. Such preparations can be whole‐inactivated virus, subunit vaccines or purified HA1; therefore, antibodies towards specific regions or formulations of interest can be detected. In addition, IgG subclasses and immunoglobulin isotypes can be quantified in serum by the use of subclass/isotype‐specific conjugated secondary antibodies. ELISAs allow measuring the actual amounts of immunoglobulin, and the use of standards allows good intra‐ and interlaboratory standardisation. The ELISA method is also suitable for high throughput and is cost effective.Comparison between HI assays and ELISAs has shown some correlation; however, the mean fold increase in HI titres is usually higher than in ELISA IgG titres. It should be noted that antibodies detected in HI assays comprise only a minor fraction of the total IgG antibody response. ELISA data were also compared to VN assay results in a clinical study of a non‐adjuvanted H5N1 vaccine candidate, showing correlation between HA‐specific IgG levels and VN titres4Some reports indicate that vaccine‐induced immune mediators may enhance disease upon subsequent influenza infection. Epidemiological observations have suggested that pre‐existing anti‐H1 antibodies were associated with enhanced disease (ED) in some people following infection with pandemic A(H1N1) virus in 2009These results have relevance for assessing “universal” vaccines that have been designed to target the HA2 region. Studies should include screening for possible vaccine‐induced disease enhancement. Relevant in vitro assays include those measuring Fc‐mediated influenza virus uptake using relevant cell lines . Proposed read‐outs are plaque assays or anti‐NP immunostaining, or real‐time PCR for viral RNA quantification in high‐throughput assays. In vivo studies in pigs can also be used to assess vaccine‐induced disease enhancement.4.1An alternative approach to current serological assays is the use of protein microarrays that can simultaneously measure antibody responses to a variety of virus strains and subtypes while requiring only small amounts of test serum. The protein array method involves HA1 proteins of different influenza subtypes spotted in triplicate onto nitrocellulose pads on glass slides. The serum samples are then added in twofold serial dilutions, and a fluorescently conjugated detection antibody is used to visualise positive signalsThe protein array was successfully applied using pre‐ and post‐H1N1pdm09 human seraFuture work should include more comparative experiments between the protein array and biological assays to assess the functional relevance of the protein array data.5Traditionally, anti‐NA assays have used the thiobarbituric acid (TBA) method. To reduce the use of highly hazardous chemicals, a mini‐TBA assay has been establishedThe ELLA method consists of coating plates with fetuin, a substrate for NA, and adding test serum and virus and/or NA. Active NA cleaves the terminal sialic acid residue from the fetuin, leaving an exposed galactose molecule. Peanut agglutinin (PNA) conjugated to horseradish peroxidase is then added whereupon the PNA binds exposed galactose molecules. Results can be determined as 50% end point titres. ELLA and mini‐TBA assay results are comparable.Variables within the ELLA assay include the source of the NA, for example purified NA, detergent disrupted virus or whole virus containing a mismatched HA. It may be necessary to heat treat the serum in order to reduce non‐specific inhibition. The amount of virus/NA added per well needs to be predetermined by titration. Ideally, this part of the assay needs to be standardised between laboratories.The Consortium for the Standardisation of Influenza Seroepidemiology (CONSISE) is carrying out work on standardisation of the ELLA assay. The aim is to identify key variables that lead to interlaboratory and interassay variability and to evaluate a serum standard. Results to date showed that the antigen dilution appears to be critical; lower titre results were generated if too much antigen was added. Use of a standard serum improved comparability, at least for anti‐N1 specific responses. Updating the assay buffer to stipulate a pH that optimises NA activity can further improve the method.Alternative anti‐NA serological assays, in addition to the established TBA and ELLA methods, are presented in Table 6Both T and B cells play a role in the generation of protective immune responses to influenza vaccines. CD4 T cells are needed for CD8 T‐cell memory as well as high‐affinity, antigen‐specific B‐cell development. Although influenza‐specific CD4 and CD8 T cells are generated against conserved influenza antigens/peptides, they do not appear to be generated at a level that is enough to afford protection year after year. However, pre‐existing memory CD4 T cells can enhance the early antibody response.Human studies have shown a link between CD4 specificity and help for the neutralising antibody response. For example, people immunised with split H5N1 vaccines followed by immunisation with a homosubtypic heterologous H5N1 vaccine generated increased neutralising antibody titres as compared to people that were not primed, the majority showing levels above the predicted protective threshold of 1:40It is likely that only a subset of the available memory CD4 T cells will be stimulated to make an effective response during vaccination. It should also be noted that some subsets may antagonise the response.Peptides are available from Biodefense and Emerging Infections (BEI) Research Resources Repository/NIH that can be used in in vitro cellular assays. The need to focus on immunodominant peptides is expected as there are other regions of the influenza proteome that do not appear to stimulate adequate T‐cell responses.Follicular helper T cells have been found in the blood which may be a correlate of influenza antibody responses6.1The enzyme‐linked immunosorbent spot (ELISpot) assay is used to quantify the numbers of antigen‐specific cytokine secreting cells after antigen stimulation. Typically, IFNγ is used as a measure of activated T cells. However, this assay is flexible and any immune cell types (T cells and B cells) and cytokines can be measured if appropriate detection antibodies are available. The procedure involves incubating antigen‐stimulated lymphocytes in 96‐well plates coated with cytokine‐specific antibody. Secreted cytokines are then detected using a biotinylated antibody, alkaline phosphatase‐conjugated streptavidin and a colour‐forming substrate to enable the visualisation of coloured spots on the plate.ELISpot is a suitable assay for measuring T‐cell responses to influenza and has been used in a number of published studies that have investigated the T‐cell response during natural infection as well as after vaccination. Interestingly, studies have shown that H5N1‐reactive memory T cells are present in populations where H5N1 is not prevalentAlthough the ELISpot assay performance is straightforward, there are a number of variables that must be considered for assay standardisation both within and between laboratories, for example peripheral blood mononuclear cell (PBMC) preparation procedures, reagents, incubation periods and the stimulating antigen used. It is also necessary to use clinical trial data and human subjects in order to ascertain correlates of protection.6.2The intracellular cytokine staining (ICS) assay can be used to evaluate T‐cell immunity and correlates of protection for influenza vaccines. This assay is currently being standardised through the European Union funded UNISEC project.The ICS assay measures multiple cytokines and lymphocyte subsets and is designed to maximise the amount of data from the limited cell numbers available during clinical trials. This collection of broad data aims to ensure that the currently unknown relevant mechanisms of cell‐mediated immunity and associated correlates of immunity are likely to be captured. The assays for influenza are adapted from those established for the evaluation of HIV vaccines in clinical trialsIn the ICS assay, common peptides between subtypes could be used to measure potential universality. Currently, most available peptide pools for influenza are optimised for CD8, rather than CD4 cells.With regard to standardisation, there is an element of subjectivity introduced by the operator when analysing flow cytometry data, for example the positioning of the gates around the cell populations of interest. This may warrant an automated analysis process.Seeing as the influenza virus infects the lungs and that a non‐highly pathogenic influenza virus does not spread into the blood, it was suggested that it may be valuable to measure early responding T cells in the lungs rather than or in addition to PBMCs. Measuring neutrophils and natural killer (NK) cells may also be of interest. The kinetics of cytokine production should be considered when establishing this type of assay as cytokine production varies over time. Thus, time points post‐vaccination/infection need to be standardised and verified. It should be noted that the ELISpot assay can detect cytokine producing cells from samples taken over a long time because the cytokines accumulate in the cell.6.3“Universal” and novel influenza vaccines frequently aim to target the cytotoxic T‐cell (CTL) response, and therefore, relevant assays are needed. It has been shown that CTL responses can be a valid correlate of protection against symptomatic influenza diseaseCTLs recognise infected cells through T‐cell receptor interaction with major histocompatibility complex (MHCI) molecules coated with peptides, followed by target cell killing . Activated CTLs also produce cytokines such as IFNγ and TNFα. A summary of established CTL assays is presented in Table 6.4The antibody‐dependent cellular cytotoxicity (ADCC) assay is a relatively new method to determine the combined antiviral effect of antibodies and Fc receptor‐bearing effector cells . The breadth of the antibody response detected was extended beyond classical neutralising (HI and VN) antibodies to antibodies recognising all viral surface proteins  by the ADCC assay. Different ADCC methodsSeveral potential assay improvements could be considered: use of target cells stably expressing antigens; replacement of NP detection by reporter gene (eg fluorescent antigen‐transfected target cells (FATT‐CTL), bioluminescent reporter gene); replacement of primary NK cells by an NK cell line; and use of methods to use BAL fluids in ADCC. The biological relevance of ADCC antibodies and the potential use of ADCC as a correlate of protection are currently under investigation.6.5Antibody‐dependent respiratory burst (ADRB) assay is an assay to measure the combined  effects of antibodies and neutrophilsThe relevance of the ADRB for influenza is still being explored, and a number of issues remain to be investigated; these include the following: correlations between formats using plate‐bound antigen and those using infected cells and the use of a reference standard on every plate and correlation with other  assays.7In summary, establishing “universal” immunoassays for “universal” influenza vaccine(s) is challenging if the vaccines differ significantly in their nature and immunogenicity properties. Therefore, different scientific rationales regarding the decision of the immunoassays are required for the development of different “universal” influenza vaccines. To avoid dilution of efforts, the choice of the primary evaluation criteria  should drive the effort for harmonisation. However, at an early phase of clinical development, more efforts on exploratory assessments should be undertaken to better define the immune profile.Steps towards standardisation of immunoassays between laboratories are the harmonisation of assay protocols, use of common standards and regular proficiency assessment of laboratories. Although the harmonisation of assay procedures might be feasible, standardisation of critical reagents will be more difficult, if not impossible, primarily due to local sourcing of reagents. Harmonisation of methods does not always lead to improved agreement between laboratories, as demonstrated for the HI assayEach laboratory should aim to appropriately validate the immunoassays used during the entire process of vaccine development from antigen discovery up to establishment of correlates of protection, including the different steps of quality control (eg potency assays), animal studies and clinical development. Global standardisation of the immunoassays is the ultimate goal; however, there is still a long way to go.The CONSISE consortium, where more than 100 members from 40 countries share study and laboratory assay protocols and other information on the Internet with free access, is a good example of efforts towards the standardisation of immunoassays. CONSISE developed new consensus protocols for the HI and VN assays, and member laboratories have aligned their assay parameters to the consensus protocols.There are different levels/types of standards:1‐  WHO International Standards—highest level2‐  National/regional/pharmacopoeial standards3‐  Working reagents4‐  In‐house standards5‐  Run controlsPossible approaches towards harmonisation of immunoassays could be the establishment of antibody/serum standards in case the vaccine candidate targets antibody responses. However, they might need to be product‐specific if particular epitopes are targeted. Standards for specific biological analytes (eg cytokines) can also be used. Cell standards for cell‐mediated immunity assays have been made in the past and more could be generated.Proficiency testing and external quality assessment are important for the evaluation of the process of harmonisation and standardisation. Testing a laboratory's quality system with samples of known, but undisclosed content will give an overview of the laboratory's performance and will provide a comparison with that of other laboratories.A clear need for further collaboration, networking and international communication regarding the harmonisation of immuno‐assays was identified, and CONSISE could be the venue for these activities. The standardisation should be initiated early, before methods drift too much. The European‐American partnership established during the organisation of this workshop was recognised as a clear asset in this direction and will be sustained.


Megavoltage CT (MVCT) simulation on the TomoTherapy Hi·Art system is an alternative to conventional CT for treatment planning in the presence of severe metal artifact. StatRT is a new feature that was implemented on the TomoTherapy operator station for performing online MVCT scanning, treatment planning and treatment delivery in one session. The clinical feasibility of using the StatRT technique and MVCT simulation to palliative treatment for a patient with substantial spinal metallic hardware is described. A patient with metastatic non‐small‐cell lung cancer involving the thoracic spine underwent conventional kilovoltage CT simulation. The metal artifact due to stainless steel spine‐stabilizing rods was too severe for treatment planning, despite attempts to correct using density override. The patient was then re‐scanned using MVCT on a tomotherapy unit. Plans were generated using both StatRT and conventional tomotherapy planning (Tomo plan) with different settings for comparison. StatRT planning ran a total of five iterations in a short planning window (10–15 min). Two Tomo plans were generated using: (1) five iterations in the “full scatter” mode, and (2) 300 iterations in the “beamlet” mode. It was noted that the DVH of the StatRT plan was almost identical to the Tomo plan optimized by the “full scatter” mode and the same number of iterations. Dose distribution analysis reveals that these three planning methods yielded comparable doses to heart, lungs and targets. This work also demonstrated that undermodulation can result in a high degree of thread effects. The overall time for the treatment process  decreases from hours to around 40 minutes using the StatRT procedure. StatRT is a feasible treatment‐planning tool for physicians to scan, contour and treat patients within one hour. This can be particularly beneficial in urgent palliative treatments.Conflict of Interest Statement: James S. Welsh has received honoraria for speaking for TomoTherapy, Inc.; Yi Rong has received travel sponsorship for TomoTherapy, Inc.PACS numbers: 87.55.D‐, 87.57.C‐ Streak artifact is one of the most significant challenges in the application of diagnostic kVCT simulation. It can be caused by one or more effects such as beam hardening, scattered radiation, poor signal‐to‐noise ratio, aliasing and object motion, which may result in significant bright and dark streaks on the reconstructed image. Metals can also cause streak artifacts, the main cause of which is the high attenuation and scattering properties of metal in diagnostic X‐ray energy range. A direct solution is to use less‐attenuating materials  or devices with smaller scatter cross‐section.(–) However such case‐by‐case solutions are not ideal for clinical practice. Promising mathematical algorithms were also proposed for artifact reduction on diagnostic CT images. But manufacturers have not yet implemented them for clinical use. In radiotherapy application, metal artifacts greatly limit the usefulness of kVCT images for contouring the target as well as organs at risk. This can be overcome by megavoltage CT (MVCT) imaging. It has been observed that compared to kVCT, MVCT images exhibit considerably reduced artifacts in metal implants such as hip implants, surgical clips and dental fillings, and provide good agreement to measurements in dose prediction. Although MVCT scans are inferior in soft tissue contrast and spatial resolution compared to those of kVCT scans, they can be used for patient alignment and treatment planning as an alternative for the situations when kVCT scans are not available or are compromised by artifacts.(–)The use of computed tomography (CT) in radiation therapy has been largely increased due to the essential role of the accurate 3D anatomical information and the attenuation coefficient data that allow tissue heterogeneity corrections in the treatment planning process. Though the vastly improved kilovoltage CT (kVCT) scanners have 3D imaging capabilities and have reduced the scanning time, metallic artifacts persist in the present generation of CT. CT artifacts have many causes including patient movement, the limitation of the detector, the image reconstruction method, and the presence of high‐density materials such as metal in or on the patient.1 Stre This allows better tissue sparing and possibly better tolerance of the treatment.StatRT is a new software package for the helical TomoTherapy Hi·Art  treatment planning system and is particularly important in time‐sensitive cases. The software is designed to manage scanning, planning and delivery in a timesaving manner. Conventionally, tomotherapy offers three options for plan optimization on the planning station: “TERMA”, “Full Scatter”, and “Beamlet”. The “TERMA” mode only accounts for the total energy released per unit mass (TERMA) of each beamlet during the process of optimization, without taking into account the transportation of charged particles and scattered particles. Thus, it is the fastest approach of the three, but not the most accurate. The Full Scatter mode calculates both TERMA as well as electron transportation in each iteration of optimization. It is the slowest but most accurate mode for dose optimization. The Beamlet mode allows users to “batch” beamlets for calculating dose contributions from each beamlet and optimize beamlet weights in each iteration with the real‐time display of the dose volume histograms. Thus, it is the most common option for conventional tomotherapy optimization. With StatRT, plans are still calculated using the same photon dose calculation engine, which is the convolution/superposition algorithm, and delivered in a helical IMRT manner to achieve highly conformal dose distributions. The differences from the conventional procedures are that the Full Scatter mode is the only option for plan optimization and all steps – including image acquisition, target and organ delineation, optimization, dose calculation and plan delivery – are performed on the operator station. It should eliminate the time for the physical transfer of patients from simulation to treatment and the data transfer from imaging to planning. An emergency palliation can be efficiently initiated with the StatRT approach on the operator station. Also, it offers operating ease as the entire process can be managed on a single computer, the Hi·Art treatment system's operator station. It is found that the dose distributions from StatRT are much more conformal than the traditional palliative techniques.,19 THowever, there are several aspects yet to be studied, such as the shortcomings of this approach, the appropriate parameters for scanning and planning, and the timelines for the first fraction. The present planning study aimed to establish a clinical workflow and feasibility for performing the StatRT palliative treatment. The reported case is also a typical example where MVCT images are the superior option due to the presence of metal artifacts in kVCT. The treatment quality of StatRT is also compared with the conventional tomotherapy planning technique on a planning station (Tomo plan) in order to determine the advantages and disadvantages of both approaches.A 72‐year‐old man was initially diagnosed and treated for stage one bronchoalveolar adenocarcinoma of left lung in 2006. Two years later he presented with back pains. CT images from a Philips Brilliance 40‐channel CT scanner  revealed a large lytic lesion at T10, consistent with metastatic disease. A bone scan showed radiotracer activity at T10. He underwent surgical intervention for what appeared to be impending spinal cord compression, specifically undergoing decompression of the spinal cord with laminectomy of T6 and T10 and a component of T11 with posterior instrumentation from T7 through L1 using stainless steel rods. The patient was prescribed for a course of palliative RT for the metastatic non‐small‐cell lung cancer, with the prescription regimen of 30 Gy in 10 fractions directed to T8 through T12. In this case, the MVCT scan took about nine minutes (around 520 seconds) using a “normal” grid and slice selection from −20 cm to +20 cm, with the central slice being the virtual setup isocenter, giving a total scan length of 40 cm. As we gained experience, we found that a shorter (around 7 minutes) scan, from −15 cm to +15 cm is often sufficient to cover most of the tumor sites. The artifacts could not be completely eliminated in the MVCT image but were substantially reduced in comparison to kVCT. The patient was sent home after MVCT acquisition and came back for a regular treatment using an approved and verified tomotherapy plan that was done in a conventional way. That is to say, the MVCT image set was exported to the Pinnacle planning system for contouring of the planning target volume (PTV), heart and lungs. It was then sent back to tomotherapy for conventional tomo planning using the Beamlet mode and 300 iterations(Tomo Plan 1). In our clinic, the image‐value‐to‐density table (IVDT) for MVCT scans was periodically verified and also acquired every time prior to a MVCT planning.Significant metallic artifacts due to the stainless steel spine stabilizing rods were observed on the initial CT images For a genuine clinical emergency with the patient scheduled to be treated immediately using the StatRT, the DQA would be conducted after the first fraction. DQA is fully integrated into the planning software, and it can be delivered from the operator station to compare with the planar chamber dose measurements using the OmniPro‐I'mRT MatriXX system  with the 2D ionization chamber array.,22±3%/3 mm between ion chamber/film measurements and dose calculation on the MVCT image set of the “cheese” phantom with density heterogeneity. The choice of the Beamlet mode and the high level of the intensity modulation resulted in longer gantry period and thus a longer treatment time (by 46%) for Tomo Plan 2 compared to the other two plans  iterations in optimization. Comparable DVHs and dose distributions were observed in the Tomo plan using the “Full Scatter” optimization setting. The StatRT technique is beneficial to the patients in need of palliative treatment by reducing the pain from being moved around.Palliative radiotherapy is generally appropriate when there are slim chances of cure and the clinical aim is for pain control or other symptomatic relief. During palliative radiotherapy it becomes important to efficiently synchronize the scanning, treatment planning, contouring, calculations or simulation‐associated statistical data, and treatment delivery in an efficient manner. StatRT is an extended utility on tomotherapy for urgent situations when time is a significant constraint. This efficiency is invaluable for facilities that have only one tomotherapy unit or circumstances in which urgent palliation is considered desirable. With the current toolset, it is possible to scan, plan and deliver radiotherapy treatment within one hour in comparison to the ordinary situation that takes hours of waiting time between simulation and treatment. A shorter planning window used in the StatRT plan still allows at least five iterations of optimization, which generates plans with clinically acceptable quality. Yet thread effects are distinct without sufficient iterations of optimization. Using recommended pitch factors (0.86/n) helps in minimizing the them.24 Nev Generating a palliative plan takes much less time on a conventional linear accelerator than the procedure described above. The portal imager or a conventional kilovoltage X‐ray simulator is normally used where the radiation oncologist specifies field borders and designs beam blocks to isolate the tumor from critical sensitive organs. However, in our facility only one tomotherapy machine is available and the volumetric CT image is required for treatment planning. This increases difficulties in palliative treatment especially for a case as described in this study. It is noted that the absorbed dose in the soft tissue regions affected by the high‐density artifacts is higher in the kVCT image than the MVCT‐based recalculation. The dose differential can be as large as 15%. Due to the mild appearance of the metallic streak artifacts, MVCT provides better image quality in the region surrounding the metal hardware. The MVCT image reveals sufficient information of the tumor and normal anatomy for patient repositioning and treatment planning. It is worth noting that recent studies show output instabilities over time of the tomotherapy imaging beam and the consequent dose effect can be as large as 3%. Therefore, our protocol requires acquisition of a new IVDT prior to every MVCT scans for dose calculation purpose.Typically, AP‐PA sets of beams are used for such a palliative treatment since the intended doses can be achieved with a homogenous dose distribution.26 GenIt might be difficult for patients with significant pain to remain in the same position for more than 30 minutes; thus we recommend a second MVCT scan prior to the treatment in order to verify the target position. The time for this additional MVCT scan was not included in the total time mentioned above. We would expect another 5–10 minutes, depending on the length of the target, the choice of the scan mode and the difficulty in registration. The entire procedure takes 40 minutes to one hour, which limits the usage of the tomotherapy unit for other patients. It is also important to coordinate the schedule with all personnel involved, including physician and medical physicist.In situations where conventional kVCT is unable to provide accurate anatomical information due to interference from high‐density materials such as metal, MVCT‐based planning can be advantageous. With the successful integration of MVCT on the workstation, tomotherapy offers two options for treatment planning using either Tomo plan or StatRT plan. Satisfying essentially all of the treatment planning objectives, the StatRT technique has proved to be an excellent solution for combining image acquisition, treatment planning and dose delivery in one session when time is the limiting factor. The dose distribution from StatRT appears equivalent to a Tomo plan with a limited number of iterations. It also appears comparable to a Tomo plan with large number of iteration except for the presence of a noticeable “thread effect” at high isodose levels. In conjunction with MVCT imaging, StatRT is a feasible tool for physicians to scan, contour and treat patients within one hour, and can be beneficial when there are severe imaging artifacts in the target area.


Drosophila melanogaster, a model species for the study of sexual selection, indirect genetic effects (IGEs) of general social interactions can influence female mate choice behaviors, but the potential impacts of IGEs associated with mating experiences are poorly understood. Here, we examined whether the IGEs associated with a previous mating experience had an effect on subsequent female mate choice behaviors and quantified the degree of additive genetic variation associated with this effect. Females from 21 different genetic backgrounds were housed with males from one of two distinct genetic backgrounds for either a short (3 hr) or long (48 hr) exposure period and their subsequent mate choice behaviors were scored. We found that the genetic identity of a previous mate significantly influenced a female's subsequent interest in males and preference of males. Additionally, a hemiclonal analysis revealed significant additive genetic variation associated with experience‐dependent mate choice behaviors, indicating a genotype‐by‐environment interaction for both of these parameters. We discuss the significance of these results with regard to the evolution of plasticity in female mate choice behaviors and the maintenance of variation in harmful male traits.Female mate choice is a complex decision‐making process that involves many context‐dependent factors. In  Although these studies are a good start, researchers have only tested for GxEs in mate choice by manipulating abiotic environmental factors. As such, we set out to directly test whether the IGEs associated with social experiences can interact with genotype to produce individual variation in female mate choice behaviors.In addition to social experiences, an individual's behavioral expression may be shaped by the specific genotypes of interacting conspecifics via indirect genetic effects . Furthermore, as 22.1Ives (hereafter “IV”) population. This population originated from a sample of 200 females and 200 males collected in South Amherst, MA, USA, 1975. Since 1980, this population has been cultured at a large census size  on nonoverlapping generations and standardized protocols  to a density of 100 eggs/vial. These oviposition vials become the natal vials for the next generation of flies.The flies used in our experiments were derived from the large outbred wild‐type y, f], and are homozygous for translocated autosomes [T rdgC st in ri pPbwD]. The resulting males in each clone line all possess one full haplotype originating from the base IV population maintained in an unrecombined state and with the translocated autosomes inherited from their CG mother. To express the haploid genome in a male hemiclonal state, clone males are crossed with virgin females from the “DX‐IV” population (which possess the “double‐X” chromosome and autosomes originating from the IV population). To express the haploid genome in a female hemiclonal state, clone males are crossed to virgin females from the base IV population. Ultimately, all target hemiclones resulting from one of these crosses posses one haplotype identical to all other individuals in the line, and one randomly inherited haplotype.From the IV population, we established 26 male clone lines using cytogenetic cloning techniques  from each of the 21 clone lines that were not used to generate either the low‐ or the high‐harm males. From each of these lines, we obtained 24 female hemiclones by crossing clone males to virgin IV females  in order to observe their subsequent mate choice behaviors  for ~4 hr. Videos files were analyzed using the program VideoFly  into individual subchambers, and left the third subchamber empty  a female spent associating with males (both high‐ and low‐harm) compared to the entire duration of the assay. Preference was defined by the amount of time (number of frames) a female spent with high‐harm male compared to the amount of time spent with either male. Our decision to use “high‐harm” males as the preference numerator was arbitrary and the conclusions and implications of these results remain the same if we had instead used the “low‐harm” males at the numerator in our analyses.lme4 package  chi‐square tests implemented in the h Manly,  whereby lmodel2 package  that was spent associating with the high‐harm male in the male choice chamber. We then calculated the correlation between these two variables, and obtained the standardized major axis (SMA) slope , with females that had been mated to “low‐harm” males showing greater levels of association with males than those females who had been mated to “high‐harm” males  nor for the interaction between length and mating treatment . When considering the random effects, we found that while clone line, the interaction between mating treatment and clone line, the interaction between length treatment and clone line, and the interaction between all three are statistically significant, they are of relatively small effect size with each only accounting for less than 2.5% of the observed phenotypic variation in the amount of time females spent associating with males . Upon analysis of the random effects, clone line, the interaction between clone line and length treatment, and the three‐way interaction were not significant factors and explained none of the observed variation. However, the interaction between clone line and mating treatment was significant and explained ~9.72% of the observed phenotypic variation in female preferences , we found no significant effects of either of our fixed effects  or their interaction. However, we did find a significant interaction between female genotype and male experience which accounted for ~9.5% of all the observed phenotypic variation Figure a. When t4.3Our study's results have implications regarding the evolution of plasticity in mate choice behaviors and female resistance to male harm. Rodríguez et al.  proposed5D. melongaster. We also identified an interaction between mating experience and individual genotype (a GxE effect) on interest in males and female preferences, suggesting that a female's preference and interest in males is highly plastic. Our results offer new insight into the maintenance of variation in male traits and the evolution of plasticity in female mate choice behaviors.In this experiment, we identified the IGEs associated with mating experience as a novel source of variation in female mate choice behaviors in the model species None.https://doi.org/10.5061/dryad.6008n.The data and codes have been deposited to Dyrad:  Click here for additional data file.


CRC) survivors with and without Lynch syndrome (LS). Participants were case–case‐matched CRC survivors with (n = 75) or without (n = 75) LS . Participants completed a mailed questionnaire assessing demographics, clinical characteristics, healthcare utilization, psychosocial variables, and provider satisfaction. LS CRC survivors reported lower provider satisfaction scores on three subscales of the Primary Care Assessment Survey: communication , interpersonal treatment , and knowledge of the patient . Among LS CRC survivors, predictors for mean communication and trust subscale scores were location of treatment and socioeconomic status. Higher mean depression scores also were associated with trust, while social support predicted higher satisfaction with communication. Sporadic CRC survivor satisfaction is driven largely by age  and patient anxiety (communication), while seeing a provider more often was associated with increased satisfaction with knowledge of the patient. LS CRC survivors reported lower levels of provider satisfaction than sporadic CRC survivors. LS survivors who received care at The University of Texas MD Anderson Cancer Center, a comprehensive cancer center (CCC), reported higher satisfaction than those receiving care at other institutions. Depressive symptoms and socioeconomic status may impact provider satisfaction ratings. Exploration of other potential predictors of provider satisfaction should be examined in this population. Additionally, further research is needed to examine the potential impact of provider satisfaction on adherence to medical recommendations in LS CRC survivors, particularly those being treated outside of CCCs.This study evaluated provider satisfaction in a sample of colorectal cancer ( Patients diagnosed with cancer often have increased healthcare needs, which may result in higher expectations of care. A greater understanding of predictors of patient satisfaction with healthcare providers (HCPs) in an oncology setting can provide valuable information to providers as well as researchers. There also may be differences between patients with sporadic colorectal cancer and those with an inherited syndrome such as Lynch syndrome. There is a significant gap in knowledge regarding the patient–provider relationship in the oncology literature generally and in the Lynch syndrome (LS) population specifically. By understanding the predictors of patient satisfaction with their HCP for individuals with LS, we can better inform community health providers, develop more targeted interventions, and ultimately improve screening and surveillance adherence. This study evaluates satisfaction with HCPs in a matched sample of LS and sporadic CRC survivors.MLH1, MSH2, MSH6, PMS2, or in the EPCAM gene LS is the most common hereditary colon cancer, accounting for approximately 3% of all colorectal cancer (CRC) cases Compared with the general population, MMR mutation carriers have a higher lifetime risk for several cancers; CRC risk ranges from 20 to 69% for men and 10 to 52% for women, with risks varying based on mutated gene Patients’ satisfaction with their healthcare providers (HCPs) has been shown to be positively correlated with adherence to screening, surveillance, and treatment For individuals with LS, one critical factor that impacts a HCP's ability to appropriately counsel patients with LS is a significant gap in knowledge about genetics and LS. HCP not only need to be adequately informed about the characteristics of LS, but also need to be able to obtain comprehensive medical and family histories, make referrals to genetics services, and recommend appropriate screening and medical management A variety of tools have been used to evaluate patient satisfaction with their HCPs in the general population, but few have been used in oncology settings Several studies have identified trust and physician knowledge as important predictors of patient satisfaction with HCP in oncology settings Other relationship factors, including communication and interpersonal behavior, also have been used to assess patient satisfaction with HCPs in oncology settings The aim of this study was to evaluate satisfaction with HCPs in a matched sample of LS and sporadic CRC survivors. Directly comparing these two populations enabled us to identify factors related to provider satisfaction that may be unique to the LS population while also adding to the limited literature on patient satisfaction with their providers in an oncology setting.n = 33) and through social media (n = 42) and had to have tested positive for a LS mutation. Sporadic CRC survivors were recruited from the tumor registry at MD Anderson (n = 75). All participants were 18 years of age or older and were able to read and speak English. Patients with CRC were limited to those with a diagnosis of CRC from 6 months to 5 years prior to enrolling in the study. LS participants recruited through MD Anderson were screened for eligibility using medical records and those recruited through social media were screened by self‐report over the phone prior to enrolling in the study. Using information from their medical records, we excluded sporadic CRC patients with a personal or family history of familial adenomatous polyposis (FAP) and inflammatory bowel disease, or those who had a first‐degree relative with CRC.This study was approved by the Institutional Review Board at the University of Texas MD Anderson Cancer Center (MD Anderson). Participants were CRC survivors with LS or sporadic cancer who were matched on age, sex, race/ethnicity, cancer stage, geography, and time since diagnosis using a LS case–sporadic case design. Survivors with LS were recruited from MD Anderson  or other healthcare institution. All individuals seen at a CCC received care at MD Anderson. Healthcare utilization was measured using a 4‐item scale developed by the Stanford Chronic Disease Self‐Management Study The 20‐item Center for Epidemiologic Studies Depression (CES‐D) scale measured depressive symptoms We used four scales from the Primary Care Assessment Survey (PCAS) to measure the patient's relationship with the treating provider for our outcome, including communication, interpersonal treatment, patient trust, and provider's knowledge of the patient (comprehensive) Bivariate differences were evaluated between LS and sporadic survivors on known or expected factors related to provider satisfaction using chi‐square, and completed with SAS version 9.3 From the overall sample of 75 LS CRC and 75 sporadic CRC survivors, we excluded seven who were missing at least one component of our outcome measure, the PCAS scale. Our analytic sample for this study included 73 LS CRC and 70 sporadic CRC survivors. The average age of participants was in their early 50s with a mean age of 52.6 years for patients with LS and 54.1 for patients with sporadic cancer, with more females than males  and LS more likely to be married . Demographic characteristics can be seen in Table P = 0.03). There were no differences on any of these variables between the two recruitment sources for LS survivors.As illustrated in Table P = 0.05), interpersonal treatment , and physician's knowledge of the patient . There was no statistical difference in provider trust between the two groups.Compared with sporadic CRC survivors, LS survivors reported lower mean provider satisfaction scores on three of the PCAS subscales: communication  and trust  subscales. Higher mean depression scores were associated with lower mean scores on the trust subscale . Higher mean scores on family support were associated with higher communication satisfaction scores . There were no significant predictors for the interpersonal or comprehensive subscale measures.Tables P < 0.05; interpersonal: −0.55; P < 0.05). Lower mean State anxiety scores were associated with higher satisfaction scores for these survivors . Increased utilization was associated with higher satisfaction with the comprehensive aspects of provider treatment .Regression results for the sporadic CRC survivors differed from those of the LS survivors. There were no specific predictors for the trust subscale. Age was negatively associated with the communication and interpersonal subscale scores for sporadic survivors, indicating that as a patient gets older, he or she is less satisfied with providers in terms of communication and overall interaction (communication: −0.59; The goal of this study was to assess patient satisfaction with their healthcare providers in a sample of CRC survivors both with and without LS. Specifically, we were interested in comparing these two groups and then assessing factors drawn from the literature that impact these ratings of HCP satisfaction. Having a better understanding of these complex patient–provider relationships can both inform community health providers and assist in the development of future interventions.In our study, LS CRC survivors reported lower levels of satisfaction with their healthcare providers than sporadic CRC survivors, especially as related to communication, interpersonal interactions, and knowledge of the patient as a person. There were no differences between the two groups in our study in terms of ratings of provider trust. LS CRC survivors who received care at CCCs reported higher satisfaction when compared to those receiving care at other institutions, specifically in terms of communication and trust. Depressive symptoms and socioeconomic variables also impacted ratings of satisfaction with provider communication and trust in our LS population. Our finding regarding higher levels of education being associated with higher provider satisfaction is contrary to what has been reported in the general oncology literature assessing overall satisfaction with health care. Specifically, higher education has been associated with lower levels of satisfaction For sporadic CRC survivors, older age, higher anxiety, and healthcare utilization impacted healthcare provider satisfaction. Specifically, older survivors reported lower levels of satisfaction with respect to provider communication and the interpersonal aspects of their care. CRC survivors who reported higher anxiety also reported lower levels of satisfaction with patient–provider communication. Additionally, the more often a patient sees a HCP, the more satisfied he or she is with how much knowledge that HCP has about him or her as a person. This finding aligns with prior research showing that cancer survivors who are able to ask their providers questions and have their providers explain things in a way they can understand are more satisfied with their care Taken together, our study findings provide information that is relevant to both clinicians and researchers in regard to factors that influence provider satisfaction in CRC survivors both with and without LS and contribute to the small body of literature that exists on provider satisfaction in an oncology setting. We found evidence to suggest that patients with LS, particularly those who are being treated outside of CCCs, are less satisfied with their HCP than sporadic CRC survivors; however, many of the factors that we hypothesized might predict provider satisfaction in this population were not significant in our regression models. Specifically, we expected that both healthcare experiences and psychosocial factors would have a greater impact on patient satisfaction with their HCPs. While some of these variables were significant in our models, the extent was less than expected based on the literature. Despite these important conclusions and comparisons between LS and sporadic CRC survivors, we recognize that our study is limited by the small sample sizes of both groups as well as the potential bias in recruitment from two different pools of patients with LS. Recruitment for this hard‐to‐reach hereditary cancer population as well as case–case matching was painstakingly undertaken to ensure high‐quality data. Additionally, the control sample is drawn from one CCC, limiting our ability to assess location of care in the sporadic CRC population. One other study limitation is the lack of data on provider specialties as participants were asked to rate the provider most involved in coordinating his/her care, but were not asked to identify specialty areas. This data should be collected in future studies. Given the above‐mentioned factors, the results from this study may not be generalizable to all CRC survivors with or without LS.We believe that the findings from this study contribute to the scant literature on patient satisfaction with their HCPs both in the oncology literature generally and in the LS population specifically. We discovered a gap in patient satisfaction with their HCPs in these two patient populations that had not previously been demonstrated in the literature and also identified predictors of provider satisfaction that are unique to each of these CRC survivor populations. We also documented that location of care is a key factor in determining patient satisfaction with their HCPs for LS CRC survivors. While these findings can aid HCPs as well as researchers, we believe that further research is needed in a larger sample as well as with qualitative data to more closely examine characteristics of the patient–provider relationship and to identify additional predictors of patient satisfaction with HCPs. This work also needs to be expanded to assess the potential impact of patient satisfaction with their HCPs on adherence to medical management recommendations in LS CRC survivors, particularly those receiving care outside of CCCs.The authors declare no conflict of interests.Table S1. Comparison of LS and sporadic CRC survivors on study variables.Click here for additional data file.


AAML0531 had greater intensive care unit (ICU)‐level requirements than enrolled patients and whether early discharge after chemotherapy administration mediated this association. Patients not enrolled on AAML0531 were more likely to be discharged early  and to require ICU‐level care  than enrolled patients, but early discharge explained only a small proportion (12.3%) of the absolute difference in ICU‐level care risk. The direct effect of nonenrollment on the need for ICU‐level care was significant , whereas the indirect effect mediated through early discharge was not . Factors other than postchemotherapy discharge strategy drive the difference in ICU utilization by trial enrollment status.Previous data suggest that patients enrolled on clinical trials for treatment of cancer have better overall survival than patients who do not enroll; however, short‐term outcomes relative to trial enrollment and corresponding mediators have not been assessed. A cohort of pediatric patients with newly‐diagnosed acute myeloid leukemia was assembled from the Pediatric Health Information System. We evaluated whether patients not enrolled onto Children's Oncology Group trial  There is conflicting evidence for a direct beneficial effect of clinical trial participation on treatment outcomes among patients with cancer We recently evaluated associations between early discharge to outpatient management during postchemotherapy neutropenia (relative to inpatient management) and both utilization of intensive care unit (ICU)‐level care Given these observations and literature suggesting differential outcomes among cancer patients by trial enrollment, we evaluated whether patients not enrolled onto AAML0531 had greater ICU utilization than those enrolled. We then assessed whether this association was mediated by differences in postchemotherapy discharge strategy.The study population was derived from a previously assembled cohort of children who received standard frontline chemotherapy for AML in the Pediatric Health Information System administrative billing database (PHIS) The exposure of interest was enrollment status on AAML0531. Patients identified in both the COG and PHIS datasets were considered “enrolled” while patients with only PHIS data were considered “not enrolled”. ICD‐9‐CM diagnosis codes were reviewed to confirm that “not enrolled” patients would not have violated AAML0531 exclusion criteria.Course‐specific follow‐up started 4 days after the last day of chemotherapy and continued until the start of the subsequent course, death, or 50 days after commencement of the last chemotherapy course, whichever occurred first. The primary outcome of interest was receipt of ICU‐level care  over the duration of follow‐up.Utilization rates (days of use per 1000 inpatient days) for each of the following resources were also presented to explore the nature of the specific ICU requirements: antibiotic, antifungal, antiviral, and vasopressor medications, parenteral nutrition, blood product replacement, and supplemental oxygen.Early discharge‐eligible patients were categorized based on timing of discharge relative to the last day of chemotherapy. Patients discharged within 3 days after chemotherapy completion were categorized as “early discharge” and all others were categorized as “standard discharge”.We proposed a mechanistic model of the association between trial enrollment status and ICU‐level care requirements suggesting postchemotherapy neutropenia management strategy (early vs. standard discharge) as a possible mediator. The following are required for early discharge to be a potential mediator: significant associations between (1) trial nonenrollment and early discharge and (2) early discharge and ICU‐level care, and (3) a non‐null relationship between trial nonenrollment and ICU‐level care All patients enrolled on AAML0531 provided informed consent for use of trial data for research. All patient data remained deidentified throughout data merging and analysis.The current analyses included 941 chemotherapy courses contributed by 390 pediatric AML patients. There were no significant differences in distributions of race, gender, age at diagnosis, or insurance at diagnosis between patients who were enrolled on the clinical trial and those who were not   on the risk for ICU‐level care into its indirect effect through early discharge  and its direct effect  through other undefined pathways. Altogether, 12.3% of the absolute effect of trial enrollment on ICU‐level care was mediated through early discharge.With respect to the specific pattern of resources utilized, patients not enrolled on AAML0531 incurred higher rates of vasopressor , fresh frozen plasma , and supplemental oxygen  than patients enrolled on the trial (Table This study found a higher risk of both ICU‐level care and early discharge for patients not enrolled on AAML0531. Because we previously demonstrated that patients discharged early to outpatient management also sustained greater rates of ICU‐level care a difference which was driven primarily by increased rates of bacterial infections Together, these results suggest that factors other than postchemotherapy discharge strategy explain the increase in ICU‐level care requirements among those not enrolled on AAML0531. In adult studies of various malignancies, trial participants have been shown to be a prognostically more favorable subset of patients We employed mediation methods which allowed for control for confounding by a variety of covariates and incorporation of an interaction between the exposure and mediator These analyses suggest that pediatric AML patients not enrolled on clinical trials have poorer short‐term outcomes, specifically greater ICU requirements, than those enrolled. Additionally, the proposed mediator, early discharge, explained only a small proportion of the difference in outcomes by trial enrollment status suggesting that changes in this practice are unlikely to resolve the discrepancy in outcome. Future studies should assess additional factors, including clinical status at presentation and barriers to accessing care, with the goal of identifying actionable mediating pathways. Mediation methods may be particularly helpful in this regard when the primary exposure is difficult or impossible to alter None declared.Figure S1. AAML0531 experimental design schema.Click here for additional data file.


Mapping hundreds of genetic variants through genome wide association studies provided an opportunity to gain insights into the pathobiology of immune‐mediated diseases. However, as most of the disease variants fall outside the gene coding sequences the functional interpretation of the exact role of the associated variants remains to be determined. The integration of disease‐associated variants with large scale genomic maps of cell‐type‐specific gene regulation at both chromatin and transcript levels deliver examples of functionally prioritized causal variants and genes. In particular, the enrichment of disease variants with histone marks can point towards the cell types most relevant to disease development. Furthermore, chromatin contact maps that link enhancers to promoter regions in a direct way allow the identification of genes that can be regulated by the disease variants. Candidate genes implicated with such approaches can be further examined through the correlation of gene expression with genotypes. Additionally, in the context of immune‐mediated diseases it is important to combine genomics with immunology approaches. Genotype correlations with the immune system as a whole, as well as with cellular responses to different stimuli, provide a valuable platform for understanding the functional impact of disease‐associated variants. The intersection of immunogenomic resources with disease‐associated variants paints a detailed picture of disease causal mechanisms. Here, we provide an overview of recent studies that combine these approaches to identify disease vulnerable pathways. Chromatin accessibilityATAC‐seq (assay for transposase accessible chromatin followed by sequencing) or DNase‐seq, often have a functional role in regulating transcription and are enriched at promoters and enhancers.a term describing regions of the genome free of nucleosomes, which might be a result of the sequence occupation by a DNA binding protein, such as transcription factors. The open chromatin regions, which can be assayed with Chromatin immunoprecipitation followed by sequencing (ChIP‐seq)an assay in which antibodies against an epitope of interest, such as a transcription factor or a histone modification, are used to pull down the protein of interest along with the genomic sequences interacting with it. The proteins are then washed off and the DNA is sequenced. The sequencing results in pile ups of reads concentrated at the positions of DNA ‐protein interaction, referred to as peaks.Genome‐wide association studies (GWAS)P‐value < 5 x 10‐8), the variant is reported as disease‐associated. GWAS can also be applied within a single group with quantitative measurements, such as a group of patients for which a response to a treatment is measured, or a group of healthy individuals for which blood cell counts have been recorded.a method that leverages the information from genetic variants spread through the whole genome and compares allele frequencies between a group of patients and a group of healthy controls, within the same population. If the frequency difference is statistically significant between the two groups a correlation between genetic variants, resulting from the non‐random inheritance of genetic regions.Quantitative trait locus (QTL)SNPs), are correlated with the gene expression levels (eQTL).a region of the genome that is correlated with a quantitative phenotype. Typically, genetic variants, such as single nucleotide polymorphisms  and CeD, result from the combination of the risk genotypes of both the HLA and non‐HLA genes, as well as an environmental trigger. Genome‐wide association studies (GWAS) revealed that complex immune traits develop as a consequence of the interplay between hundreds to thousands of common variantsCD28, ICOS and CTLA4, is associated to CeD, RA and T1D. The sharing of genetic regions associated with immune diseases is widespread; of the 90 risk loci associated with T1D, RA, CeD and MS, 33 (37%) overlap between two or more diseases.CTLA4, induce severe immunodeficiency and a spectrum of autoimmune and autoinflammatory diseases.A clear picture emerging from GWAS is that immune‐mediated diseases to some extent result from the dysregulation of the same biological pathways. For example, a locus encoding genes for receptors that control T‐cell activation, Here, we provide an overview of the recent advances in the genetics of immune‐mediated diseases. We discuss how the immunogenomic cross‐disciplinary toolkit can be used as a platform for inferring correlations between genotypes and individual genes, cellular traits, as well as the immune system as a whole Fig. . FinallyITGA, ITGAL, ICAM and ITGB8 genes, encoding integrins, the pro‐inflammatory cell surface proteins that mediate leucocyte accumulation at the site of inflammation.The effects of genetic variants on gene expression are often assessed through genotype correlation with gene expression levels measured across tens to thousands of individuals  receptor in CD4+ T‐cell pathways could play a protective role for T1D.The very early eQTL mapping studies have already recognized the importance of cell‐type‐specific gene regulation. Dimas et al.CD52, a target for antibody therapy used in MS treatment.+ and CD8+ T cells, showed a limited overlap between eQTLs and GWAS SNPs (21 SNPs affecting the expression of 133 genes) based on a cohort of 313 healthy individuals.Regulatory variants can exhibit opposite effects across different cell types.et al.,γ and demonstrated that 467 eQTLs overlapped with disease‐associated GWAS SNPs, 53% of which were stimulation specific. One of the eQTL‐GWAS SNPs was an MS variant that affects IRF8 expression following 2 hr stimulation with lipopolysaccharide. Earlier studies that investigated the expression levels of IRF8 in peripheral blood mononuclear cells using microarrays failed to identify a variant controlling the expression of this gene,IRF8 is a regulatory factor of type‐1 interferons, which are elevated in patients with SLE, whereas patients with MS present low interferon levels.γ,+ T cells stimulated with anti‐CD3/anti‐CD28 beads.et al. identified 157 GWAS SNPs that overlapped with genetic variants that affected gene expression in CD4+ T cells in a cohort of 348 healthy individuals.IL23R and a variant nearby IL2RA associated with T1D, MS and vitiligo, only presented an effect on gene expression 48 hr following stimulation. Given that most effector functions of immune cells are performed following stimulation, it is not surprising that the majority of immune disease variants are functional in activated cells. Further studies are necessary to investigate different stimulation contexts in more detail.However, even if the relevant cell type is identified, the functional effect of a variant may not be detected unless the cell is challenged in an appropriate environment. Fairfax Gene expression regulation results from the tight interplay between gene enhancers and promoters. Chromatin immunoprecipitation followed by sequencing (ChIP‐seq), assesses DNA–protein interactions by pulling down regions of the genome that are bound by the protein of interest. Recently, this method has been used to annotate the activity of non‐coding regions of the genome through the presence of different post‐translational histone modifications. Histone marks highlight genomic regions that regulate gene expression, they reflect change in chromatin structure that is often coupled with DNA accessibility for binding by different proteins, such as transcription factors (TFs). International consortia have worked together to comprehensively annotate the non‐coding sequences of the genome across a wide range of cell lines and primary cell types.+ T‐cell subsets in a number of autoimmune disorders, including T1D and RA. CD4+ memory T cells and regulatory T (Treg) cells showed high enrichment for variants associated with a number of diseases, including RA, IBD and CeD.α‐chain of IL‐2 receptor, which affects their phenotype and decreases their survival.Comprehensive annotation of the regulatory chromatin provides an opportunity to interpret the role of non‐coding disease variants. Indeed, development of statistical approaches that integrate GWAS SNPs with histone marks proved to be a valuable approach to prioritize disease‐relevant cell types+ T‐cell subsets marked by histone‐3 lysine‐27 acetylation (H3K27ac).+ T cells, from 200 individuals, Chen et al.Leveraging ChIP‐seq data allowed the mapping of a proportion of GWAS variants in active enhancer regions of CD4n = 262) of GWAS SNPs associated with autoimmune diseases residing within the DNase hypersensitive sites in immune cells altered the TF binding motif for the IRF9 pathway.γ, pointing towards a potentially important role for this pathway in the development of autoimmunity.In addition to ChIP‐seq, genome activity can also be measured by chromatin accessibility, either through mapping regions that undergo cutting by DNase (DNase hypersensitive sites)TNFAIP3, the closest gene, but also with IL20RA.RASGRP1, a gene that activates the extracellular signal‐regulated kinase/mitogen‐activated protein kinase cascade and regulates T‐cell and B‐cell development and differentiation.Despite the observed enrichment of disease variants in regulatory non‐coding sequences it is estimated that only 10–20% of 823 disease variants lie within transcription factor binding motifs, suggesting other mechanisms of gene expression regulation,et al. observed that trans methylation QTLs, where genetic variants affect distant rather than local methylation status, were enriched for immune‐associated GWAS traits.trans‐methylation QTLs that influenced the TF binding sites, including two SNPs on chromosome 4 associated with ulcerative colitis. They prioritized one of them as the causal SNP based on its association with lower methylation and the higher gene expression of NFKB1. By incorporating Hi‐C assay with DNA methylation and RNA sequencing, Bonder et al., showed that inter‐chromosomal contacts provide a mechanism by which some trans‐methylation QTLs can act. The 402 identified CpG islands overlapped with CTCF, RAD21 and SMC3 TF binding sites.Gene expression regulation is also reflected through DNA methylation. By combining DNA methylation with RNA sequencing from 3841 Dutch individuals, Bonder To gain comprehensive insights into the effects of genetic variants on the immune system, genomic assays have to be complemented with traditional immunological approaches. The network of cellular interactions can be assessed at a global scale, for instance by looking at mechanisms that control cell frequency and cell proliferation, as well as at the cellular level, by measuring protein expression and identifying genes that drive the phenotype of interest. To accurately infer the causal relationships between genetic variants and cellular traits it is important to carry out the experiments in cells isolated from healthy individuals, limiting the effects of active disease or ongoing treatment.+ : CD8+ T‐cell ratio. Both signals mapped to the MHC region, explaining 8% of the observed variance. Interestingly, one of these associations overlapped with a T1D variant where the T1D risk allele increases the number of CD4+ cells by decreasing their apoptosis rate.et al.COG6, SPRED2, RUNX1 and ATXN2/SH2B3/BRAP genes pointed towards a novel link between eosinophil function and RA. Study of immune cell frequencies and surface protein expression levels of 170 dizygotic and 75 monozygotic pairs of twins using seven distinct 14‐plex antibody panels identified 151 independent heritable immune traits, including, for example, the proportion of CD10+ immature B cells associated with the genotypes of the MME gene, which encodes for a metallo‐peptidase.+ Treg cells. The authors identified a SNP that increases the level of CD39, and so alters the proportion of CD39+ Treg cells. CD39 along with CD73 are enzymes that degrade the pro‐inflammatory ATP molecule to an anti‐inflammatory adenosine.The ratio between different immune cell subsets is heritable and could partly account for one of the pathobiological disease mechanisms.+ effector memory T cells.et al.+ T effector memory cells and measured relative cell abundance, as well as gene expression of 215 genes located in RA loci, and cell proliferation capacity upon in vitro stimulation with anti‐CD28/anti‐CD3. The authors identified a group of genes whose basal level could predict the proliferative potential of effector memory cells, along with a non‐coding genetic variant that increased cell division capacity. Although, this study has not linked RA risk loci with the effect on CD4+ memory cell proliferation, it exemplifies how to link genotype to immune cell function.In another study, the authors demonstrated that genes located near RA‐associated variants were highly expressed in CD4α levels.β were identified as being mostly driven by genetics, compared with environmental factors and the microbiome.α subunit of the IL‐2 receptor with Crohn's disease and MS.et al., de‐convoluted complex immune response signatures to a range of stimuli.α upon stimulation, despite the presence of IL‐1β, suggesting a genetic component underlying this effect.The effector function of immune cells is to communicate with each other through expression of receptors and receptor ligands, combined with the secretion of specific molecules, such as cytokines. Alteration of these cellular functions results in an impaired immune response. Interestingly, the cytokine levels in the blood have been shown to be highly heritable.Over the last decade, hundreds of immune disease loci have been successfully mapped. Recent advances in genomics have enabled functional follow‐up studies that provide insights into the molecular mechanisms by which risk variants drive disease pathology.in vitro. This process has to be repeated a number of times on blood drawn from individuals of the same population to reach a cohort size large enough that it would allow for reliable identification of QTL effects. QTL effects have been annotated mostly in the context of expression assays, however, a proportion of GWAS variants may not act through gene regulation measured by bulk gene expression assays, calling for further development of genomic tools.In this review, we have provided recent examples where the correlations of quantitative immunogenomic phenotypes with disease‐associated loci prioritized causal variants and suggested disrupted gene pathways and cellular functions. Although the majority of individual allelic effects have a miniscule effect on the overall phenotype, the effects can be higher on the molecular or cellular levels. Hence, future efforts have to be focused on identifying the critical disease cell types in which the associated variants are functional. These studies are challenging to conduct, as certain cell populations only represent a small proportion of the whole blood and need to be isolated using reliable markers and cell sorting. Importantly, isolated cell populations are often difficult to culture Human Cell Atlas.A challenge in GWAS follow‐up studies is that often the causal cell types are unknown. Typically, cell types have been identified through immunology studies where a limited set of specific cell markers, both intracellular and extracellular, have been used to characterize cell populations. A promising new method, that is unbiased to a predefined set of markers, is single‐cell RNA sequencing (scRNA‐seq). This approach can identify previously unknown heterogeneity in a sample based on gene expression measured at the individual cell level. There is now a major international effort that aims to use scRNA‐seq to characterize all human cells, the The authors have no competing interests.