Implementation of a Prospective Index-Cluster Sampling Strategy for the Detection of Presymptomatic Viral Respiratory Infection in Undergraduate Students.

Background: Index-cluster studies may help characterize the spread of communicable infections in the presymptomatic state. We describe a prospective index-cluster sampling strategy (ICSS) to detect presymptomatic respiratory viral illness and its implementation in a college population. Methods: We enrolled an annual cohort of first-year undergraduates who completed daily electronic symptom diaries to identify index cases (ICs) with respiratory illness. Investigators then selected 5-10 potentially exposed, asymptomatic close contacts (CCs) who were geographically co-located to follow for infections. Symptoms and nasopharyngeal samples were collected for 5 days. Logistic regression model-based predictions for proportions of self-reported illness were compared graphically for the whole cohort sampling group and the CC group. Results: We enrolled 1379 participants between 2009 and 2015, including 288 ICs and 882 CCs. The median number of CCs per IC was 6 (interquartile range, 3-8). Among the 882 CCs, 111 (13%) developed acute respiratory illnesses. Viral etiology testing in 246 ICs (85%) and 719 CCs (82%) identified a pathogen in 57% of ICs and 15% of CCs. Among those with detectable virus, rhinovirus was the most common (IC: 18%; CC: 6%) followed by coxsackievirus/echovirus (IC: 11%; CC: 4%). Among 106 CCs with a detected virus, only 18% had the same virus as their associated IC. Graphically, CCs did not have a higher frequency of self-reported illness relative to the whole cohort sampling group. Conclusions: Establishing clusters by geographic proximity did not enrich for cases of viral transmission, suggesting that ICSS may be a less effective strategy to detect spread of respiratory infection.

Access to COVID-19 testing by individuals with housing insecurity during the early days of the COVID-19 pandemic in the United States: a scoping review.

Introduction: The COVID-19 pandemic focused attention on healthcare disparities and inequities faced by individuals within marginalized and structurally disadvantaged groups in the United States. These individuals bore the heaviest burden across this pandemic as they faced increased risk of infection and difficulty in accessing testing and medical care. Individuals experiencing housing insecurity are a particularly vulnerable population given the additional barriers they face. In this scoping review, we identify some of the barriers this high-risk group experienced during the early days of the pandemic and assess novel solutions to overcome these barriers. Methods: A scoping review was performed following PRISMA-Sc guidelines looking for studies focusing on COVID-19 testing among individuals experiencing housing insecurity. Barriers as well as solutions to barriers were identified as applicable and summarized using qualitative methods, highlighting particular ways that proved effective in facilitating access to testing access and delivery. Results: Ultimately, 42 studies were included in the scoping review, with 143 barriers grouped into four categories: lack of cultural understanding, systemic racism, and stigma; medical care cost, insurance, and logistics; immigration policies, language, and fear of deportation; and other. Out of these 42 studies, 30 of these studies also suggested solutions to address them. Conclusion: A paucity of studies have analyzed COVID-19 testing barriers among those experiencing housing insecurity, and this is even more pronounced in terms of solutions to address those barriers. Expanding resources and supporting investigators within this space is necessary to ensure equitable healthcare delivery.

RADx-UP Testing Core: Access to COVID-19 Diagnostics in Community-Engaged Research with Underserved Populations.

Research on the COVID-19 pandemic revealed a disproportionate burden of COVID-19 infection and death among underserved populations and exposed low rates of SARS-CoV-2 testing in these communities. A landmark National Institutes of Health (NIH) funding initiative, the Rapid Acceleration of Diagnostics-Underserved Populations (RADx-UP) program, was developed to address the research gap in understanding the adoption of COVID-19 testing in underserved populations. This program is the single largest investment in health disparities and community-engaged research in the history of the NIH. The RADx-UP Testing Core (TC) provides community-based investigators with essential scientific expertise and guidance on COVID-19 diagnostics. This commentary describes the first 2 years of the TC's experience, highlighting the challenges faced and insights gained to safely and effectively deploy large-scale diagnostics for community-initiated research in underserved populations during a pandemic. The success of RADx-UP shows that community-based research to increase access and uptake of testing among underserved populations can be accomplished during a pandemic with tools, resources, and multidisciplinary expertise provided by a centralized testing-specific coordinating center. We developed adaptive tools to support individual testing strategies and frameworks for these diverse studies and ensured continuous monitoring of testing strategies and use of study data. In a rapidly evolving setting of tremendous uncertainty, the TC provided essential and real-time technical expertise to support safe, effective, and adaptive testing. The lessons learned go beyond this pandemic and can serve as a framework for rapid deployment of testing in response to future crises, especially when populations are affected inequitably.

Assessment of the Feasibility of Using Noninvasive Wearable Biometric Monitoring Sensors to Detect Influenza and the Common Cold Before Symptom Onset.

Importance: Currently, there are no presymptomatic screening methods to identify individuals infected with a respiratory virus to prevent disease spread and to predict their trajectory for resource allocation. Objective: To evaluate the feasibility of using noninvasive, wrist-worn wearable biometric monitoring sensors to detect presymptomatic viral infection after exposure and predict infection severity in patients exposed to H1N1 influenza or human rhinovirus. Design, Setting, and Participants: The cohort H1N1 viral challenge study was conducted during 2018; data were collected from September 11, 2017, to May 4, 2018. The cohort rhinovirus challenge study was conducted during 2015; data were collected from September 14 to 21, 2015. A total of 39 adult participants were recruited for the H1N1 challenge study, and 24 adult participants were recruited for the rhinovirus challenge study. Exclusion criteria for both challenges included chronic respiratory illness and high levels of serum antibodies. Participants in the H1N1 challenge study were isolated in a clinic for a minimum of 8 days after inoculation. The rhinovirus challenge took place on a college campus, and participants were not isolated. Exposures: Participants in the H1N1 challenge study were inoculated via intranasal drops of diluted influenza A/California/03/09 (H1N1) virus with a mean count of 106 using the median tissue culture infectious dose (TCID50) assay. Participants in the rhinovirus challenge study were inoculated via intranasal drops of diluted human rhinovirus strain type 16 with a count of 100 using the TCID50 assay. Main Outcomes and Measures: The primary outcome measures included cross-validated performance metrics of random forest models to screen for presymptomatic infection and predict infection severity, including accuracy, precision, sensitivity, specificity, F1 score, and area under the receiver operating characteristic curve (AUC). Results: A total of 31 participants with H1N1 (24 men [77.4%]; mean [SD] age, 34.7 [12.3] years) and 18 participants with rhinovirus (11 men [61.1%]; mean [SD] age, 21.7 [3.1] years) were included in the analysis after data preprocessing. Separate H1N1 and rhinovirus detection models, using only data on wearble devices as input, were able to distinguish between infection and noninfection with accuracies of up to 92% for H1N1 (90% precision, 90% sensitivity, 93% specificity, and 90% F1 score, 0.85 [95% CI, 0.70-1.00] AUC) and 88% for rhinovirus (100% precision, 78% sensitivity, 100% specificity, 88% F1 score, and 0.96 [95% CI, 0.85-1.00] AUC). The infection severity prediction model was able to distinguish between mild and moderate infection 24 hours prior to symptom onset with an accuracy of 90% for H1N1 (88% precision, 88% sensitivity, 92% specificity, 88% F1 score, and 0.88 [95% CI, 0.72-1.00] AUC) and 89% for rhinovirus (100% precision, 75% sensitivity, 100% specificity, 86% F1 score, and 0.95 [95% CI, 0.79-1.00] AUC). Conclusions and Relevance: This cohort study suggests that the use of a noninvasive, wrist-worn wearable device to predict an individual's response to viral exposure prior to symptoms is feasible. Harnessing this technology would support early interventions to limit presymptomatic spread of viral respiratory infections, which is timely in the era of COVID-19.

Innate-like Gene Expression of Lung-Resident Memory CD8+ T Cells during Experimental Human Influenza: A Clinical Study.

Rationale: Suboptimal vaccine immunogenicity and antigenic mismatch, compounded by poor uptake, means that influenza remains a major global disease. T cells recognizing peptides derived from conserved viral proteins could enhance vaccine-induced cross-strain protection. Objectives: To investigate the kinetics, phenotypes, and function of influenza virus-specific CD8+ resident memory T (Trm) cells in the lower airway and infer the molecular pathways associated with their response to infection in vivo. Methods: Healthy volunteers, aged 18-55, were inoculated intranasally with influenza A/California/4/09(H1N1). Blood, upper airway, and (in a subgroup) lower airway samples were obtained throughout infection. Symptoms were assessed by using self-reported diaries, and the nasal viral load was assessed by using quantitative PCR. T-cell responses were analyzed by using a three-color FluoroSpot assay, flow cytometry with MHC I-peptide tetramers, and RNA sequencing, with candidate markers being confirmed by using the immunohistochemistry results for endobronchial biopsy specimens. Measurements and Main Results: After challenge, 57% of participants became infected. Preexisting influenza-specific CD8+ T cells in blood correlated strongly with a reduced viral load, which peaked at Day 3. Influenza-specific CD8+ T cells in BAL fluid were highly enriched and predominantly expressed the Trm markers CD69 and CD103. Comparison between preinfection CD8+ T cells in BAL fluid and blood by using RNA sequencing revealed 3,928 differentially expressed genes, including all major Trm-cell markers. However, gene set enrichment analysis of BAL-fluid CD8+ T cells showed primarily innate cell-related pathways and, during infection, included upregulation of innate chemokines (Cxcl1, Cxcl10, and Cxcl16) that were also expressed by CD8+ cells in bronchial tissues. Conclusions: CD8+ Trm cells in the human lung display innate-like gene and protein expression that demonstrates blurred divisions between innate and adaptive immunity. Clinical study registered with www.clinicaltrials.gov (NCT02755948).

A blood-based host gene expression assay for early detection of respiratory viral infection: an index-cluster prospective cohort study.

BACKGROUND: Early and accurate identification of individuals with viral infections is crucial for clinical management and public health interventions. We aimed to assess the ability of transcriptomic biomarkers to identify naturally acquired respiratory viral infection before typical symptoms are present. METHODS: In this index-cluster study, we prospectively recruited a cohort of undergraduate students (aged 18-25 years) at Duke University (Durham, NC, USA) over a period of 5 academic years. To identify index cases, we monitored students for the entire academic year, for the presence and severity of eight symptoms of respiratory tract infection using a daily web-based survey, with symptoms rated on a scale of 0-4. Index cases were defined as individuals who reported a 6-point increase in cumulative daily symptom score. Suspected index cases were visited by study staff to confirm the presence of reported symptoms of illness and to collect biospecimen samples. We then identified clusters of close contacts of index cases (ie, individuals who lived in close proximity to index cases, close friends, and partners) who were presumed to be at increased risk of developing symptomatic respiratory tract infection while under observation. We monitored each close contact for 5 days for symptoms and viral shedding and measured transcriptomic responses at each timepoint each day using a blood-based 36-gene RT-PCR assay. FINDINGS: Between Sept 1, 2009, and April 10, 2015, we enrolled 1465 participants. Of 264 index cases with respiratory tract infection symptoms, 150 (57%) had a viral cause confirmed by RT-PCR. Of their 555 close contacts, 106 (19%) developed symptomatic respiratory tract infection with a proven viral cause during the observation window, of whom 60 (57%) had the same virus as their associated index case. Nine viruses were detected in total. The transcriptomic assay accurately predicted viral infection at the time of maximum symptom severity (mean area under the receiver operating characteristic curve [AUROC] 0·94 [95% CI 0·92-0·96]), as well as at 1 day (0·87 [95% CI 0·84-0·90]), 2 days (0·85 [0·82-0·88]), and 3 days (0·74 [0·71-0·77]) before peak illness, when symptoms were minimal or absent and 22 (62%) of 35 individuals, 25 (69%) of 36 individuals, and 24 (82%) of 29 individuals, respectively, had no detectable viral shedding. INTERPRETATION: Transcriptional biomarkers accurately predict and diagnose infection across diverse viral causes and stages of disease and thus might prove useful for guiding the administration of early effective therapy, quarantine decisions, and other clinical and public health interventions in the setting of endemic and pandemic infectious diseases. FUNDING: US Defense Advanced Research Projects Agency.

Nasopharyngeal Protein Biomarkers of Acute Respiratory Virus Infection.

Infection of respiratory mucosa with viral pathogens triggers complex immunologic events in the affected host. We sought to characterize this response through proteomic analysis of nasopharyngeal lavage in human subjects experimentally challenged with influenza A/H3N2 or human rhinovirus, and to develop targeted assays measuring peptides involved in this host response allowing classification of acute respiratory virus infection. Unbiased proteomic discovery analysis identified 3285 peptides corresponding to 438 unique proteins, and revealed that infection with H3N2 induces significant alterations in protein expression. These include proteins involved in acute inflammatory response, innate immune response, and the complement cascade. These data provide insights into the nature of the biological response to viral infection of the upper respiratory tract, and the proteins that are dysregulated by viral infection form the basis of signature that accurately classifies the infected state. Verification of this signature using targeted mass spectrometry in independent cohorts of subjects challenged with influenza or rhinovirus demonstrates that it performs with high accuracy (0.8623 AUROC, 75% TPR, 97.46% TNR). With further development as a clinical diagnostic, this signature may have utility in rapid screening for emerging infections, avoidance of inappropriate antibacterial therapy, and more rapid implementation of appropriate therapeutic and public health strategies.

A Genomic Signature of Influenza Infection Shows Potential for Presymptomatic Detection, Guiding Early Therapy, and Monitoring Clinical Responses.

Early, presymptomatic intervention with oseltamivir (corresponding to the onset of a published host-based genomic signature of influenza infection) resulted in decreased overall influenza symptoms (aggregate symptom scores of 23.5 vs 46.3), more rapid resolution of clinical disease (20 hours earlier), reduced viral shedding (total median tissue culture infectious dose [TCID50] 7.4 vs 9.7), and significantly reduced expression of several inflammatory cytokines (interferon-γ, tumor necrosis factor-α, interleukin-6, and others). The host genomic response to influenza infection is robust and may provide the means for early detection, more timely therapeutic interventions, a meaningful reduction in clinical disease, and an effective molecular means to track response to therapy.

Longitudinal analysis of leukocyte differentials in peripheral blood of patients with acute respiratory viral infections.

BACKGROUND: Leukocyte counts and differentials are commonly acquired in patients with suspected respiratory viral infections and may contribute diagnostic information. However, most published work is limited to a single timepoint at initial presentation to a medical provider, which may correspond to widely varying points in the course of disease. OBJECTIVES: To examine the temporal development and time-dependent utility of routine leukocyte differentials in the diagnosis of respiratory viral infections. STUDY DESIGN: We analyzed data from recent experimental human challenges with influenza A/H3N2, human rhinovirus (HRV), and respiratory syncytial virus (RSV). Routine clinical lab cell counts and differentials were measured daily from the time period immediately prior to inoculation through the eventual resolution of symptomatic disease. RESULTS: Approximately 50% of challenged individuals developed symptoms and viral shedding consistent with clinical disease. Subpopulations of WBC showed marked differences between symptomatic and asymptomatic individuals over time, but these changes were much more profound and consistent in influenza infection. Influenza-infected subjects develop both relative lymphopenia and relative monocytosis, both of which closely mirror symptom development in time. A lymphocyte:monocyte ratio of <2 correctly classifies 100% of influenza (but not RSV or HRV) infected subjects at the time of maximal symptoms. CONCLUSIONS: Leukocyte differentials may suggest a viral etiology in patients with upper respiratory infection, but are not sufficient to allow differentiation between common viruses. Timing of data acquisition relative to the disease course is a key component in determining the utility of these tests.

A host-based RT-PCR gene expression signature to identify acute respiratory viral infection.

Improved ways to diagnose acute respiratory viral infections could decrease inappropriate antibacterial use and serve as a vital triage mechanism in the event of a potential viral pandemic. Measurement of the host response to infection is an alternative to pathogen-based diagnostic testing and may improve diagnostic accuracy. We have developed a host-based assay with a reverse transcription polymerase chain reaction (RT-PCR) TaqMan low-density array (TLDA) platform for classifying respiratory viral infection. We developed the assay using two cohorts experimentally infected with influenza A H3N2/Wisconsin or influenza A H1N1/Brisbane, and validated the assay in a sample of adults presenting to the emergency department with fever (n = 102) and in healthy volunteers (n = 41). Peripheral blood RNA samples were obtained from individuals who underwent experimental viral challenge or who presented to the emergency department and had microbiologically proven viral respiratory infection or systemic bacterial infection. The selected gene set on the RT-PCR TLDA assay classified participants with experimentally induced influenza H3N2 and H1N1 infection with 100 and 87% accuracy, respectively. We validated this host gene expression signature in a cohort of 102 individuals arriving at the emergency department. The sensitivity of the RT-PCR test was 89% [95% confidence interval (CI), 72 to 98%], and the specificity was 94% (95% CI, 86 to 99%). These results show that RT-PCR-based detection of a host gene expression signature can classify individuals with respiratory viral infection and sets the stage for prospective evaluation of this diagnostic approach in a clinical setting.

Comparing influenza and RSV viral and disease dynamics in experimentally infected adults predicts clinical effectiveness of RSV antivirals.

BACKGROUND: Antivirals reduce influenza viral replication and illness measures, particularly if initiated early, within 48 h of symptom onset. Whether experimental antivirals that reduce respiratory syncytial virus (RSV) load would also reduce disease is unknown. This study compares viral and disease dynamics in humans experimentally infected with influenza or RSV. METHODS: Clinical strains of RSV-A and influenza A were inoculated intranasally into 20 and 17 healthy volunteers, respectively, on day 0. Symptom scores and nasal washes were performed twice daily, and daily mucus weights were collected. Viral loads in nasal washes were quantified by culture (plaque assay in HEp-2 cells for RSV and by end point dilution in Madin-Darby canine kidney cells for influenza). RESULTS: After influenza inoculation, influenza viral load and illness markers increased simultaneously until day 2. Within individual subjects, peak influenza load occurred 0.4 days (95% CI -0.4, 1.3) before peak symptoms. Influenza viral load and disease declined thereafter. After RSV inoculation, a longer incubation period occurred prior to viral detection and symptom onset. RSV load and disease increased together until day 5. Within individual subjects, peak RSV loads occurred 0.2 days (95% CI -0.7, 1.05) before peak symptoms, after which both illness measures and viral load declined together. CONCLUSIONS: Viral and disease dynamics in experimental human infections suggest that reducing RSV load, if timed similarly to clinically-effective influenza antivirals, might be expected to have a similar or greater window of opportunity for reducing clinical RSV disease.

A host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza H1N1 or H3N2.

There is great potential for host-based gene expression analysis to impact the early diagnosis of infectious diseases. In particular, the influenza pandemic of 2009 highlighted the challenges and limitations of traditional pathogen-based testing for suspected upper respiratory viral infection. We inoculated human volunteers with either influenza A (A/Brisbane/59/2007 (H1N1) or A/Wisconsin/67/2005 (H3N2)), and assayed the peripheral blood transcriptome every 8 hours for 7 days. Of 41 inoculated volunteers, 18 (44%) developed symptomatic infection. Using unbiased sparse latent factor regression analysis, we generated a gene signature (or factor) for symptomatic influenza capable of detecting 94% of infected cases. This gene signature is detectable as early as 29 hours post-exposure and achieves maximal accuracy on average 43 hours (p = 0.003, H1N1) and 38 hours (p-value = 0.005, H3N2) before peak clinical symptoms. In order to test the relevance of these findings in naturally acquired disease, a composite influenza A signature built from these challenge studies was applied to Emergency Department patients where it discriminates between swine-origin influenza A/H1N1 (2009) infected and non-infected individuals with 92% accuracy. The host genomic response to Influenza infection is robust and may provide the means for detection before typical clinical symptoms are apparent.

Temporal dynamics of host molecular responses differentiate symptomatic and asymptomatic influenza a infection.

Exposure to influenza viruses is necessary, but not sufficient, for healthy human hosts to develop symptomatic illness. The host response is an important determinant of disease progression. In order to delineate host molecular responses that differentiate symptomatic and asymptomatic Influenza A infection, we inoculated 17 healthy adults with live influenza (H3N2/Wisconsin) and examined changes in host peripheral blood gene expression at 16 timepoints over 132 hours. Here we present distinct transcriptional dynamics of host responses unique to asymptomatic and symptomatic infections. We show that symptomatic hosts invoke, simultaneously, multiple pattern recognition receptors-mediated antiviral and inflammatory responses that may relate to virus-induced oxidative stress. In contrast, asymptomatic subjects tightly regulate these responses and exhibit elevated expression of genes that function in antioxidant responses and cell-mediated responses. We reveal an ab initio molecular signature that strongly correlates to symptomatic clinical disease and biomarkers whose expression patterns best discriminate early from late phases of infection. Our results establish a temporal pattern of host molecular responses that differentiates symptomatic from asymptomatic infections and reveals an asymptomatic host-unique non-passive response signature, suggesting novel putative molecular targets for both prognostic assessment and ameliorative therapeutic intervention in seasonal and pandemic influenza.

Gene expression signatures diagnose influenza and other symptomatic respiratory viral infections in humans.

Acute respiratory infections (ARIs) are a common reason for seeking medical attention, and the threat of pandemic influenza will likely add to these numbers. Using human viral challenge studies with live rhinovirus, respiratory syncytial virus, and influenza A, we developed peripheral blood gene expression signatures that distinguish individuals with symptomatic ARIs from uninfected individuals with >95% accuracy. We validated this "acute respiratory viral" signature-encompassing genes with a known role in host defense against viral infections-across each viral challenge. We also validated the signature in an independently acquired data set for influenza A and classified infected individuals from healthy controls with 100% accuracy. In the same data set, we could also distinguish viral from bacterial ARIs (93% accuracy). These results demonstrate that ARIs induce changes in human peripheral blood gene expression that can be used to diagnose a viral etiology of respiratory infection and triage symptomatic individuals.

Loss of hPot1 function leads to telomere instability and a cut-like phenotype.

The human telomere binding protein hPot1 binds to the most distal single-stranded extension of telomeric DNA in vitro, and probably in vivo, as well as associating with the double-stranded telomeric DNA binding proteins TRF1 and TRF2 through the bridging proteins PTOP (also known as PIP1 or TINT1) and TIN2. Disrupting either the DNA binding activity of hPot1 or its association with PTOP results in elongated telomeres, suggesting a role for hPot1 in telomere length regulation. However, mutations to POT1 and Cdc13p, the fission and budding yeast genes encoding the structural orthologs of this protein, leads to telomere instability and cell death. Thus, it is possible that the hPot1 protein may also serve to cap and protect telomeres in humans. Indeed, we now find that knocking down the expression of hPot1 in human cells causes apoptosis or senescence, as well as an increase in telomere associations and anaphase bridges, telltale signs of telomere instability. In addition, knockdown cells also displayed chromatin bridges between interphase cells, reminiscent of the cut phenotype that was first described in fission yeast and in which cytokinesis progresses despite a failure of chromatid separation. However, unlike the yeast cut phenotypes, we suggest that the cut-like phenotype observed in hPot1 knockdown cells is a consequence of the fusion of chromosome ends and that this fusion impedes proper chromosomal segregation. We conclude that hPot1 protects chromosome ends from illegitimate recombination, catastrophic chromosome instability, and abnormal chromosome segregation.

HPV-16 E6/7 immortalization sensitizes human keratinocytes to ultraviolet B by altering the pathway from caspase-8 to caspase-9-dependent apoptosis.

UVB from solar radiation is both an initiating and promoting agent for skin cancer. We have found that primary human keratinocytes undergo an apoptotic response to UVB. To determine whether these responses are altered during the course of immortalization, we examined markers of apoptosis in primary human foreskin keratinocytes (HFK) transduced with either a retroviral vector expressing the E6 and E7 genes of HPV-16 or with empty vector alone (LXSN-HFK). Whereas LXSN-HFK as well as early passage keratinocytes expressing HPV-16 E6 and E7 (p7 E6/7-HFK) were both moderately responsive to UVB irradiation, late passage-immortalized keratinocytes (p27 E6/7-HFK) were exquisitely sensitive to UVB-induced apoptosis. After exposure to UVB, enhanced annexin V-positivity and internucleosomal DNA fragmentation were observed in p27 E6/7-HFK compared with either LXSN- or p7 E6/7-HFK. Caspase-3 fluorometric activity assays as well as immunoblot analysis with antibodies to caspase-3 and poly(ADP-ribose) polymerase revealed elevated caspase-3 activity and processing at lower UVB doses in p27 E6/7-HFK compared with LXSN- or p7 E6/7-HFK. In addition, the caspase inhibitor DEVD-CHO reduced the apoptotic response and increased survival of all three HFK types. Immunoblot analysis revealed that caspase-8 was activated in all three cell types, but caspase-9 was only activated in p27 E6/7-HFK. Cell cycle analysis further showed that only p27 E6/7-HFK exhibit G(2)/M accumulation that is enhanced by UVB treatment. This accumulation was associated with a rapid down-regulation of Bcl-2 in these cells. The immortalization process subsequent to the expression of HPV E6 and E7 may therefore determine UVB sensitivity by switching the mode of apoptosis from a caspase-8 to a Bcl-2-caspase-9-mediated pathway of apoptosis.