Human basal-like breast cancer is represented by one of the two mammary tumor subtypes in dogs.

BACKGROUND: About 20% of breast cancers in humans are basal-like, a subtype that is often triple-negative and difficult to treat. An effective translational model for basal-like breast cancer is currently lacking and urgently needed. To determine whether spontaneous mammary tumors in pet dogs could meet this need, we subtyped canine mammary tumors and evaluated the dog-human molecular homology at the subtype level. METHODS: We subtyped 236 canine mammary tumors from 3 studies by applying various subtyping strategies on their RNA-seq data. We then performed PAM50 classification with canine tumors alone, as well as with canine tumors combined with human breast tumors. We identified feature genes for human BLBC and luminal A subtypes via machine learning and used these genes to repeat canine-alone and cross-species tumor classifications. We investigated differential gene expression, signature gene set enrichment, expression association, mutational landscape, and other features for dog-human subtype comparison. RESULTS: Our independent genome-wide subtyping consistently identified two molecularly distinct subtypes among the canine tumors. One subtype is mostly basal-like and clusters with human BLBC in cross-species PAM50 and feature gene classifications, while the other subtype does not cluster with any human breast cancer subtype. Furthermore, the canine basal-like subtype recaptures key molecular features (e.g., cell cycle gene upregulation, TP53 mutation) and gene expression patterns that characterize human BLBC. It is enriched in histological subtypes that match human breast cancer, unlike the other canine subtype. However, about 33% of canine basal-like tumors are estrogen receptor negative (ER-) and progesterone receptor positive (PR+), which is rare in human breast cancer. Further analysis reveals that these ER-PR+ canine tumors harbor additional basal-like features, including upregulation of genes of interferon-γ response and of the Wnt-pluripotency pathway. Interestingly, we observed an association of PGR expression with gene silencing in all canine tumors and with the expression of T cell exhaustion markers (e.g., PDCD1) in ER-PR+ canine tumors. CONCLUSIONS: We identify a canine mammary tumor subtype that molecularly resembles human BLBC overall and thus could serve as a vital translational model of this devastating breast cancer subtype. Our study also sheds light on the dog-human difference in the mammary tumor histology and the hormonal cycle.

Human basal-like breast cancer is represented by one of the two mammary tumor subtypes in dogs.

Background: About 20% of breast cancers in humans are basal-like, a subtype that is often triple negative and difficult to treat. An effective translational model for basal-like breast cancer (BLBC) is currently lacking and urgently needed. To determine if spontaneous mammary tumors in pet dogs could meet this need, we subtyped canine mammary tumors and evaluated the dog-human molecular homology at the subtype level. Methods: We subtyped 236 canine mammary tumors from 3 studies by applying various subtyping strategies on their RNA-seq data. We then performed PAM50 classification with canine tumors alone, as well as with canine tumors combined with human breast tumors. We investigated differential gene expression, signature gene set enrichment, expression association, mutational landscape, and other features for dog-human subtype comparison. Results: Our independent genome-wide subtyping consistently identified two molecularly distinct subtypes among the canine tumors. One subtype is mostly basal-like and clusters with human BLBC in cross-species PAM50 classification, while the other subtype does not cluster with any human breast cancer subtype. Furthermore, the canine basal-like subtype recaptures key molecular features (e.g., cell cycle gene upregulation, TP53 mutation) and gene expression patterns that characterize human BLBC. It is enriched histological subtypes that match human breast cancer, unlike the other canine subtype. However, about 33% of canine basal-like tumors are estrogen receptor negative (ER-) and progesterone receptor positive (PR+), which is rare in human breast cancer. Further analysis reveals that these ER-PR+ canine tumors harbor additional basal-like features, including upregulation of genes of interferon-γ response and of the Wnt-pluripotency pathway. Interestingly, we observed an association of PGR expression with gene silencing in all canine tumors, and with the expression of T cell exhaustion markers (e.g., PDCD1 ) in ER-PR+ canine tumors. Conclusions: We identify a canine mammary tumor subtype that molecularly resembles human BLBC overall, and thus could serve as a vital spontaneous animal model of this devastating breast cancer subtype. Our study also sheds light on the dog-human difference in the mammary tumor histology and the hormonal cycle.

Development and internal validation of risk scores to diagnose infectious mononucleosis among college students.

BACKGROUND: Individual symptoms and signs of infectious mononucleosis (IM) are of limited value for diagnosis. OBJECTIVE: To develop and validate risk scores based on signs and symptoms with and without haematologic parameters for the diagnosis of IM. DESIGN AND SETTING: Data were extracted from electronic health records of a university health centre and were divided into derivation (9/1/2015-10/31/2017) and a prospective temporal internal validation (11/1/2017-1/31/2019) cohort. METHOD: Independent predictors for the diagnosis of IM were identified in univariate analysis using the derivation cohort. Logistic regression models were used to develop 2 risk scores: 1 with only symptoms and signs (IM-NoLab) and 1 adding haematologic parameters (IM-Lab). Point scores were created based on the regression coefficients, and patients were grouped into risk groups. Primary outcomes were area under the receiver operating characteristic curve (AUROCC) and classification accuracy. RESULTS: The IM-NoLab model had 4 predictors and identified a low-risk group (7.9% with IM) and a high-risk group (22.2%) in the validation cohort. The AUROCC was 0.75 in the derivation cohort and 0.69 in the validation cohort. The IM-Lab model had 3 predictors and identified a low-risk group (3.6%), a moderate-risk group (12.5%), and a high-risk group (87.6%). The AUROCC was 0.97 in the derivation cohort and 0.93 in the validation cohort. CONCLUSION: We derived and internally validated the IM-NoLab and IM-Lab risk scores. The IM-Lab score in particular had very good discrimination and have the potential to reduce the need for diagnostic testing for IM.

Access and Utilization of Asthma Medications Among Patients Who Receive Care in Federally Qualified Health Centers.

OBJECTIVES: To describe access to and use of prescription asthma medications, and to assess factors associated with asthma exacerbation, healthcare utilization, and health status among asthma patients treated at Federally Qualified Health Centers. METHODS: This is a retrospective cross-sectional study. We analyzed data from the 2014 National Health Center Patient Survey. This data is publicly available from the Health Resources and Services Administration. Data was collected from patients receiving face-to-face care from health centers funded under Section 330 of the Public Health Service Act. Data from patients was collected between October 8, 2014, and April 17, 2015. We included adult participants who reported having a diagnosis of asthma and confirmed that they still have asthma. Association between explanatory variables (access to prescription medications and use of asthma controller medications) and outcome variables (asthma exacerbations, asthma hospitalizations or emergency department visits, and self-rated health) was assessed using multivariable regression analyses while adjusting for demographics. RESULTS: A total of 919 participants with asthma were included. Approximately 32% of the participants experienced delays in getting prescription medications, 26% were unable to get them, 60% experienced an asthma exacerbation last year, 48% rated their health as fair/poor, and 19% visited a hospital or an emergency department last year. Multivariable results showed that participants who were currently taking controller medications were more likely to have experienced an asthma exacerbation (OR = 4.02; 95% CI 1.91 to 8.45; P < .01), or visited a hospital or an emergency department (OR = 3.07; 95% CI 1.39 to 6.73; P < .01) in the last year compared with those who had never taken controller medications. Experiencing difficulties in accessing asthma medications was associated with lower self-rated health (ß = -.51; 95% CI -0.94 to -0.08; P = .02). CONCLUSIONS: Future interventions should seek to improve asthma patient care and health outcomes using innovative strategies that act at multiple levels of the healthcare system (eg, individual, interpersonal, community levels).

Sample size methods for evaluation of predictive biomarkers.

Treatment selection biomarkers are those that can be useful in guiding choice of therapy. Just as new therapies require evaluation in appropriately designed clinical trials to determine their benefit, therapy selection biomarkers require evaluation in appropriately designed studies. These studies may be prospective clinical trials or retrospective studies based on specimens stored from a completed clinical trial. Ideally, patient treatment assignments should be randomized, and consideration should be given to an appropriate sample size-either for prospective planning of a new study or access to a sufficient number of stored specimens. Here, we develop a novel sample size method for estimation of a confidence interval of specified average width, for an intuitively appealing previously proposed parameter that reflects the expected benefit of using biomarker-guided therapy relative to a standard-of-care therapy. The estimation approach combines Monte Carlo and regression to result in a procedure that performs well over a range of scenarios. Although derived under a specific Cox proportional hazards regression model, robustness to model violations is demonstrated by evaluation under accelerated failure time and cure models. The sample size method produces adequate or conservative sample size estimates under a range of scenarios. Computer code in R and C++, and applications for Mac and Windows are made available for implementation of the sample size estimation procedure. The method is applied to a real data setting and results discussed.

Evaluating biomarkers for treatment selection from reproducibility studies.

We consider evaluating new or more accurately measured predictive biomarkers for treatment selection based on a previous clinical trial involving standard biomarkers. Instead of rerunning the clinical trial with the new biomarkers, we propose a more efficient approach which requires only either conducting a reproducibility study in which the new biomarkers and standard biomarkers are both measured on a set of patient samples, or adopting replicated measures of the error-contaminated standard biomarkers in the original study. This approach is easier to conduct and much less expensive than studies that require new samples from patients randomized to the intervention. In addition, it makes it possible to perform the estimation of the clinical performance quickly, since there will be no requirement to wait for events to occur as would be the case with prospective validation. The treatment selection is assessed via a working model, but the proposed estimator of the mean restricted lifetime is valid even if the working model is misspecified. The proposed approach is assessed through simulation studies and applied to a cancer study.

Canine tumor mutational burden is correlated with TP53 mutation across tumor types and breeds.

Spontaneous canine cancers are valuable but relatively understudied and underutilized models. To enhance their usage, we reanalyze whole exome and genome sequencing data published for 684 cases of >7 common tumor types and >35 breeds, with rigorous quality control and breed validation. Our results indicate that canine tumor alteration landscape is tumor type-dependent, but likely breed-independent. Each tumor type harbors major pathway alterations also found in its human counterpart (e.g., PI3K in mammary tumor and p53 in osteosarcoma). Mammary tumor and glioma have lower tumor mutational burden (TMB) (median < 0.5 mutations per Mb), whereas oral melanoma, osteosarcoma and hemangiosarcoma have higher TMB (median ≥ 1 mutations per Mb). Across tumor types and breeds, TMB is associated with mutation of TP53 but not PIK3CA, the most mutated genes. Golden Retrievers harbor a TMB-associated and osteosarcoma-enriched mutation signature. Here, we provide a snapshot of canine mutations across major tumor types and breeds.

Time to blood, respiratory and urine culture positivity in the intensive care unit: Implications for de-escalation.

OBJECTIVES: Concern for late detection of bacterial pathogens is a barrier to early de-escalation efforts. The purpose of this study was to assess blood, respiratory and urine culture results at 72 h to test the hypothesis that early negative culture results have a clinically meaningful negative predictive value. METHODS: We retrospectively reviewed all patients admitted to the medical intensive care unit between March 2012 and July 2018 with blood cultures obtained. Blood, respiratory and urine culture results were assessed for time to positivity, defined as the time between culture collection and preliminary species identification. The primary outcome was the negative predictive value of negative blood culture results at 72 h. Secondary outcomes included sensitivity, specificity, positive predictive value and negative predictive value of blood, respiratory and urine culture results. RESULTS: The analysis included 1567 blood, 514 respiratory and 1059 urine cultures. Of the blood, respiratory and urine cultures ultimately positive, 90.3%, 76.2% and 90.4% were positive at 72 h. The negative predictive value of negative 72-h blood, respiratory and urine cultures were 0.99, 0.82 and 0.97, respectively. Antibiotic de-escalation had good specificity, positive predictive value and negative predictive value for finalized negative cultures. CONCLUSION: Negative blood and urine culture results at 72 h had a high negative predictive value. These findings have important ramifications for antimicrobial stewardship efforts and support protocolized re-evaluation of empiric antibiotic therapy at 72 h. Caution should be used in patients with clinically suspected pneumonia, since negative respiratory culture results at 72 h were weakly predictive of finalized negative cultures.

Using a Mobile Health Intervention (DOT Selfie) With Transfer of Social Bundle Incentives to Increase Treatment Adherence in Tuberculosis Patients in Uganda: Protocol for a Randomized Controlled Trial.

BACKGROUND: The World Health Organization's End TB Strategy envisions a world free of tuberculosis (TB)-free of deaths, disease, and suffering due to TB-by 2035. Nonadherence reduces cure rates, prolongs infectiousness, and contributes to the emergence of multidrug-resistant TB (MDR-TB). Moreover, MDR-TB is a growing, complex, and costly problem that presents a major obstacle to TB control. Directly observed therapy (DOT) for treatment adherence monitoring is the recommended standard; however, it is challenging to implement at scale because it is labor-intensive. Mobile health interventions can facilitate remote adherence monitoring and minimize the costs and inconveniences associated with standard DOT. OBJECTIVE: The study aims to evaluate the effectiveness of using video directly observed therapy (VDOT) plus incentives to improve medication adherence in TB treatment versus usual-care DOT in an African context. METHODS: The DOT Selfie study is an open-label, randomized controlled trial (RCT) with 2 parallel groups, in which 144 adult patients with TB aged 18-65 years will be randomly assigned to receive the usual-care DOT monitoring or VDOT as the intervention. The intervention will consist of a smartphone app, a weekly internet subscription, translated text message reminders, and incentives for those who adhere. The participant will use a smartphone to record and send time-stamped encrypted videos showing their daily medication ingestion. This video component will directly substitute the need for daily face-to-face meetings between the health provider and patients. We hypothesize that the VDOT intervention will be more effective because it allows patients to swallow their pills anywhere, anytime. Moreover, patients will receive mobile-phone-based "social bundle" incentives to motivate adherence to continued daily submission of videos to the health system. The health providers will log into a secured computer system to verify treatment adherence, document missed doses, investigate the reasons for missed doses, and follow prespecified protocol measures to re-establish medication adherence. The primary endpoint is the adherence level as measured by the fraction of expected doses observed over the treatment period. The main secondary outcome will be time-to-treatment completion in both groups. RESULTS: This study was funded in 2019. Enrollment began in July and is expected to be completed by November 2020. Data collection and follow-up are expected to be completed by June 2021. Results from the analyses based on the primary endpoint are expected to be submitted for publication by December 2021. CONCLUSIONS: This random control trial will be among the first to evaluate the effectiveness of VDOT within an African setting. The results will provide robust scientific evidence on the implementation and adoption of mobile health (mHealth) tools, coupled with incentives to motivate TB medication adherence. If successful, VDOT will apply to other low-income settings and a range of chronic diseases with lifelong treatment, such as HIV/AIDs. TRIAL REGISTRATION: ClinicalTrials.gov NCT04134689; http://clinicaltrials.gov/ct2/show/NCT04134689. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/18029.

Defining adequate contact for transmission of Mycobacterium tuberculosis in an African urban environment.

BACKGROUND: The risk of infection from respiratory pathogens increases according to the contact rate between the infectious case and susceptible contact, but the definition of adequate contact for transmission is not standard. In this study we aimed to identify factors that can explain the level of contact between tuberculosis cases and their social networks in an African urban environment. METHODS: This was a cross-sectional study conducted in Kampala, Uganda from 2013 to 2017. We carried out an exploratory factor analysis (EFA) in social network data from tuberculosis cases and their contacts. We evaluated the factorability of the data to EFA using the Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO). We used principal axis factoring with oblique rotation to extract and rotate the factors, then we calculated factor scores for each using the weighted sum scores method. We assessed construct validity of the factors by associating the factors with other variables related to social mixing. RESULTS: Tuberculosis cases (N = 120) listed their encounters with 1154 members of their social networks. Two factors were identified, the first named "Setting" captured 61% of the variance whereas the second, named 'Relationship' captured 21%. Median scores for the setting and relationship factors were 10.2 (IQR 7.0, 13.6) and 7.7 (IQR 6.4, 10.1) respectively. Setting and Relationship scores varied according to the age, gender, and nature of the relationship among tuberculosis cases and their contacts. Family members had a higher median setting score (13.8, IQR 11.6, 15.7) than non-family members (7.2, IQR 6.2, 9.4). The median relationship score in family members (9.9, IQR 7.6, 11.5) was also higher than in non-family members (6.9, IQR 5.6, 8.1). For both factors, household contacts had higher scores than extra-household contacts (p < .0001). Contacts of male cases had a lower setting score as opposed to contacts of female cases. In contrast, contacts of male and female cases had similar relationship scores. CONCLUSIONS: In this large cross-sectional study from an urban African setting, we identified two factors that can assess adequate contact between tuberculosis cases and their social network members. These findings also confirm the complexity and heterogeneity of social mixing.

Video directly observed therapy for supporting and monitoring adherence to tuberculosis treatment in Uganda: a pilot cohort study.

INTRODUCTION: Nonadherence to treatment remains an obstacle to tuberculosis (TB) control worldwide. The aim of this study was to evaluate the feasibility of using video directly observed therapy (VDOT) for supporting TB treatment adherence in Uganda. METHODS: From May to December 2018, we conducted a pilot cohort study at a TB clinic in Kampala City. We enrolled patients aged 18-65 years with ≥3 months remaining of their TB treatment. Participants were trained to use a smartphone app to record videos of medication intake and submit them to a secured system. Trained health workers logged into the system to watch the submitted videos. The primary outcome was adherence measured as the fraction of expected doses observed (FEDO). In a secondary analysis, we examined differences in FEDO by sex, age, phone ownership, duration of follow-up, reasons for missed videos and patients' satisfaction at study exit. RESULTS: Of 52 patients enrolled, 50 were analysed. 28 (56%) were male, the mean age was 31 years (range 19-50 years) and 35 (70%) owned smartphones. Of the 5150 videos expected, 4231 (82.2%) were received. The median FEDO was 85% (interquartile range 66%-94%) and this significantly differed by follow-up duration. Phone malfunction, uncharged battery and VDOT app malfunctions were the commonest reasons for missed videos. 92% of patients reported being very satisfied with using VDOT. CONCLUSION: VDOT was feasible and acceptable for monitoring and supporting TB treatment. It resulted in high levels of adherence, suggesting that digital technology holds promise in improving patient monitoring in Uganda.

Diet-regulated behavior: FVB/N mice fed a lean diet exhibit increased nocturnal bouts of aggression between littermates.

The hyperactive FVB/N inbred mouse strain is widely used for transgenic research applications, although rarely for behavioral studies. These mice have visual impairments via retinal degeneration, but are considered highly intelligent and rely largely on olfaction. While investigating diet-induced obesity in autotaxin transgenic FVB/N mice, we observed an increase in the necessity for male, but not female, cage separations. Based on the observations, we hypothesized that feeding FVB/N mice a lean diet increases nocturnal bouts of aggression between male littermates. The diets of adult littermates were switched from normal chow to either ad libitum high-fat (45% fat) or lean (10% fat) matched diets for 27 weeks, whereby the mice reached an average of 43 g versus 35 g, respectively. Then, cage separations due to nocturnal bouts of aggression became mandatory, even though littermates peacefully cohabitated for 10-16 weeks previously. Since the data was of an unusual nature, it required uncommon statistical methods to be engendered to evaluate whether and where significance existed. Therefore, utilizing the randomization and population models, we established a methodology and postulated that either testosterone, the autotaxin transgene or diet alteration was the causal factor. Statistical evaluation demonstrated a significant correlation between cage separations and aggressive behavior associated with the lean-diet-fed mice, not autotaxin. Biochemical data did not appear to explain the behavior. In contrast, energy metabolism highlighted differences between the groups of normally hyperactive mice by diet. This characteristic makes FVB/N male mice unsuitable subjects for long-term studies with lean-diet modifications.

SEG - A Software Program for Finding Somatic Copy Number Alterations in Whole Genome Sequencing Data of Cancer.

As next-generation sequencing technology advances and the cost decreases, whole genome sequencing (WGS) has become the preferred platform for the identification of somatic copy number alteration (CNA) events in cancer genomes. To more effectively decipher these massive sequencing data, we developed a software program named SEG, shortened from the word "segment". SEG utilizes mapped read or fragment density for CNA discovery. To reduce CNA artifacts arisen from sequencing and mapping biases, SEG first normalizes the data by taking the log2-ratio of each tumor density against its matching normal density. SEG then uses dynamic programming to find change-points among a contiguous log2-ratio data series along a chromosome, dividing the chromosome into different segments. SEG finally identifies those segments having CNA. Our analyses with both simulated and real sequencing data indicate that SEG finds more small CNAs than other published software tools.

Autotaxin exacerbates tumor progression by enhancing MEK1 and overriding the function of miR-489-3p.

Upregulated expression of autotaxin, a secreted phospholipase and phosphodiesterase enzyme, appears in malignant disease. The identification of a circulating miRNA signature should distinguish autotaxin-mediated disease and also elucidate unknown molecular mechanisms that rationalize its malignant potential. Using female transgenic 'AT-ATX' mice, whereby human wild-type autotaxin is expressed in liver under the control of the alpha-1 antitrypsin promoter, transgenic animals express augmented autotaxin in circulation and a percentage develop tumors. Serum collected at necropsy had circulating miRNAs analyzed for statistical significance. The ensuing autotaxin-mediated miRNome differentiated between groups: healthy FVB/N mice versus AT-ATX mice with and without tumors. Intriguingly, miR-489-3p was sharply increased in AT-ATX tumor-bearing mice. Tissue analysis showed a correlation between miR-489-3p expression in tumors and surrounding milieu with autotaxin concentration in circulation. Sequence alignment suggested miR-489-3p targets MEK1, which was confirmed through in vitro studies. Exogenously added miR-489-3p, which decreases MEK1 in normal cells, dramatically increased MEK1 expression in cells stably expressing autotaxin. Taken together, this suggests that autotaxin overrides the normal regulatory function of miR-489-3p to inhibit MEK1 via coordinately increased miR-489-3p appearing in serum.

Validation of biomarkers to predict response to immunotherapy in cancer: Volume I - pre-analytical and analytical validation.

Immunotherapies have emerged as one of the most promising approaches to treat patients with cancer. Recently, there have been many clinical successes using checkpoint receptor blockade, including T cell inhibitory receptors such as cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) and programmed cell death-1 (PD-1). Despite demonstrated successes in a variety of malignancies, responses only typically occur in a minority of patients in any given histology. Additionally, treatment is associated with inflammatory toxicity and high cost. Therefore, determining which patients would derive clinical benefit from immunotherapy is a compelling clinical question. Although numerous candidate biomarkers have been described, there are currently three FDA-approved assays based on PD-1 ligand expression (PD-L1) that have been clinically validated to identify patients who are more likely to benefit from a single-agent anti-PD-1/PD-L1 therapy. Because of the complexity of the immune response and tumor biology, it is unlikely that a single biomarker will be sufficient to predict clinical outcomes in response to immune-targeted therapy. Rather, the integration of multiple tumor and immune response parameters, such as protein expression, genomics, and transcriptomics, may be necessary for accurate prediction of clinical benefit. Before a candidate biomarker and/or new technology can be used in a clinical setting, several steps are necessary to demonstrate its clinical validity. Although regulatory guidelines provide general roadmaps for the validation process, their applicability to biomarkers in the cancer immunotherapy field is somewhat limited. Thus, Working Group 1 (WG1) of the Society for Immunotherapy of Cancer (SITC) Immune Biomarkers Task Force convened to address this need. In this two volume series, we discuss pre-analytical and analytical (Volume I) as well as clinical and regulatory (Volume II) aspects of the validation process as applied to predictive biomarkers for cancer immunotherapy. To illustrate the requirements for validation, we discuss examples of biomarker assays that have shown preliminary evidence of an association with clinical benefit from immunotherapeutic interventions. The scope includes only those assays and technologies that have established a certain level of validation for clinical use (fit-for-purpose). Recommendations to meet challenges and strategies to guide the choice of analytical and clinical validation design for specific assays are also provided.

Validation of biomarkers to predict response to immunotherapy in cancer: Volume II - clinical validation and regulatory considerations.

There is growing recognition that immunotherapy is likely to significantly improve health outcomes for cancer patients in the coming years. Currently, while a subset of patients experience substantial clinical benefit in response to different immunotherapeutic approaches, the majority of patients do not but are still exposed to the significant drug toxicities. Therefore, a growing need for the development and clinical use of predictive biomarkers exists in the field of cancer immunotherapy. Predictive cancer biomarkers can be used to identify the patients who are or who are not likely to derive benefit from specific therapeutic approaches. In order to be applicable in a clinical setting, predictive biomarkers must be carefully shepherded through a step-wise, highly regulated developmental process. Volume I of this two-volume document focused on the pre-analytical and analytical phases of the biomarker development process, by providing background, examples and "good practice" recommendations. In the current Volume II, the focus is on the clinical validation, validation of clinical utility and regulatory considerations for biomarker development. Together, this two volume series is meant to provide guidance on the entire biomarker development process, with a particular focus on the unique aspects of developing immune-based biomarkers. Specifically, knowledge about the challenges to clinical validation of predictive biomarkers, which has been gained from numerous successes and failures in other contexts, will be reviewed together with statistical methodological issues related to bias and overfitting. The different trial designs used for the clinical validation of biomarkers will also be discussed, as the selection of clinical metrics and endpoints becomes critical to establish the clinical utility of the biomarker during the clinical validation phase of the biomarker development. Finally, the regulatory aspects of submission of biomarker assays to the U.S. Food and Drug Administration as well as regulatory considerations in the European Union will be covered.

Differential Toxicities of Nickel Salts to the Nematode Caenorhabditis elegans.

This study focused on assessing whether nickel (Ni) toxicity to the nematode Caenorhabditis elegans was affected by the molecular structure of the Ni salt used. Nematodes were exposed to seven Ni salts [Ni sulfate hexahydrate (NiSO4·6H2O), Ni chloride hexahydrate (NiCl2·6H2O), Ni acetate tetrahydrate (Ni(OCOCH3)2·4H2O), Ni nitrate hexahydrate (N2NiO6·6H2O), anhydrous Ni iodide (NiI2), Ni sulfamate hydrate (Ni(SO3NH2)2·H2O), and Ni fluoride tetrahydrate (NiF2·4H2O)] in an aquatic medium for 24 h, and lethality curves were generated and analyzed. Ni fluoride, Ni iodide, and Ni chloride were most toxic to C. elegans, followed by Ni nitrate, Ni sulfamate, Ni acetate, and Ni sulfate. The LC50 values of the halogen-containing salts were statistically different from the corresponding value of the least toxic salt, Ni sulfate. This finding is consistent with the expected high bioavailability of free Ni ions in halide solutions. We recommend that the halide salts be used in future Ni testing involving aquatic invertebrates.

Erratum to: Immune monitoring technology primer.

[This corrects the article DOI: 10.1186/s40425-015-0086-9.].

Immune monitoring technology primer.

BACKGROUND: Recent biotechnological developments have resulted in increasing interest in immunology biomarkers. These biomarkers have potential clinical utility in the near future as predictors of treatment response. Hence, clinical validation of these predictive markers is critical. FINDINGS: The process of clinically validating a predictive biomarker is reviewed. Validation of a predictive biomarker requires quantifying the strength of a statistical interaction between marker and a treatment. Different study designs are considered. CONCLUSIONS: Clinical validation of immunology biomarkers can be demanding both in terms of time and resources, and careful planning and study design are critical.