Reconstruct recent multi-population migration history by using identical-by-descent sharing

Identical-by-descent (IBD) is a fundamental genomic characteristic in population genetics and has been widely used for population history reconstruction. However, limited by the nature of IBD, which could only capture the relationship between two individuals/haplotypes, existing IBD-based history inference is constrained to two populations. In this study, we propose a novel framework by leveraging IBD sharing in multi-population and develop a method, MatrixIBD, to reconstruct recent multi-population migration history. Specifically, we employ the structured coalescent theory to precisely model the genealogical process and then estimate the IBD sharing across multiple populations. Within our model, we establish a theoretical connection between migration history and IBD sharing. Our method is rigorously evaluated through simulations, revealing its remarkable accuracy and robustness. Furthermore, we apply MatrixIBD to Central and South Asia in the Human Genome Diversity Project and successfully reconstruct the recent migration history of three closely related populations in South Asia. By taking into account the IBD sharing across multiple populations simultaneously, MatrixIBD enables us to attain clearer and more comprehensive insights into the history of regions characterized by complex migration dynamics. This approach provides a holistic perspective on intricate patterns embedded within the recent population migration history.

Artificial intelligence diagnostic model for multi-site fracture X-ray images of extremities based on deep convolutional neural networks

Background

The rapid and accurate diagnosis of fractures is crucial for timely treatment of trauma patients. Deep learning, one of the most widely used forms of artificial intelligence (AI), is now commonly employed in medical imaging for fracture detection. This study aimed to construct a deep learning model using big data to recognize multiple-fracture X-ray images of extremity bones.

Methods

Radiographic imaging data of extremities were retrospectively collected from five hospitals between January 2017 and September 2020. The total number of people finally included was 25,635 and the total number of images included was 26,098. After labeling the lesions, the randomized method used 90% of the data as the training set to develop the fracture detection model, and the remaining 10% was used as the validation set to verify the model. The faster region convolutional neural networks (R-CNN) algorithm was adopted to construct diagnostic models for detection. The Dice coefficient was used to evaluate the image segmentation accuracy. The performances of detection models were evaluated with sensitivity, specificity, and area under the receiver operating characteristic curve (AUC).

Results

The free-response receiver operating characteristic (FROC) curve value was 0.886 and 0.843 for the detection of single and multiple fractures, respectively. Additionally, the effective identification AUC for all parts was higher than 0.920. Notably, the AUC for wrist fractures reached 0.952. The average accuracy in detecting bone fracture regions in the extremities was 0.865. When analyzing single and multiple lesions at the patient level, the sensitivity was 0.957 for patients with multiple lesions and 0.852 for those with single lesions. In the segmentation task, the training set (the data set used by the machine learning model to train and learn) and the validation set (the data set used to evaluate the performance of the model) reached 0.996 and 0.975, respectively.

Conclusions

The faster R-CNN training algorithm exhibits excellent performance in simultaneously identifying fractures in the hands, feet, wrists, ankles, radius and ulna, and tibia and fibula on X-ray images. It demonstrates high accuracy, low false-negative rates, and controllable false-positive rates. It can serve as a valuable screening tool.

Revolutionizing vascular imaging: trends and future directions of 4D flow MRI based on a 20-year bibliometric analysis

Background

Four-dimensional flow magnetic resonance imaging (4D flow MRI) is a promising new technology with potential clinical value in hemodynamic quantification. Although an increasing number of articles on 4D flow MRI have been published over the past decades, few studies have statistically analyzed these published articles. In this study, we aimed to perform a systematic and comprehensive bibliometric analysis of 4D flow MRI to explore the current hotspots and potential future directions.

Methods

The Web of Science Core Collection searched for literature on 4D flow MRI between 2003 and 2022. CiteSpace was utilized to analyze the literature data, including co-citation, cooperative network, cluster, and burst keyword analysis.

Results

A total of 1,069 articles were extracted for this study. The main research hotspots included the following: quantification and visualization of blood flow in different clinical settings, with keywords such as "cerebral aneurysm", "heart", "great vessel", "tetralogy of Fallot", "portal hypertension", and "stiffness"; optimization of image acquisition schemes, such as "resolution" and "reconstruction"; measurement and analysis of flow components and patterns, as indicated by keywords "pattern", "KE", "WSS", and "fluid dynamics". In addition, international consensus for metrics derived from 4D flow MRI and multimodality imaging may also be the future research direction.

Conclusions

The global domain of 4D flow MRI has grown over the last 2 decades. In the future, 4D flow MRI will evolve towards becoming a relatively short scan duration with adequate spatiotemporal resolution, expansion into the diagnosis and treatment of vascular disease in other related organs, and a shift in focus from vascular structure to function. In addition, artificial intelligence (AI) will assist in the clinical promotion and application of 4D flow MRI.

A Retrospective Study on COVID-19 Infections Caused by Omicron Variant with Clinical, Epidemiological, and Viral Load Evaluations in Breakthrough Infections

Purpose: To explore the clinical, epidemiological, and viral load characteristics of COVID-19 caused by the omicron variant. Methods: Based on the COVID-19 epidemic caused by SARS-CoV-2 Omicron BA.2 broke out in Shanghai, China. To analyze whether there is any association between clinical symptoms and viral load of COVID-19 with age, sex, and combined disease and whether the clinical symptoms and viral load are associated with vaccine-breakthrough infections. Results: The most common symptoms were cough, expectoration, and fatigue, which were more common in women than males (p < 0.001). The average viral clearance time in the > 75 years group was the longest (6.64 days). The viral load in the 60-75 years group was significantly higher than that in the other groups (p < 0.001). The 18-45 years old group had the most clinical symptoms at admission (45.39%). The days of nucleic acid-negative conversion, average viral load, highest viral load, and clinical symptoms in comorbid chronic disease patients are longer (p < 0.001). The average and highest viral loads in the unvaccinated group were longer than those in the vaccine breakthrough infection groups (p < 0.001). However, the clinical symptoms in the vaccine breakthrough infection group were significantly more severe than those in the unvaccinated group (p < 0.001). Conclusions: We found that female patients, the elderly, and those with underlying comorbidities had longer clinical positive symptoms and viral loads. Although vaccination may not reduce clinical symptoms, it can shorten the viral load and the time required for virus clearance.

Pneumonia-Plus: a deep learning model for the classification of bacterial, fungal, and viral pneumonia based on CT tomography

OBJECTIVES

This study aims to develop a deep learning algorithm, Pneumonia-Plus, based on computed tomography (CT) images for accurate classification of bacterial, fungal, and viral pneumonia.

METHODS

A total of 2763 participants with chest CT images and definite pathogen diagnosis were included to train and validate an algorithm. Pneumonia-Plus was prospectively tested on a nonoverlapping dataset of 173 patients. The algorithm's performance in classifying three types of pneumonia was compared to that of three radiologists using the McNemar test to verify its clinical usefulness.

RESULTS

Among the 173 patients, area under the curve (AUC) values for viral, fungal, and bacterial pneumonia were 0.816, 0.715, and 0.934, respectively. Viral pneumonia was accurately classified with sensitivity, specificity, and accuracy of 0.847, 0.919, and 0.873. Three radiologists also showed good consistency with Pneumonia-Plus. The AUC values of bacterial, fungal, and viral pneumonia were 0.480, 0.541, and 0.580 (radiologist 1: 3-year experience); 0.637, 0.693, and 0.730 (radiologist 2: 7-year experience); and 0.734, 0.757, and 0.847 (radiologist 3: 12-year experience), respectively. The McNemar test results for sensitivity showed that the diagnostic performance of the algorithm was significantly better than that of radiologist 1 and radiologist 2 (p < 0.05) in differentiating bacterial and viral pneumonia. Radiologist 3 had a higher diagnostic accuracy than the algorithm.

CONCLUSIONS

The Pneumonia-Plus algorithm is used to differentiate between bacterial, fungal, and viral pneumonia, which has reached the level of an attending radiologist and reduce the risk of misdiagnosis. The Pneumonia-Plus is important for appropriate treatment and avoiding the use of unnecessary antibiotics, and provide timely information to guide clinical decision-making and improve patient outcomes.

CLINICAL RELEVANCE STATEMENT

Pneumonia-Plus algorithm could assist in the accurate classification of pneumonia based on CT images, which has great clinical value in avoiding the use of unnecessary antibiotics, and providing timely information to guide clinical decision-making and improve patient outcomes.

KEY POINTS

• The Pneumonia-Plus algorithm trained from data collected from multiple centers can accurately identify bacterial, fungal, and viral pneumonia. • The Pneumonia-Plus algorithm was found to have better sensitivity in classifying viral and bacterial pneumonia in comparison to radiologist 1 (5-year experience) and radiologist 2 (7-year experience). • The Pneumonia-Plus algorithm is used to differentiate between bacterial, fungal, and viral pneumonia, which has reached the level of an attending radiologist.

Pre-Existing Allergies Patients with Higher Viral Load and Longer Recovery Days Infected by SARS-CoV-2 Omicron BA.2 in Shanghai, China, 2022

Background

It is not known whether the viral load and the number of days to negative nucleic acid increased in patients with a history of allergy during the COVID-19 pandemic.

Objective

To investigate the impact of allergy labels on SARS-CoV-2 Omicron outcomes.

Methods

This retrospective cohort study included 62,293 patients with mild Omicron infection between April 9, 2022, and May 31, 2022. Using 1:2 propensity score matching, we identified 2177 COVID-19 patients with a history of allergy and 4254 COVID-19 patients with no history of allergy. The differences in viral load, days to nucleic acid turning negative, and clinical symptoms were compared between the two groups.

Results

Compared with the group with no allergies, the number of days before negative nucleic acid conversion of COVID-19 patients with allergies was significantly higher, the viral load was significantly higher, and the cumulative negative conversion rates at 5-10 days were all lower (p < 0.01). Patients with a history of allergy to antibiotics had higher viral load and more days with negative nucleic acid levels (p < 0.001). Subgroup analysis revealed that the viral load in penicillin-allergic and cephalosporins-allergic patients was significantly compared to patients without any history of allergies (p < 0.05).

Conclusion

Patients with a history of allergy have a more significant viral load and a longer duration of nucleic acid negative conversion upon COVID-19 infection, particularly those allergic to antibiotics.

Omicron variant of SARS-COV-2 in Shanghai: Clinical features and inactivated vaccine efficacy in 13,120 elderly patients

Background: Few reports concerning inactivated vaccine efficacy in elderly patients with Omicron infection. We aimed at demonstrating the clinical characteristics of elderly patients with mild disease and assessing the protective effect of the vaccine preliminarily. Methods: 13,120 mild patients who aged beyond 60 years old were included in this study totally, medical records were collected and analyzed. Results: Patients beyond 60 years had more chronic comorbidities, significantly lower ORF1ab and N gene CT values, and longer time of nucleic acid conversion than other age groups. Higher CT value of ORF1ab and N gene were found in older patients who received a booster dose of vaccine than in those who received two doses. The time of nucleic acid conversion was longest in unvaccinated old patients, with a decreasing trend from those who received two doses to those who received a booster doses. We also used random forest and logistic regression to screen for factors strongly associated with nucleic acid conversion and to predict the time of nucleic acid conversion. Conclusion: For mild patients with Omicron infection, patients aged>60 years had mild clinical symptoms, higher viral loads, and longer time of nucleic acid conversion, when compared with younger patients. The inactivated SARS-CoV-2 vaccine provided effective protection among adults with omicron variant infection, and the effectiveness of three doses of the vaccine was greater than that of two doses of the vaccine. Special attention should be given to elderly patients.

A Deep Learning Model for the Diagnosis and Discrimination of Gram-Positive and Gram-Negative Bacterial Pneumonia for Children Using Chest Radiography Images and Clinical Information

Purpose

This study aimed to develop a deep learning model based on chest radiography (CXR) images and clinical data to accurately classify gram-positive and gram-negative bacterial pneumonia in children to guide the use of antibiotics.

Methods

We retrospectively collected CXR images along with clinical information for gram-positive (n=447) and gram-negative (n=395) bacterial pneumonia in children from January 1, 2016, to June 30, 2021. Four types of machine learning models based on clinical data and six types of deep learning algorithm models based on image data were constructed, and multi-modal decision fusion was performed.

Results

In the machine learning models, CatBoost, which only used clinical data, had the best performance; its area under the receiver operating characteristic curve (AUC) was significantly higher than that of the other models (P<0.05). The incorporation of clinical information improved the performance of deep learning models that relied solely on image-based classification. Consequently, AUC and F1 increased by 5.6% and 10.2% on average, respectively. The best quality was achieved with ResNet101 (model accuracy: 0.75, recall rate: 0.84, AUC: 0.803, F1: 0.782).

Conclusion

Our study established a pediatric bacterial pneumonia model that utilizes CXR and clinical data to accurately classify cases of gram-negative and gram-positive bacterial pneumonia. The results confirmed that the addition of image data to the convolutional neural network model significantly improved its performance. While the CatBoost-based classifier had greater advantages owing to a smaller dataset, the quality of the Resnet101 model trained using multi-modal data was comparable to that of the CatBoost model, even with a limited number of samples.

Distinguishing Renal Cell Carcinoma From Normal Kidney Tissue Using Mass Spectrometry Imaging Combined With Machine Learning

PURPOSE

Accurately distinguishing renal cell carcinoma (RCC) from normal kidney tissue is critical for identifying positive surgical margins (PSMs) during partial and radical nephrectomy, which remains the primary intervention for localized RCC. Techniques that detect PSM with higher accuracy and faster turnaround time than intraoperative frozen section (IFS) analysis can help decrease reoperation rates, relieve patient anxiety and costs, and potentially improve patient outcomes.

MATERIALS AND METHODS

Here, we extended our combined desorption electrospray ionization mass spectrometry imaging (DESI-MSI) and machine learning methodology to identify metabolite and lipid species from tissue surfaces that can distinguish normal tissues from clear cell RCC (ccRCC), papillary RCC (pRCC), and chromophobe RCC (chRCC) tissues.

RESULTS

From 24 normal and 40 renal cancer (23 ccRCC, 13 pRCC, and 4 chRCC) tissues, we developed a multinomial lasso classifier that selects 281 total analytes from over 27,000 detected molecular species that distinguishes all histological subtypes of RCC from normal kidney tissues with 84.5% accuracy. On the basis of independent test data reflecting distinct patient populations, the classifier achieves 85.4% and 91.2% accuracy on a Stanford test set (20 normal and 28 RCC) and a Baylor-UT Austin test set (16 normal and 41 RCC), respectively. The majority of the model's selected features show consistent trends across data sets affirming its stable performance, where the suppression of arachidonic acid metabolism is identified as a shared molecular feature of ccRCC and pRCC.

CONCLUSION

Together, these results indicate that signatures derived from DESI-MSI combined with machine learning may be used to rapidly determine surgical margin status with accuracies that meet or exceed those reported for IFS.

COVID-19 imaging, where do we go from here? Bibliometric analysis of medical imaging in COVID-19

OBJECTIVES

We conducted a systematic and comprehensive bibliometric analysis of COVID-19-related medical imaging to determine the current status and indicate possible future directions.

METHODS

This research provides an analysis of Web of Science Core Collection (WoSCC) indexed articles on COVID-19 and medical imaging published between 1 January 2020 and 30 June 2022, using the search terms "COVID-19" and medical imaging terms (such as "X-ray" or "CT"). Publications based solely on COVID-19 themes or medical image themes were excluded. CiteSpace was used to identify the predominant topics and generate a visual map of countries, institutions, authors, and keyword networks.

RESULTS

The search included 4444 publications. The journal with the most publications was European Radiology, and the most co-cited journal was Radiology. China was the most frequently cited country in terms of co-authorship, with the Huazhong University of Science and Technology being the institution contributing with the highest number of relevant co-authorships. Research trends and leading topics included: assessment of initial COVID-19-related clinical imaging features, differential diagnosis using artificial intelligence (AI) technology and model interpretability, diagnosis systems construction, COVID-19 vaccination, complications, and predicting prognosis.

CONCLUSIONS

This bibliometric analysis of COVID-19-related medical imaging helps clarify the current research situation and developmental trends. Subsequent trends in COVID-19 imaging are likely to shift from lung structure to function, from lung tissue to other related organs, and from COVID-19 to the impact of COVID-19 on the diagnosis and treatment of other diseases. Key Points • We conducted a systematic and comprehensive bibliometric analysis of COVID-19-related medical imaging from 1 January 2020 to 30 June 2022. • Research trends and leading topics included assessment of initial COVID-19-related clinical imaging features, differential diagnosis using AI technology and model interpretability, diagnosis systems construction, COVID-19 vaccination, complications, and predicting prognosis. • Future trends in COVID-19-related imaging are likely to involve a shift from lung structure to function, from lung tissue to other related organs, and from COVID-19 to the impact of COVID-19 on the diagnosis and treatment of other diseases.

A bibliometric analysis of the application of imaging in sleep in neurodegenerative disease

Objective

The purpose of this study was to examine the current state of the application of imaging in sleep research in degenerative disease, as well as hotspots and trends.

Materials and methods

A search was conducted on the Web of Science Core Collection (WoSCC) between 1 September 2012, and 31 August 2022 for literature related to sleep imaging. This study analyzed 7,679 articles published in this field over the past 10 years, using CiteSpace to analyze tendencies, countries, institutions, authors, and hotspots.

Results

There were 7,679 articles on the application of imaging to sleep research published by 566 institutions located in 135 countries in 1,428 journals; the number of articles was increasing on a yearly basis. According to keyword analysis, the research direction of the application of imaging in sleep research focused on the effects of degenerative diseases on sleep, such as Parkinson's disease, Alzheimer's disease, and small vessel disease. A literature evaluation found that Parkinson's disease, insomnia, sleep quality, and rapid eye movement sleep behavior disorder were the top research trends in this field.

Conclusion

A growing body of research has focused on sleep disorders caused by degenerative diseases. In the application of imaging to sleep research, magnetic resonance functional brain imaging represents a reliable research method. In the future, more aging-related diseases may be the subject of sleep-related research, and imaging could provide convenient and reliable evidence in this respect.

Regulation of Cell-Signaling Pathways by Berbamine in Different Cancers

Natural product research is a cornerstone of the architectural framework of clinical medicine. Berbamine is a natural, potent, pharmacologically active biomolecule isolated from Berberis amurensis. Berbamine has been shown to modulate different oncogenic cell-signaling pathways in different cancers. In this review, we comprehensively analyze how berbamine modulates deregulated pathways (JAK/STAT, CAMKII/c-Myc) in various cancers. We systematically analyze how berbamine induces activation of the TGF/SMAD pathway for the effective inhibition of cancer progression. We also summarize different nanotechnological strategies currently being used for proficient delivery of berbamine to the target sites. Berbamine has also been reported to demonstrate potent anti-cancer and anti-metastatic effects in tumor-bearing mice. The regulation of non-coding RNAs by berbamine is insufficiently studied, and future studies must converge on the identification of target non-coding RNAs. A better understanding of the regulatory role of berbamine in the modulation of non-coding RNAs and cell-signaling pathways will be advantageous in the effective translation of laboratory findings to clinically effective therapeutics.

Risk stratification and prognosis in pulmonary arterial hypertension: the Singapore experience

Funding Acknowledgements

Type of funding sources: None.

Aims & Background: Guidelines recommend the risk stratification of patients with pulmonary arterial hypertension (PAH) at baseline and on follow-up, so as to guide the management and titration of therapy in these patients.  This approach has been validated in various pulmonary hypertension registries in the West.  We aim to study the value of risk stratification on the prognosis of PAH patients in Asia.

Methods

A retrospective review of all PAH patients from 2002 to 2018 from a single tertiary cardiac centre was performed. Inclusion criteria was the availability of both initial visit and follow-up data. Patients were classified into low-, medium-, and high-risk groups in both initial and follow-up visits based on the variables in the 2015 ESC/ERS PH risk stratification table  according to the "score and average" method used by SPAHR and COMPERA registries (total score divided by number of variables assessed and rounded to nearest integer). An average score of 1, 2 and 3 was defined as low, medium and high risk respectively. The primary outcomes was all-cause mortality.

Results

 A total of 102 patients (mean age 57 ± 18 years old, 82 females) were included. Survival was significantly affected by PAH subtype and risk profile. On multivariate analysis, baseline risk did not impact on mortality. Follow-up risk stage impacted on prognosis, with significantly poorer prognosis noted in both intermediate- (adj HR 3.12, 95% CI 1.03 – 9.48, p = 0.045) and high-risk (adj HR = 7.84, 95% CI 2.22 – 27.64, p = 0.001) groups. Patients who improved their risk groups to low risk on follow-up had  similar survival to stable low-risk patients, but those patients whose risk group worsened on follow-up had significantly worse prognosis (adj HR = 5.44, 95% CI 1.26 – 13.75, p = 0.02).

Conclusion

Risk stratification is useful in prognosticating Asian PAH patients. There is potential survival benefit in optimising treatment to achieve a low-risk profile.

Drug resistance to targeted therapeutic strategies in non-small cell lung cancer

Rapidly developing molecular biology techniques have been employed to identify cancer driver genes in specimens from patients with non-small cell lung cancer (NSCLC). Inhibitors and antibodies that specifically target driver gene-mediated signaling pathways to suppress tumor growth and progression are expected to extend the survival time and further improve the quality of life of patients. However, the health of patients with advanced and metastatic NSCLC presents significant challenges due to treatment resistance, mediated by cancer driver gene alteration, epigenetic alteration, and tumor heterogeneity. In this review, we discuss two different resistance mechanisms in NSCLC targeted therapies, namely changes in the targeted oncogenes (on-target resistance) and changes in other related signaling pathways (off-target resistance) in tumor cells. We highlight the conventional mechanisms of drug resistance elicited by the complex heterogeneous microenvironment of NSCLC during targeted therapy, including mutations in epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), the receptor tyrosine kinase ROS proto-oncogene 1 (ROS1), and the serine/threonine-protein kinase BRAF (v-Raf murine sarcoma viral oncogene homolog B). We also discuss the mechanism of action of less common oncoproteins, as in-depth understanding of these molecular mechanisms is important for optimizing treatment strategies.

Response gene to complement-32 promotes cell survival via the NF-κB pathway in non-small-cell lung cancer

Response gene to complement (RGC)-32 regulates the cell cycle in response to complement activation. The present study demonstrated that the expression level of RGC-32 is higher in human non-small-cell lung cancer (NSCLC) tissues compared with health controls. Overexpressing RGC-32 induced p65 nucleus translocation, significantly increased nuclear p65 levels and promoted the proliferation of A549 cells. Knockdown of RGC-32 by short hairpin RNA decreased the expression level of nuclear p65 and inhibited cell proliferation. The increase in cell proliferation induced by RGC32 could be abolished by the NF-κB inhibitor pyrrolidine dithiocarbamate. Mechanistic studies indicated that RGC32 mediated NF-κB downstream genes, including vascular cell adhesion protein 1, interleukin-6, cyclin dependent kinase inhibitor 2C, testin and vascular endothelial growth factor A. In summary, the present study demonstrated a novel role of RGC-32 in the progression of NSCLC via the NF-κB pathway and p65. Therefore, RGC-32 could be a potential therapeutic target for NSCLC.

The DNA Repair Nuclease MRE11A Functions as a Mitochondrial Protector and Prevents T Cell Pyroptosis and Tissue Inflammation

In the autoimmune disease rheumatoid arthritis (RA), CD4+ T cells promote pro-inflammatory effector functions by shunting glucose away from glycolysis and ATP production. Underlying mechanisms remain unknown, and here we implicate the DNA repair nuclease MRE11A in the cells' bioenergetic failure. MRE11A deficiency in RA T cells disrupted mitochondrial oxygen consumption and suppressed ATP generation. Also, MRE11A loss of function caused leakage of mitochondrial DNA (mtDNA) into the cytosol, triggering inflammasome assembly, caspase-1 activation, and pyroptotic cell death. Caspase-1 activation was frequent in lymph-node-residing T cells in RA patients. In vivo, pharmacologic and genetic inhibition of MRE11A resulted in tissue deposition of mtDNA, caspase-1 proteolysis, and aggressive tissue inflammation. Conversely, MRE11A overexpression restored mitochondrial fitness and shielded tissue from inflammatory attack. Thus, the nuclease MRE11A regulates a mitochondrial protection program, and MRE11A deficiency leads to DNA repair defects, energy production, and failure and loss of tissue homeostasis.

[Discussion of correlation between histogram analysis of quantitative diffusion weighted imaging and Gleason score of prostate cancer]

Objective: To discuss the correlation between histogram analysis of quantitative mono-exponential, bi-exponential and diffusion kurtosis models in diffusion weighted imaging and the Gleason score of prostate cancer, and evaluate the application value and diagnostic efficiency in identifying low and high grade prostate cancer. Methods: A total of 50 patients with histologically confirmed as prostate cancer were examined from May 2015 to May 2016 in the Second Affiliated Hospital of Soochow University using DWI performed at 3.0 T with an extended b-value range from 0 to 2 000 s/mm(2). Data were post-processed by whole tumor histogram analysis,the ROI was manually drown in DWI (b=1 000 s/mm(2)) step by step along the outline of cancer, and quantitative analysis were performed respectively by mono-exponential, bi-exponential and diffusion kurtosis models for quantification of apparent diffusion coefficients (ADCs), diffusivity D, pseudo-diffusivity D(*), perfusion fraction f, diffusion coefficients by non-Gaussian distribution (D(k)) and kurtosis coefficient (K).Then the histogram analysis was performed to get the mean, median, 25th percentile, 75th percentile, skewness and kurtosis. The correlation between histogram analysis results of these quantitative parameters and Gleason score of prostate cancer were evaluated by Spearman correlation coefficient. The diagnostic performance of histogram analysis results of each quantitative parameters in identifying low (Gleason score≤6) and high (Gleason score>6) grade prostate cancer was performed by comparing the area under the ROC curve and the curve values. Results: The values of ADC, D and D(k) (mean, median, 25th, 75th) were negatively correlated with Gleason score of prostate cancer (r value was -0.388--0.624, P<0.05). The values of D (skewness and kurtosis) had a certain correlation with Gleason score of prostate cancer (r value were 0.413 and 0.402, P<0.05). The histogram analysis results of D(*) and f had no statistically significant correlation with Gleason score of prostate cancer (P>0.05). The values of K (mean, median, 25th, kurtosis) were positively correlated with Gleason score of prostate cancer (r value was 0.423-0.699,P<0.05). The diagnostic efficiency of histogram analysis results of these quantitative parameter values in identifying low and high grade prostate cancer showed that the ADC (median), D (25th), D(k) (mean) and K (25th) had a larger area under the curve, and were 0.844, 0.873, 0.815, and 0.919 respectively, the differences of area under the curve between any two of these parameters above were not statistically significant (all P>0.05). Conclusions: The quantitative parameters of three diffusion models (ADC, D, D(k), K) in DWI are all related to the Gleason score of prostate cancer, but in the differential diagnosis of low and high grade prostate cancer, the diagnostic efficacy of mono-exponential model is sufficient. The more complex model such as bi-exponential and diffusion kurtosis may complement it in other ways.

Nanoparticle systems for cancer vaccine

As effective tools for public health, vaccines prevent disease by priming the body's adaptive and innate immune responses against an infection. Due to advances in understanding cancers and their relationship with the immune system, there is a growing interest in priming host immune defenses for a targeted and complete antitumor response. Nanoparticle systems have shown to be promising tools for effective antigen delivery as vaccines and/or for potentiating immune response as adjuvants. Here, we highlight relevant physiological processes involved in vaccine delivery, review recent advances in the use of nanoparticle systems for vaccines and discuss pertinent challenges to viably translate nanoparticle-based vaccines and adjuvants for public use.

Nanoparticle-Laden Macrophages for Tumor-Tropic Drug Delivery

Macrophages hold great potential in cancer drug delivery because they can sense chemotactic cues and home to tumors with high efficiency. However, it remains a challenge to load large amounts of therapeutics into macrophages without compromising cell functions. This study reports a silica-based drug nanocapsule approach to solve this issue. The nanocapsule consists of a drug-silica complex filling and a solid silica sheath, and it is designed to minimally release drug molecules in the early hours of cell entry. While taken up by macrophages at high rates, the nanocapsules minimally affect cell migration in the first 6-12 h, buying time for macrophages to home to tumors and release drugs in situ. In particular, it is shown that doxorubicin (Dox) as a representative drug can be loaded into macrophages up to 16.6 pg per cell using this approach. When tested in a U87MG xenograft model, intravenously (i.v.) injected Dox-laden macrophages show comparable tumor accumulation as untreated macrophages. Therapy leads to efficient tumor growth suppression, while causing little systematic toxicity. This study suggests a new cell platform for selective drug delivery, which can be readily extended to the treatment of other types of diseases.

Role of microRNA-410 in molecular oncology: A double edged sword

MicroRNAs (miRNAs) are short non-coding single-stranded RNAs, which play significant roles in the regulation of a myriad of biological processes. Overwhelmingly increasing high-impact research has also deepened our understanding about the central role of miRNAs in cancer development, metastatic spread, and development of resistance against various drugs. Recent studies have identified miRNAs that regulate RNA expression/processing and posttranscriptional expression of important oncogenes and tumor suppressors. Rapidly emerging experimentally verified data have started to shed light on the significance of miRNAs as biomarkers for diagnostic, prognostic, and monitoring purposes. Next-generation sequencing and DNA microarray technologies have helped us tremendously in the identification of miRNA and mRNA signatures in different cancers and their subtypes on a genome-wide scale. It is being increasing realized that miRNAs have diametrically opposite roles in different cancers. miR-410 is context-dependently involved in positive and negative regulation of cancers. miR-410 negatively regulates BAK1, CETN3, and BRD7 to promote cancer. However, miR-410 effectively targetes c-MET, AGTR1, and SNAIL to suppress cancer. In this review, we will comprehensively summarize most recent evidence available related to the "split personality" of miR-410 in different cancers.

Abstract 3534: Protein acylation mediates encapsulation of Src kinase into exosomes

Exosomes are nanosized vesicles (30-150 nm) secreted from almost all cell types (1). Exosomes play important roles in cell-cell communication through the transfer of exosomal proteins, mRNA, and microRNAs, mediating immune escape and promoting tumor progression (2,3). However, it remains unclear how oncogenic proteins are selectively disseminated through exosomes. Myristoylation is lipid modification of protein involved in the attachment of N-terminal glycine of proteins with a myristoyl group. It is critical for various biologic functions including cell signaling, protein localization, and cell-cell communication (4). In this study, we evaluated the role of protein acylation for the encapsulation of Src family kinases in exosomes. Myristoylation promotes the enrichment of Src kinase in exosomes whereas palmitoylation inhibits the encapsulation process. Additionally, phosphorylated Src protein was more favored to be capsulated in exosomes. Mechanistically, knockdown of TSG101 decreased expression levels of Src kinase in exosomes, indicating that Src encapsulation into exosomes is associated with endosomal sorting complexes required for transport (ESCRT). Finally, Src kinase can be translocated to normal cells via exosomes cargo to induce pathologic signaling. These results provide new insights of Src kinase encapsulation mechanism into exosomes, and therapeutic approaches for inhibiting the transfer of oncogenic proteins through targeting protein myristoylation process.

References:

1. Simons M, Raposo G. Exosomes–vesicular carriers for intercellular communication. Curr Opin Cell Biol 2009;21(4):575-81.

2. Skog J et al. Glioblastoma microvesicles transport RNA and proteins that promote tumour growth and provide diagnostic biomarkers. Nature Cell Biol 2008;10(12):1470-6.

3. Abusamra AJ et al. Tumor exosomes expressing Fas ligand mediate CD8+ T-cell apoptosis. Blood Cells Mol Dis 2005;35(2):169-73.

4. Casey PJ. Protein lipidation in cell signaling. Science 1995;268(5208):221.

Citation Format: Ru Wen, Qianjin Li, Sungjin Kim, Yongjie Ma, Jin Xie, Houjian Cai. Protein acylation mediates encapsulation of Src kinase into exosomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3534.

The Platin-X series: activation, targeting, and delivery

Anticancer platinum (Pt) complexes have long been considered to be one of the biggest success stories in the history of medicinal inorganic chemistry. Yet there remains the hunt for the "magic bullet" which can satisfy the requirements of an effective chemotherapeutic drug formulation. Pt(iv) complexes are kinetically more inert than the Pt(ii) congeners and offer the opportunity to append additional functional groups/ligands for prodrug activation, tumor targeting, or drug delivery. The ultimate aim of functionalization is to enhance the tumor selective action and attenuate systemic toxicity of the drugs. Moreover, an increase in cellular accumulation to surmount the resistance of the tumor against the drugs is also of paramount importance in drug development and discovery. In this review, we will address the attempts made in our lab to develop Pt(iv) prodrugs that can be activated and delivered using targeted nanotechnology-based delivery platforms.

Core hydrophobicity tuning of a self-assembled particle results in efficient lipid reduction and favorable organ distribution

Atherosclerosis, the deadliest disease in the United States, arises due to the build up of plaques in the arteries as a result of excessive cholesterol deposition and an impaired cholesterol removal process. High density lipoproteins (HDL), popularly known as "good cholesterol", are naturally occurring nano-sized particles that, along with apolipoproteins, are deployed to maintain cholesterol homeostasis in the body. Both cholesterol efflux, from the fat-laden macrophages in the arteries, and intracellular lipid transport, to deliver cholesterol to the mitochondria of liver cells for metabolism, hold key responsibilities to maintain healthy lipid levels inside the body. We designed a library of nine mitochondria targeted polymer-lipid hybrid nanoparticles (NPs), comprised of completely synthetic yet biodegradable components, that are capable of performing HDL-like functions. Using this library, we optimized a superior mitochondria targeted NP candidate, which can show favourable organ distribution, therapeutic potential, and non-toxic properties. Two targeted NP formulations with optimum NP size, zeta potential, and cholesterol binding and release properties were identified. Lipid reduction and anti-oxidative properties of these two NPs demonstrated cholesterol removal ability. In vivo therapeutic evaluation of the targeted-NP formulations in apolipoprotein E knockout (apoE^-/^-) mice indicated lipid reduction and anti-inflammatory properties compared to non-targeted NPs. This synthetic targeted NP with potential abilities to participate in both extra- and intracellular cholesterol transport might potentiate therapeutic interventions for heart diseases.

[Preliminary applicability evaluation of Prostate Imaging Reporting and Data System version 2 diagnostic score in 3.0T multi-parameters magnetic resonance imaging combined with prostate specific antigen density for prostate cancer]

Objective: To investigate the preliminary applicability of Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) score in the condition of 3.0T multi-parametric magnetic resonance imaging (Mp-MRI) combined with clinical classic indicators for the diagnosis of prostate cancer (PCa). Methods: The clinical and MRI materials of 247 patients of suspicious prostate disease treated in Second Affiliated Hospital of Soochow University from June 2015 to November 2016 were analyzed retrospectively, including 110 cases with PCa and 137 cases without cancer.All cases underwent the high-resolution axial T(2)-weighted imaging (T(2)WI), diffusion weighted imaging (DWI) and dynamic contrast enhancement-magnetic resonance imaging (DCE-MRI) and were confirmed pathologically by puncture biopsies.The Mp-MRI materials of all cases were scored according to PI-RADS v2.The prostate volume and prostate specific antigen (PSA) density (PSAD) value were calculated according to the formulas.The univariate and multivariate analysis were performed for the observed indicators (age, prostate volume, PSA, PSAD and PI-RADS v2 score) to determine the independent predictors for PCa.Then, a Logistic regression model (combined prediction model) was established by the independent predictors for combined diagnosis of PCa.The receiver operating characteristic curve (ROC) curve analysis was performed to get the sensitivity and specificity of each independent predictor and the model to diagnose PCa.The differences of AUC values of each independent predictor and the model were compared with each other to evaluate the diagnostic performance for PCa. Results: The differences in the age, prostate volume, PSA, PSAD and the PI-RADS v2 score between patients with PCa and non-cancer group were all statistically significant (t=2.870, Z=-4.230, -7.787, -9.477, -10.826, all P<0.05). The PSAD and PI-RADS v2 score were independent predictors for PCa (OR=3.331, 10.546, both P<0.05). The Logistic regression combined prediction model by PI-RADS v2 score and PSAD to forecast PCa was Logit(P)=-5.097+ 2.309×PSAD+ 1.214×PI-RADS v2 score.The area under the curve (AUC) of ROC in the combined model (0.911) was higher than that in the PI-RADS v2 score (0.886) and PSAD (0.851) and the differences were all statistically significant (Z=2.416, 2.716, both P<0.05); but the difference in the AUC value between PI-RADS v2 score and PSAD was not statistically significant (Z=1.191, P=0.234). The diagnostic sensitivity of PSAD, PI-RADS v2 score and the model were: 0.891, 0.782 and 0.855, respectively; the specificity were 0.449, 0.912 and 0.847, respectively on their positive thresholds (0.15 μg·L(-1)·ml(-1,) 4 and -0.82). Conclusion: PI-RADS v2 score combined with PSAD in diagnosing PCa is superior to the single application of them and it can lead to high diagnostic sensitivity and specificity for PCa.

Role of targeting nanoparticles for cancer immunotherapy and imaging

Cancer immunotherapy involves the delivery of immunogenic compounds and/or the priming, or induction, of the body’s natural immune system to target cancer. The use of cancer immunotherapy has led to various means of cancer prevention and treatment that have produced prolonged life expectancy and stabilized disease. Nanoparticles are promising vehicles or adjuvants for effective delivery of therapeutics, antigens, stimulatory effectors, or antibodies for therapeutic invention. Targeting nanoparticles are especially useful due to their capability of accumulating in specific sites of interest like tumors and, thereby, decreasing risks of damage to normal tissue. Targeting can be achieved by incorporation of cell-surface related binding molecules or antibodies. This review explores the role of targeting nanoparticles as delivery or adjuvant sys­tems to modulate immune response; and as imaging tracking systems for cancer.

A novel redox regulator, MnTnBuOE-2-PyP5+, enhances normal hematopoietic stem/progenitor cell function

The signaling of reactive oxygen species (ROS) is essential for the maintenance of normal cellular function. However, whether and how ROS regulate stem cells are unclear. Here, we demonstrate that, in transgenic mice expressing the human manganese superoxide dismutase (MnSOD) gene, a scavenger of ROS in mitochondria, the number and function of mouse hematopoietic stem/progenitor cells (HSPC) under physiological conditions are enhanced. Importantly, giving MnTnBuOE-2-PyP⁵⁺(MnP), a redox- active MnSOD mimetic, to mouse primary bone marrow cells or to C57B/L6 mice significantly enhances the number of HSPCs. Mechanistically, MnP reduces superoxide to hydrogen peroxide, which activates intracellular Nrf2 signaling leading to the induction of antioxidant enzymes, including MnSOD and catalase, and mitochondrial uncoupling protein 3. The results reveal a novel role of ROS signaling in regulating stem cell function, and suggest a possible beneficial effect of MnP in treating pathological bone marrow cell loss and in increasing stem cell population for bone marrow transplantation.

A Prodrug of Two Approved Drugs, Cisplatin and Chlorambucil, for Chemo War Against Cancer

Cancer cells maintain normal mitochondrial glutathione as one of the defense mechanisms to inhibit mitochondrial membrane polarization and hence apoptosis. A combinational therapeutic modality Platin-Cbl, a prodrug of FDA-approved chemotherapeutic agents, cisplatin and chlorambucil (Cbl), was synthesized and characterized to explore the potential of this compound to initiate chemo war on cancer cells using the active drugs, cisplatin and Cbl, when delivered to the cellular power house mitochondrion using a targeted nanoparticle designed to get associated with this organelle. Platin-Cbl demonstrated significantly high cytotoxic activity across a number of tumor cell lines as well as in a cisplatin-resistant cancer cell line compared with cisplatin or its mixture with Cbl suggesting its unique potency in cisplatin-resistant tumors. A mitochondria-targeted nanoparticle formulation of Platin-Cbl allowed for its efficacious mitochondrial delivery. In vitro studies documented high potency of Platin-Cbl nanoparticle formulations. Cisplatin-resistant cells upon treatment with Platin-Cbl were still able to manage energy production to a certain extent via fatty acid pathway; the advantage of using T-Platin-Cbl-NP is that this nanoparticle treatment causes impairment of all metabolic pathways in cisplatin-resistant cells forcing the cells to undergo efficient apoptosis. This study highlights a combination of several beneficial effects for a cascade of events to overcome resistance associated with single drug therapy. Mol Cancer Ther; 16(4); 625-36. ©2017 AACR.

Turn up the cellular power generator with vitamin E analogue formulation

The down regulation of the cellular power generator, adenosine triphosphate (ATP) synthase, in various cancer cells plays an obstructive role in mitochondria-mediated cell death. Cancer cells up-regulate ATPase inhibitory factor 1 (IF1) and down-regulate β-F1-ATPase of ATP synthase to enhance aerobic glycolysis for tumor growth via inhibiting total ATP synthase activity in the oxidative phosphorylation (OXPHOS) pathway. Alpha-tocopheryl succinate (α-TOS), one of the most bioactive derivatives of vitamin E, can selectively induce apoptosis in numerous cancer cells. The cancer cell selective apoptosis inducing property of α-TOS is correlated to: mitochondrial destabilization, inhibition of anti-apoptotic B cell lymphoma 2 (Bcl2) and protein kinase C (PKC), caspase 3 activation, production of mitochondrial reactive oxygen species (ROS), and inhibition of succinate dehydrogenase activity of mitochondrial complex II, and interaction with complex I to some extent. There is no report which elucidates the effects of α-TOS on the cellular power generator, complex V or ATP synthase. Here, we report the activation of mitochondrial ATP synthase using a suitably designed chemical formulation of α-TOS for the first time. A mitochondria targeted α-TOS nanoparticle formulation demonstrated enhanced cytotoxicity and mitochondrial activities in cancer cells by inhibiting Bcl2 protein and activating ATP synthase. The modulation of ATP synthase in cancer cells by the engineered formulation of α-TOS can be promising for solid cancers with compromised ATP synthase.

Mitochondrion: A Promising Target for Nanoparticle-Based Vaccine Delivery Systems

Vaccination is one of the most popular technologies in disease prevention and eradication. It is promising to improve immunization efficiency by using vectors and/or adjuvant delivery systems. Nanoparticle (NP)-based delivery systems have attracted increasing interest due to enhancement of antigen uptake via prevention of vaccine degradation in the biological environment and the intrinsic immune-stimulatory properties of the materials. Mitochondria play paramount roles in cell life and death and are promising targets for vaccine delivery systems to effectively induce immune responses. In this review, we focus on NPs-based delivery systems with surfaces that can be manipulated by using mitochondria targeting moieties for intervention in health and disease.

Nanotechnology inspired tools for mitochondrial dysfunction related diseases

Mitochondrial dysfunctions are recognized as major factors for various diseases including cancer, cardiovascular diseases, diabetes, neurological disorders, and a group of diseases so called "mitochondrial dysfunction related diseases". One of the major hurdles to gain therapeutic efficiency in diseases where the targets are located in the mitochondria is the accessibility of the targets in this compartmentalized organelle that imposes barriers toward internalization of ions and molecules. Over the time, different tools and techniques were developed to improve therapeutic index for mitochondria acting drugs. Nanotechnology has unfolded as one of the logical and encouraging tools for delivery of therapeutics in controlled and targeted manner simultaneously reducing side effects from drug overdose. Tailor-made nanomedicine based therapeutics can be an excellent tool in the toolbox for diseases associated with mitochondrial dysfunctions. In this review, we present an extensive coverage of possible therapeutic targets in different compartments of mitochondria for cancer, cardiovascular, and mitochondrial dysfunction related diseases.

Latexin sensitizes leukemogenic cells to gamma-irradiation-induced cell-cycle arrest and cell death through Rps3 pathway

Leukemia is a leading cause of cancer death. Recently, the latexin (Lxn) gene was identified as a potential tumor suppressor in several types of solid tumors and lymphoma, and Lxn expression was found to be absent or downregulated in leukemic cells. Whether Lxn functions as a tumor suppressor in leukemia and what molecular and cellular mechanisms are involved are unknown. In this study, the myeloid leukemogenic FDC-P1 cell line was used as a model system and Lxn was ectopically expressed in these cells. Using the protein pull-down assay and mass spectrometry, ribosomal protein subunit 3 (Rps3) was identified as a novel Lxn binding protein. Ectopic expression of Lxn inhibited FDC-P1 growth in vitro. More surprisingly, Lxn enhanced gamma irradiation-induced DNA damages and induced cell-cycle arrest and massive necrosis, leading to depletion of FDC-P1 cells. Mechanistically, Lxn inhibited the nuclear translocation of Rps3 upon radiation, resulting in abnormal mitotic spindle formation and chromosome instability. Rps3 knockdown increased the radiation sensitivity of FDC-P1, confirming that the mechanism of action of Lxn is mediated by Rps3 pathway. Moreover, Lxn enhanced the cytotoxicity of chemotherapeutic agent, VP-16, on FDC-P1 cells. Our study suggests that Lxn itself not only suppresses leukemic cell growth but also potentiates the cytotoxic effect of radio- and chemotherapy on cancer cells. Lxn could be a novel molecular target that improves the efficacy of anti-cancer therapy.

Identification and characterization of the sex-determiner transformer-2 homologue in Chinese shrimp, Fenneropenaeus chinensis

The transformer-2 gene, encoding a protein (Tra-2) which directs sex-specifically alternative splicing of doublesex (dsx) pre-mRNA in combination with the transformer (Tra) protein, has been proved to play important roles on sex differentiation and sex development in Drosophila melanogaster. In the present study, a tra-2 homologue (FcTra-2) was cloned and characterized in the Chinese shrimp, Fenneropenaeus chinensis. A FcTra-2 genomic DNA sequence with a length of 8,871 bp was obtained and verified to consist of 7 exons and 6 introns. Three alternatively spliced mRNA transcripts, designated as FcTra-2a, FcTra-2b and FcTra-2c, were isolated and characterized. Sequence analysis showed that FcTra-2 included a RNA recognition motif and a linker region, which shared high sequence identities with Tra-2 from other species and 2 arginine/serine rich regions. Further studies were performed on the isoform FcTra-2c, since it exhibited a significantly higher expression level in ovary than in other tissues. In early developmental stages of the shrimp, FcTra-2c was detected to suddenly increase its expression level at the mysis stage. In juvenile stage, FcTra-2c displayed a significantly higher expression level in female Chinese shrimp than in males. These data indicated that FcTra-2 might be involved in female sex determination in Chinese shrimp.

Deletion of PI3K-p85alpha gene impairs lineage commitment, terminal maturation, cytokine generation and cytotoxicity of NK cells

Class IA phosphotidylinositol-3-kinases (PI3Ks) are a family of p85/p110 heterodimeric lipid kinases that are important in regulating signaling events in B and T cells. However, their role in natural killer (NK) cells is not understood. Here, using mice that lack the regulatory p85alpha subunit and its alternatively spliced variants p55alpha/p50alpha (collectively termed as p85alpha(-/-)), we defined the role of PI3K in NK cell development and function. p85alpha(-/-) mice had impaired lineage commitment leading to reduced NK cellularity in the bone marrow and liver. p85alpha(-/-) NK cells showed a defective Ly49 subset specification and a decreased expression of CD43. Lack of p85alpha severely reduced the NK-mediated cytotoxicity against tumor cells representing 'induced-self' and 'missing-self'. More importantly, NKG2D and NK1.1 receptor-mediated cytokine and chemokine generation was significantly compromised in p85alpha(-/-) NK cells. These results reveal a previously unrecognized role of p85alpha in the development, terminal maturation, cytokine/chemokine generation and tumor clearance of NK cells.

Biomarkers in transplantation: Prospective, blinded measurement of predictive value for the flow cytometry crossmatch after negative antiglobulin crossmatch in kidney transplantation

This prospective, blinded observational study was conducted to measure the predictive value the of flow cytometric crossmatch for biopsy-proven acute rejection, graft loss, or death following kidney transplantation. Patients were selected for renal transplantation on the basis of a conventional antihuman globulin cytotoxic T-cell crossmatch. Flow crossmatch was performed simultaneously, but the results were not disclosed to the transplant team. A total of 257 kidney transplant recipients were enrolled in the study; 78 patients experienced biopsy-proven rejection in the first post-transplant year, and 41 patients lost their graft or died during the period of follow-up (mean: 2046 days). Kaplan-Meier estimates of rejection, graft loss, or patient death did not differ between subjects with a positive or negative flow crossmatch. Cox analyses showed no influence of the flow crossmatch on the risk of biopsy-proven acute rejection (P = 0.987). The sensitivity and specificity of the flow crossmatch for prediction of biopsy-proven rejection were 0.128 and 0.883, and the positive and negative post-test probabilities were 0.323 and 0.301, respectively. The magnitude of the channel shift did not influence the multivariate Cox regression model. The area under the receiver operating characteristic curve of the flow crossmatch was 0.483 (P = 0.71) and 0.572 (P = 0.38), respectively for the living and cadaver transplant recipients, indicating no discriminative value in this study population. Flow crossmatch appears to have no significant incremental value in predicting biopsy-proven acute rejection, graft loss, or death following kidney transplantation in patients who have a negative antihuman globulin cytotoxic T-cell crossmatch against their donor.

Variations in the human phospholipase Cgamma2 gene in patients with B-cell defects of unknown etiology

Our recent studies using targeted gene disruption have shown that defects in phospholipase Cgamma2 (PLCgamma2) result in a B-cell abnormality that is very similar to that seen in Btk-deficient mice. Null mutations in either PLCG2 or BTK are associated with decreased numbers of mature B cells, failure to make antibodies to some T cell-independent antigens and the absence of CD5+ peritoneal B cells. Mutations in BTK in humans cause a more severe defect in B-cell development characterized by almost complete absence of B cells in the peripheral circulation, profound hypogammaglobulinemia and an inability to produce antibodies to any antigens. However, not all patients with severe defects in B-cell development have mutations in BTK or the components of the B-cell signal transduction complex. To explore the possibility that some patients with defects in B-cell development of unknown etiology might have mutations in PLCG2, we determined the genomic structure of this gene and established conditions to analyze the 32 exons of the gene and the flanking sequences by single-strand conformation polymorphism. Although 24 polymorphic variants of this gene were found in 35 patients, we did not identify any alterations that were likely to be the cause of disease.