Biphasic co-detection of melanoma aneuploid tumor cells and tumor endothelial cells in guidance of specifying the field cancerized surgical excision margin and administering immunotherapy.

An optimum safety excision margin (EM) delineated by precise demarcation of field cancerization along with reliable biomarkers that enable predicting and timely evaluating patients' response to immunotherapy significantly impact effective management of melanoma. In this study, optimized biphasic "immunofluorescence staining integrated with fluorescence insitu hybridization" (iFISH) was conducted along the diagnosis-metastasis-treatment-cellular MRD axis to longitudinally co-detect a full spectrum of intact CD31- aneuploid tumor cells (TCs), CD31+ aneuploid tumor endothelial cells (TECs), viable and necrotic circulating TCs (CTCs) and circulating TECs (CTECs) expressing PD-L1, Ki67, p16 and Vimentin in unsliced specimens of the resected primary tumor, EM, dissected sentinel lymph nodes (SLNs) and peripheral blood in an early-stage melanoma patient. Numerous PD-L1+ aneuploid TCs and TECs were detected at the conventional safety EM (2 cm), quantitatively indicating the existence of a field cancerized EM for the first time. Contrary to highly heterogeneous PD-L1 expression and degrees of Chr8 aneuploidy in TCs and TECs in the primary lesions as well as CTCs and CTECs in peripheral blood, almost all TCs and TECs in SLNs and EM were homogeneously PD-L1+ haploid cells. Dynamic monitoring and cellular MRD assessment revealed that, in contrast to PD-L1+ CTCs being responsive to the immune checkpoint inhibitor (ICI-anti-PD-1), multiploid (≥pentasomy 8) PD-L1+ and Ki67+ CTECs were respectively resistant to ICI-sensitized T cells. In therapeutically stressed lymphatic and hematogenous metastatic cascades, stratified phenotypic and karyotypic profiling of iFISH tissue and liquid biopsied TCs, TECs, CTCs and CTECs in future large-cohort studies will enable appropriate re-specification of the optimal safety EM and distribution mapping of in-depth characterized, subcategorized target cells to help illustrate their metastatic relevance, ultimately improving risk stratification and clinical intervention of tumor progression, metastases, therapy resistance and cancer relapse.

Current status of weight bias and stigma in pediatrics and the need for greater focus on populations at risk.

PURPOSE OF REVIEW: Obesity is one of the most common pediatric chronic conditions in the United States, affecting approximately 20% of American youth and is more common amongst Black, Latino, and Indigenous and low socioeconomic populations. The condition places children and adolescents at increased risk of physical and mental health conditions partly mediated by the weight bias and stigmatization experienced during the potentially vulnerable periods of childhood and adolescence. RECENT FINDINGS: Weight bias and the resulting stigma are pervasive in society. Children have been shown to internalize this bias and its devaluation, which have been shown to contribute to worsening metabolic and mental health outcomes independently. Studies suggest weight stigmatization more adversely affects Black, Latino, and Indigenous children, suggesting the potential for adverse synergistic effects of these historical biases on such youth. SUMMARY: Addressing childhood obesity successfully across all racial, ethnic, and socioeconomic lines requires addressing weight bias and stigma. Steps toward this end include collaborative efforts to promote cross-cultural competence and upstander bias education and training for those who care for children, person-centered communication, and a culture of inclusivity across governmental, healthcare, educational, entertainment, and advertising sectors.

Data science competition for cross-site individual tree species identification from airborne remote sensing data.

Data on individual tree crowns from remote sensing have the potential to advance forest ecology by providing information about forest composition and structure with a continuous spatial coverage over large spatial extents. Classifying individual trees to their taxonomic species over large regions from remote sensing data is challenging. Methods to classify individual species are often accurate for common species, but perform poorly for less common species and when applied to new sites. We ran a data science competition to help identify effective methods for the task of classification of individual crowns to species identity. The competition included data from three sites to assess each methods' ability to generalize patterns across two sites simultaneously and apply methods to an untrained site. Three different metrics were used to assess and compare model performance. Six teams participated, representing four countries and nine individuals. The highest performing method from a previous competition in 2017 was applied and used as a baseline to understand advancements and changes in successful methods. The best species classification method was based on a two-stage fully connected neural network that significantly outperformed the baseline random forest and gradient boosting ensemble methods. All methods generalized well by showing relatively strong performance on the trained sites (accuracy = 0.46-0.55, macro F1 = 0.09-0.32, cross entropy loss = 2.4-9.2), but generally failed to transfer effectively to the untrained site (accuracy = 0.07-0.32, macro F1 = 0.02-0.18, cross entropy loss = 2.8-16.3). Classification performance was influenced by the number of samples with species labels available for training, with most methods predicting common species at the training sites well (maximum F1 score of 0.86) relative to the uncommon species where none were predicted. Classification errors were most common between species in the same genus and different species that occur in the same habitat. Most methods performed better than the baseline in detecting if a species was not in the training data by predicting an untrained mixed-species class, especially in the untrained site. This work has highlighted that data science competitions can encourage advancement of methods, particularly by bringing in new people from outside the focal discipline, and by providing an open dataset and evaluation criteria from which participants can learn.

Formation of Artificial Fermi Surfaces with a Triangular Superlattice on a Conventional Two-Dimensional Electron Gas.

Imposing an external periodic electrostatic potential to the electrons confined in a quantum well makes it possible to engineer synthetic two-dimensional band structures, with electronic properties different from those in the host semiconductor. Here we report the fabrication and study of a tunable triangular artificial lattice on a GaAs/AlGaAs heterostructure where it is possible to transform from the original GaAs band structure and a circular Fermi surface to a new band structure with multiple artificial Fermi surfaces simply by altering a gate bias. For weak electrostatic modulation magnetotransport measurements reveal multiple quantum oscillations and commensurability oscillations due to the electron scattering from the artificial lattice. Increasing the strength of the modulation reveals new commensurability oscillations of the electrons from the artificial Fermi surface scattering from the triangular artificial lattice. These results show that low disorder gate-tunable lateral superlattices can be used to form artificial two-dimensional crystals with designer electronic properties.

Case report: Post-therapeutic laryngeal carcinoma patient possessing a high ratio of aneuploid CTECs to CTCs rapidly developed de novo malignancy in pancreas.

Effectively evaluating therapeutic efficacy, detecting minimal residual disease (MRD) after therapy completion, and predicting early occurrence of malignancy in cancer patients remain as unmet imperative clinical demands. This article presents a case of a laryngeal carcinoma patient who had a surgical resection and complete post-operative chemoradiotherapy in combination with the targeted therapy, then rapidly developed pancreatic adenocarcinoma. Detected by SE-iFISH, the patient had a substantial amount of 107 non-hematological aneuploid circulating rare cells including 14 circulating tumor cells (CTCs, CD31-/CD45-) and 93 circulating tumor endothelial cells (CTECs, CD31+/CD45-) with a high ratio of CTECs/CTCs > 5 upon finishing post-surgical combination regimens. Positive detection of those aneuploid non-hematological circulating rare cells was five months prior to subsequent plasma CA19-9 increasing and ten months before the de novo pancreatic cancer was diagnosed by medical imaging modalities. Besides previously reported clinical utilities of co-detection of aneuploid CD31- CTCs and CD31+ CTECs in real-time evaluation of therapeutic efficacy, longitudinal monitoring of emerging treatment resistance and adequate detection of MRD, a large cohort study is necessary to further investigate whether, and how, a high ratio of MRD CTECs to CTCs may function as an appropriate index forecasting either occurrence or metastatic distant recurrence of malignancy in post-therapeutic cancer patients.

Nonhematogenic circulating aneuploid cells confer inferior prognosis and therapeutic resistance in gliomas.

Aneuploidy is the hallmark of malignancy. Our previous study successfully detected nonhematogenic circulating aneuploidy cells (CACs) in types of gliomas. The current prospective clinical study aims to further precisely subcategorize aneuploid CACs, including CD31- circulating tumor cells (CTCs) and CD31+ circulating tumor endothelial cells, and thoroughly investigate the clinical utilities of these different subtypes of cells. Co-detection and analysis of CTCs and circulating tumor-derived endothelial cells (CTECs) expressing CD133, glial fibrillary acidic protein (GFAP), or epidermal growth factor receptor variant III (EGFR vIII) were performed by integrated subtraction enrichment and immunostaining fluorescence in situ hybridization (SE-iFISH) in 111 preoperative primary diffuse glioma patients. Aneuploid CACs could be detected in most de novo glioma patients. Among detected CACs, 45.6% were CD31- /CD45- aneuploid CTCs and the remaining 54.4% were CD31+ /CD45- aneuploid CTECs. Positive detection of CTECs significantly correlated with disruption of the blood-brain barrier. The median number of large CTCs (L CTCs, >5 µm, 2) in low-grade glioma (WHO grade 2) was less than high-grade glioma (WHO grades 3 and 4) (3, p = 0.044), but this difference was not observed in small CTCs (S CTCs, ≤5 µm), CTECs or CACs (CTCs + CTECs). The numbers of CTCs, CTECs, or CACs in patients with contrast-enhancing (CE) lesions considerably exceeded that of non-CE lesions (p < 0.05). Receiver operating characteristic curves demonstrated that CD31+ CTECs, especially L CTECs, exhibited a close positive relationship with CE lesions. Survival analysis revealed that the high number of CD31- CTCs could be an adverse factor for compromised progression-free survival and overall survival. Longitudinal surveillance of CD31- CTCs was suitable for evaluating the therapeutic response and for monitoring potential emerging treatment resistance.

Analysis of the prognostic role and biological characteristics of circulating tumor cell-associated white blood cell clusters in non-small cell lung cancer.

Background: Recently, circulating tumor-cell-associated white blood cell (CTC-WBC) clusters have been reported to have prognostic value in some cancers. The prognostic role of CTC-WBC clusters in lung cancer has not yet been elucidated. Very little information is available about the biological characteristics of CTC-WBC clusters. Methods: A total of 82 patients with non-small cell lung cancer (NSCLC) were included in this study, and 61 patients with advanced-stage disease were closely followed-up. All patients had blood drawn prior to treatment. Subtraction enrichment and immunostaining-fluorescence in situ hybridization (SE-iFISH) platform was used to isolate and identify CTCs and CTC-WBC clusters. Kaplan-Meier survival analysis and Cox regression analysis were applied to assess patient progression-free survival (PFS). Further, qualitative and quantitative analyses the size and ploidy characteristics of CTC-WBC clusters. Results: Firstly, CTC-WBC clusters appeared more in the advanced (stage III and IV) stage (P=0.043) than in the early stage. Furthermore, the multivariable analysis (Cox proportional hazards model) revealed that the high-CTC (≥7/6 mL) group and CTC-WBC clusters (≥1/6 mL) positive group both had significantly worse PFS, with a hazard ratio (HR) of 2.89 [95% confidence interval (CI): 1.36-6.17, P=0.006] and 2.18 (95% CI: 1.07-4.43, P=0.031), respectively. In the conjoint analysis, compared to patients with <7 CTCs/6 mL without CTC-WBC clusters, patients with ≥7 CTCs/6 mL with CTC-WBC clusters had the highest risk of progression (HR =7.13, 95% CI: 2.51-20.23, P<0.001). In addition, the presence of ≥3-cell CTC-WBC clusters in patients may indicate a shorter PFS (P<0.05) and a higher risk of progression (HR =2.90, 95% CI: 1.06-7.89, P=0.037). Furthermore, compared with the characteristics of the total CTCs, almost all of the CTCs that could recruit WBCs were large cells (≥5 µm) and exhibited polyploidy (≥ tetraploid) (both P<0.01). Conclusions: The presence of CTC-WBC clusters was an independent prognostic factor for advanced NSCLC. The joint analysis of CTCs and CTC-WBC clusters could provide additional prognostic value to the enumeration of CTCs alone. Besides, most of the CTCs in CTC-WBC clusters were large polyploid cells.

Identification and Comprehensive Co-Detection of Necrotic and Viable Aneuploid Cancer Cells in Peripheral Blood.

Aneuploid circulating tumor cells (CTCs, CD31-) and circulating tumor endothelial cells (CTECs, CD31+) exhibit an active interplay in peripheral blood, and play an essential role in tumorigenesis, neoangiogenesis, disease progression, therapy-resistant minimal residual disease (MRD), cancer metastasis and relapse. Currently, most CTC detection techniques are restricted to the indistinguishable quantification of circulating rare cells, including both necrotic and viable cells in cancer patients. Clinically imperative demands to distinguish and detect live and/or dead non-hematological aneuploid cancer cells in peripheral blood, which will assist in the rapid evaluation of therapeutic effects, real-time monitoring of treatment resistance longitudinally developed along with therapy and the effective detection of post-therapeutic MRD, have not yet been achieved. The integrated subtraction enrichment and immunostaining-fluorescence in situ hybridization (SE-iFISH)-derived novel strategy was developed in this study, aiming to precisely identify and detect live and necrotic cancer cells (NC) enriched from carcinoma patients' biofluids. The innovative SE-iFISH (NC) provides a meaningful and practical approach to co-detect various viable and necrotic aneuploid CTCs and CTECs. The detected circulating rare cells can be characterized and categorized into diverse subtypes based upon cell viability, morphology, multiple tumor markers' expression, and the degree of aneuploidy relevant to both malignancy and therapeutic resistance. Each subtype of live or necrotic CTCs and CTECs possesses distinct utility in anti-cancer drug development, translational research, and clinical practice.

Aneuploid Circulating Tumor Cells as a Predictor of Response to Neoadjuvant Chemotherapy in Non-Small Cell Lung Cancer.

PURPOSE: This study aimed to explore the potential application of circulating tumor cells (CTCs) in predicting the therapeutic effect of neoadjuvant chemotherapy (NAC) in non-small-cell lung cancer (NSCLC). METHODS: Using integrated subtraction enrichment and immunostaining-fluorescence in situ hybridization, the serial CTCs of patients with NSCLC were detected in 7.5 mL of blood at baseline and after two cycles of cisplatin-based NAC, and all aneuploidies of chromosome 8 were examined in the enriched CTCs. Tumor responses were evaluated radiologically with serial chest computed tomography (CT) using the response evaluation criteria in solid tumors and microscopically using the tumor cell necrosis rate (TCNR) of the resected specimen after NAC. RESULTS: After two cycles of cisplatin-based NAC, 89% (8/9) of the patients with radiological partial response to NAC had reduced CTC numbers, while 73% (8/11) of the patients with stable disease exhibited increased CTC numbers (P = 0.0098). On pathological examination, 90% (9/10) of patients with a TCNR lower than 30% had >1 CTC post-NAC, while 80% (4/5) of patients with a TCNR higher than 30% had ≤1 CTC post-NAC (P = 0.017). In aneuploidy analysis, the positive rate (CTC > 0) of triploid CTCs was found to have increased after NAC, in contrast with the tetraploid and multiploid CTCs. Furthermore, tetraploid and multiploid CTCs were found to be significantly downregulated in the patients with partial response to NAC. CONCLUSION: The correlations of aneuploid CTCs with both radiological and pathological responses in patients with NSCLC who received NAC were summarized, and the findings indicate that enumerating and karyotyping aneuploid CTCs can serve as a surrogate marker for disease monitoring in NSCLC.

Role of aneuploid circulating tumor cells and CD31+ circulating tumor endothelial cells in predicting and monitoring anti-angiogenic therapy efficacy in advanced NSCLC.

Prognosticating the efficacy of anti-angiogenic therapy through longitudinal monitoring and early detection of treatment resistance in cancer patients remain highly challenging. In this study, co-detection and comprehensive phenotypic and karyotypic molecular characterization of aneuploid circulating tumor cells (CTCs) and circulating tumor endothelial cells (CTECs) were conducted on non-small cell lung cancer (NSCLC) patients receiving bevacizumab plus chemotherapy. Prognostic values of the cell-based significant univariate risk factors identified by Cox regression analyses were progressively investigated. Subjects showing an increase in total post-therapeutic platelet endothelial cell adhesion molecule-1 (CD31)- CTCs and CD31+ CTECs exhibited a significantly reduced median progression-free survival (mPFS) and overall survival. Further stratification analyses indicated that pretherapeutic patients bearing vimentin (Vim)+ CTECs (mesenchymal M-type) at baseline revealed a significantly shortened mPFS compared with patients with Vim- CTECs. Post-therapeutic patients harboring epithelial cell adhesion molecule (EpCAM)+ CTCs and CTECs (epithelial E-type), regardless of Vim expression or not, showed a significantly reduced mPFS. Post-therapeutic patients possessing de novo EpCAM+ /Vim+ (hybrid E/M-type) CTECs displayed the shortest mPFS. Patients harboring either pre- or post-therapeutic EpCAM- /Vim- null CTECs (N-type) exhibited a better response to therapy compared to patients harboring EpCAM+ and/or Vim+ CTECs. The presented results support the notion that baseline Vim+ CTECs and post-therapeutic EpCAM+ CTCs and CTECs are predictive biomarkers for longitudinal monitoring of response to anti-angiogenesis combination regimens in NSCLC patients.

Dysregulated KRAS gene-signaling axis and abnormal chromatin remodeling drive therapeutic resistance in heterogeneous-sized circulating tumor cells in gastric cancer patients.

The mechanism by which heterogeneous-sized circulating tumor cells (CTCs) in gastric cancer (GC) patients are resistant to the targeted therapy and/or chemotherapy remains unclear. This study investigated prognostic value and genomic variations of size-heterogenous CTCs, in an attempt to unravel the molecular mechanisms underlying the therapeutic resistance, which is relevant to poor prognosis in GC. Aneuploid CTCs, detected in 111 advanced GC patients, were categorized into small (≤white blood cell [WBC], 25.54%) and large (>WBC, 74.46%) cells. Pre-treatment patients possessing ≥3 baseline small CTCs with trisomy 8 (SCTCstri) or ≥6 large multiploid CTCs (LCTCsmulti) showed an inferior median progression-free survival. Moreover, the cut-off value of ≥6 LCTCsmulti was also an effective prognosticator for poor median overall survival. Single cell-based DNA sequencing of 50 targeted CTCs indicated that SCTCstri and LCTCsmulti harbored distinct gene variations respectively. Mutations in the KRAS and Rap1 pathway were remarkably abundant in SCTCstri, whereas several unique mutations in the MET/PI3K/AKT pathway and SMARCB1 gene were identified in LCTCsmulti. Obtained results suggested that SCTCstri and LCTCsmulti exhibited different mechanisms to therapy resistance and correlated with patients' poor outcome.

PD-L1+ aneuploid circulating tumor endothelial cells (CTECs) exhibit resistance to the checkpoint blockade immunotherapy in advanced NSCLC patients.

Sustained angiogenesis and increased PD-L1 expression on endothelial and carcinoma cells contribute toward fostering an immunosuppressive microenvironment suitable for tumor growth. PD-L1+ CTCs were reported to associate with poor prognosis in NSCLC patients. However, whether or not aneuploid circulating tumor endothelial cells (CTECs) express PD-L1, then serve as a surrogate biomarker to evaluate immunotherapy efficacy remains unknown. In this study, a novel SE-iFISH strategy was established to comprehensively quantify and characterize a full spectrum of aneuploid CTCs and CTECs in advanced NSCLC patients subjected to second-line anti-PD-1 (nivolumab) immunotherapy. In situ co-detection of diverse subtypes of aneuploid CTCs and CTECs expressing PD-L1 and Vimentin was performed. The present clinical study demonstrated that significant amounts of PD-L1+ aneuploid CTCs and CTECs could be detected in histopathologic hPD-L1- patients. In contrast to decreased PD-L1+ CTCs, the number of multiploid PD-L1+ CTECs (≥tetrasomy 8) undergoing post-therapeutic karyotype shifting increased in patients along with tumor progression following anti-PD-1 treatment. Progressive disease (PD) lung cancer patients possessing multiploid PD-L1+ CTECs had a significantly shorter PFS compared to those without PD-L1+ CTECs. In carcinoma patients, aneuploid CTCs and CTECs may exhibit a functional interplay with respect to tumor angiogenesis, progression, metastasis, and response to immunotherapy.

Epithelial-type systemic breast carcinoma cells with a restricted mesenchymal transition are a major source of metastasis.

Carcinoma cells undergo epithelial-mesenchymal transition (EMT); however, contributions of EMT heterogeneity to disease progression remain a matter of debate. Here, we addressed the EMT status of ex vivo cultured circulating and disseminated tumor cells (CTCs/DTCs) in a syngeneic mouse model of metastatic breast cancer (MBC). Epithelial-type CTCs with a restricted mesenchymal transition had the strongest lung metastases formation ability, whereas mesenchymal-type CTCs showed limited metastatic ability. EpCAM expression served as a surrogate marker to evaluate the EMT heterogeneity of clinical samples from MBC, including metastases, CTCs, and DTCs. The proportion of epithelial-type CTCs, and especially DTCs, correlated with distant metastases and poorer outcome of patients with MBC. This study fosters our understanding of EMT in metastasis and underpins heterogeneous EMT phenotypes as important parameters for tumor prognosis and treatment. We further suggest that EpCAM-dependent CTC isolation systems will underestimate CTC numbers but will quantify clinically relevant metastatic cells.

A data science challenge for converting airborne remote sensing data into ecological information.

Ecology has reached the point where data science competitions, in which multiple groups solve the same problem using the same data by different methods, will be productive for advancing quantitative methods for tasks such as species identification from remote sensing images. We ran a competition to help improve three tasks that are central to converting images into information on individual trees: (1) crown segmentation, for identifying the location and size of individual trees; (2) alignment, to match ground truthed trees with remote sensing; and (3) species classification of individual trees. Six teams (composed of 16 individual participants) submitted predictions for one or more tasks. The crown segmentation task proved to be the most challenging, with the highest-performing algorithm yielding only 34% overlap between remotely sensed crowns and the ground truthed trees. However, most algorithms performed better on large trees. For the alignment task, an algorithm based on minimizing the difference, in terms of both position and tree size, between ground truthed and remotely sensed crowns yielded a perfect alignment. In hindsight, this task was over simplified by only including targeted trees instead of all possible remotely sensed crowns. Several algorithms performed well for species classification, with the highest-performing algorithm correctly classifying 92% of individuals and performing well on both common and rare species. Comparisons of results across algorithms provided a number of insights for improving the overall accuracy in extracting ecological information from remote sensing. Our experience suggests that this kind of competition can benefit methods development in ecology and biology more broadly.

Comparing clinical judgment with the MySurgeryRisk algorithm for preoperative risk assessment: A pilot usability study.

BACKGROUND: Major postoperative complications are associated with increased cost and mortality. The complexity of electronic health records overwhelms physicians' abilities to use the information for optimal and timely preoperative risk assessment. We hypothesized that data-driven, predictive-risk algorithms implemented in an intelligent decision-support platform simplify and augment physicians' risk assessments. METHODS: This prospective, nonrandomized pilot study of 20 physicians at a quaternary academic medical center compared the usability and accuracy of preoperative risk assessment between physicians and MySurgeryRisk, a validated, machine-learning algorithm, using a simulated workflow for the real-time, intelligent decision-support platform. We used area under the receiver operating characteristic curve to compare the accuracy of physicians' risk assessment for six postoperative complications before and after interaction with the algorithm for 150 clinical cases. RESULTS: The area under the receiver operating characteristic curve of the MySurgeryRisk algorithm ranged between 0.73 and 0.85 and was significantly better than physicians' initial risk assessments (area under the receiver operating characteristic curve between 0.47 and 0.69) for all postoperative complications except cardiovascular. After interaction with the algorithm, the physicians significantly improved their risk assessment for acute kidney injury and for an intensive care unit admission greater than 48 hours, resulting in a net improvement of reclassification of 12% and 16%, respectively. Physicians rated the algorithm as easy to use and useful. CONCLUSION: Implementation of a validated, MySurgeryRisk computational algorithm for real-time predictive analytics with data derived from the electronic health records to augment physicians' decision-making is feasible and accepted by physicians. Early involvement of physicians as key stakeholders in both design and implementation of this technology will be crucial for its future success.

MySurgeryRisk: Development and Validation of a Machine-learning Risk Algorithm for Major Complications and Death After Surgery.

OBJECTIVE: To accurately calculate the risk for postoperative complications and death after surgery in the preoperative period using machine-learning modeling of clinical data. BACKGROUND: Postoperative complications cause a 2-fold increase in the 30-day mortality and cost, and are associated with long-term consequences. The ability to precisely forecast the risk for major complications before surgery is limited. METHODS: In a single-center cohort of 51,457 surgical patients undergoing major inpatient surgery, we have developed and validated an automated analytics framework for a preoperative risk algorithm (MySurgeryRisk) that uses existing clinical data in electronic health records to forecast patient-level probabilistic risk scores for 8 major postoperative complications (acute kidney injury, sepsis, venous thromboembolism, intensive care unit admission >48 hours, mechanical ventilation >48 hours, wound, neurologic, and cardiovascular complications) and death up to 24 months after surgery. We used the area under the receiver characteristic curve (AUC) and predictiveness curves to evaluate model performance. RESULTS: MySurgeryRisk calculates probabilistic risk scores for 8 postoperative complications with AUC values ranging between 0.82 and 0.94 [99% confidence intervals (CIs) 0.81-0.94]. The model predicts the risk for death at 1, 3, 6, 12, and 24 months with AUC values ranging between 0.77 and 0.83 (99% CI 0.76-0.85). CONCLUSIONS: We constructed an automated predictive analytics framework for machine-learning algorithm with high discriminatory ability for assessing the risk of surgical complications and death using readily available preoperative electronic health records data. The feasibility of this novel algorithm implemented in real time clinical workflow requires further testing.

Using FHIR to Construct a Corpus of Clinical Questions Annotated with Logical Forms and Answers.

This paper describes a novel technique for annotating logical forms and answers for clinical questions by utilizing Fast Healthcare Interoperability Resources (FHIR). Such annotations are widely used in building the semantic parsing models (which aim at understanding the precise meaning of natural language questions by converting them to machine-understandable logical forms). These systems focus on reducing the time it takes for a user to get to information present in electronic health records (EHRs). Directly annotating questions with logical forms is a challenging task and involves a time-consuming step of concept normalization annotation. We aim to automate this step using the normalized codes present in a FHIR resource. Using the proposed approach, two annotators curated an annotated dataset of 1000 questions in less than 1 week. To assess the quality of these annotations, we trained a semantic parsing model which achieved an accuracy of 94.2% on this corpus.

Evolutionary Expression of HER2 Conferred by Chromosome Aneuploidy on Circulating Gastric Cancer Cells Contributes to Developing Targeted and Chemotherapeutic Resistance.

Purpose: Previous human epidermal growth factor receptor-2 (HER2)-derived resistance studies were based on ex vivo models, which could not mirror evolutionary expression of HER2 during therapy. To investigate dynamic expression of HER2 and its contribution to developing therapeutic resistance conferred by chromosome aneuploidy, both the HER2 phenotype and chromosome 8 (Chr 8) aneuploidy on circulating tumor cells (CTC) were coexamined in advanced gastric cancer (AGC) patients.Experimental Design: A total of 115 AGC patients, including 56 of histopathologic HER2+ (hHER2+) subjects who received first-line HER2-targeted therapy plus chemotherapy, and 59 of hHER2- patients who received chemotherapy alone, were prospectively enrolled. Both HER2 phenotype and Chr8 aneuploidy of CTCs in patients were coexamined by HER2-iFISH during therapy.Results: A fluctuated positive HER2 phenotype on CTCs (cHER2+) was revealed, showing cHER2+ at different time intervals during treatment. Acquisition of the cHER2+ phenotype in 91.0% of hHER2+ and 76.2% hHER2- patients was demonstrated to correlate with development of resistance to trastuzumab-targeted therapy for hHER2+ patients and chemotherapy alone for hHER2- patients. Aneuploid Chr8 was demonstrated to participate in the acquisition of the cHER2+ phenotype, which provides a growth advantage to HER2+ CTCs against therapeutic pressure, leading to the development of therapeutic resistance.Conclusions: Compared with low positivity of conventional histopathologic hHER2 examination routinely performed once, significant higher positivity of cHER2+ on CTCs was observed. Continuously examining cHER2 shows unique advantages with respect to monitoring therapeutic resistance in real time in carcinoma patients. Moreover, contribution of chromosome aneuploidy to the phenotypic evolution of HER2 expression on CTCs may help elucidate underlying mechanisms of developing therapeutic resistance. Clin Cancer Res; 24(21); 5261-71. ©2018 AACR.

Quantified postsurgical small cell size CTCs and EpCAM+ circulating tumor stem cells with cytogenetic abnormalities in hepatocellular carcinoma patients determine cancer relapse.

Detection of hepatocellular carcinoma circulating tumor cells performed with conventional strategies, is significantly limited due to inherently heterogeneous and dynamic expression of EpCAM, as well as degradation of cytokeratins during epithelial-to-mesenchymal transition, which inevitably lead to non-negligible false negative detection of such "uncapturable and invisible" CTCs. A novel SE-iFISH strategy, improved for detection of HCC CTCs in this study, was applied to comprehensively detect, in situ phenotypically and karyotypically characterize hepatocellular and cholangiocarcinoma CTCs (CD45-/CD31-) in patients subjected to surgical resection. Clinical significance of diverse subtypes of CTC was systematically investigated. Existence of small cell size CTCs (≤5 µm of WBCs) with cytogenetic abnormality of aneuploid chromosome 8, which constituted majority of the detected CTCs in HCC patients, was demonstrated for the first time. The stemness marker EpCAM+ aneuploid circulating tumor stem cells (CTSCs), and EpCAM- small CTCs with trisomy 8, promote tumor growth. Postsurgical quantity of small triploid CTCs (≥5 cells/6 ml blood), multiploid (≥pentasomy 8) CTSCs or CTM (either one ≥ 1) significantly correlated to HCC patients' poor prognosis, indicating that detection of those specific subtypes of CTCs and CTSCs in post-operative patients help predict neoplasm recurrence.