The HLA-I landscape confers prognosis and antitumor immunity in breast cancer.

Breast cancer is a highly heterogeneous disease with varied subtypes, prognoses and therapeutic responsiveness. Human leukocyte antigen class I (HLA-I) shapes the immunity and thereby influences the outcome of breast cancer. However, the implications of HLA-I variations in breast cancer remain poorly understood. In this study, we established a multiomics cohort of 1156 Chinese breast cancer patients for HLA-I investigation. We calculated four important HLA-I indicators in each individual, including HLA-I expression level, somatic HLA-I loss of heterozygosity (LOH), HLA-I evolutionary divergence (HED) and peptide-binding promiscuity (Pr). Then, we evaluated their distribution and prognostic significance in breast cancer subtypes. We found that the four breast cancer subtypes had distinct features of HLA-I indicators. Increased expression of HLA-I and LOH were enriched in triple-negative breast cancer (TNBC), while Pr was relatively higher in hot tumors within TNBCs. In particular, a higher Pr indicated a better prognosis in TNBCs by regulating the infiltration of immune cells and the expression of immune molecules. Using the matched genomic and transcriptomic data, we found that mismatch repair deficiency-related mutational signature and pathways were enriched in low-Pr TNBCs, suggesting that targeting mismatch repair deficiency for synthetic lethality might be promising therapy for these patients. In conclusion, we presented an overview of HLA-I indicators in breast cancer and provided hints for precision treatment for low-Pr TNBCs.

The mitochondrial ribosomal protein mRpL4 regulates Notch signaling.

Mitochondrial ribosomal proteins (MRPs) assemble as specialized ribosome to synthesize mtDNA-encoded proteins, which are essential for mitochondrial bioenergetic and metabolic processes. MRPs are required for fundamental cellular activities during animal development, but their roles beyond mitochondrial protein translation are poorly understood. Here, we report a conserved role of the mitochondrial ribosomal protein L4 (mRpL4) in Notch signaling. Genetic analyses demonstrate that mRpL4 is required in the Notch signal-receiving cells to permit target gene transcription during Drosophila wing development. We find that mRpL4 physically and genetically interacts with the WD40 repeat protein wap and activates the transcription of Notch signaling targets. We show that human mRpL4 is capable of replacing fly mRpL4 during wing development. Furthermore, knockout of mRpL4 in zebrafish leads to downregulated expression of Notch signaling components. Thus, we have discovered a previously unknown function of mRpL4 during animal development.

Unraveling the Significance of MET Focal Amplification in Lung Cancer: Integrative NGS, FISH, and IHC Investigation.

MET amplification (METamp) represents a promising therapeutic target in non-small cell lung cancer, but no consensus has been established to identify METamp-dependent tumors that could potentially benefit from MET inhibitors. In this study, an analysis of MET amplification/overexpression status was performed in a retrospectively recruited cohort comprising 231 patients with non-small cell lung cancer from Shanghai Chest Hospital (SCH cohort) using 3 methods: fluorescence in situ hybridization (FISH), hybrid capture-based next-generation sequencing, and immunohistochemistry for c-MET and phospho-MET. The SCH cohort included 130 cases known to be METamp positive by FISH and 101 negative controls. The clinical relevance of these approaches in predicting the efficacy of MET inhibitors was evaluated. Additionally, next-generation sequencing data from another 2 cohorts including 22,010 lung cancer cases were utilized to examine the biological characteristics of different METamp subtypes. Of the 231 cases, 145 showed MET amplification/overexpression using at least 1 method, whereas only half of them could be identified by all 3 methods. METamp can occur as focal amplification or polysomy. Our study revealed that the inconsistency between next-generation sequencing and FISH primarily occurred in the polysomy subtype. Further investigations indicated that compared with polysomy, focal amplification correlated with fewer co-occurring driver mutations, higher protein expressions of c-MET and phospho-MET, and higher incidence in acquired resistance than in de novo setting. Moreover, patients with focal amplification presented a more robust response to MET inhibitors compared with those with polysomy. Notably, a strong correlation was observed between focal amplification and programmed cell death ligand-1 expression, indicating potential therapeutic implications with combined MET inhibitor and immunotherapy for patients with both alterations. Our findings provide insights into the molecular complexity and clinical relevance of METamp in lung cancer, highlighting the role of MET focal amplification as an oncogenic driver and its feasibility as a primary biomarker to further investigate the clinical activity of MET inhibitors in future studies.

High-Resolution Mass Spectrometry Screening of Quaternary Ammonium Compounds (QACs) in Dust from Homes and Various Microenvironments in South China.

Despite their ubiquitous use, information regarding the presence of quaternary ammonium compounds (QACs) in various microenvironments remains scarce and only a small subset of QACs has been monitored using targeted chemical analysis. In this study, a total of 111 dust samples were collected from homes and various public settings in South China during the COVID-19 pandemic and were analyzed for traditional and emerging QACs using high-resolution mass spectrometry. The total traditional QAC concentrations in residential dust (∑traditional QAC, sum of 18 traditional QACs) ranged from 13.8 to 150 µg/g with a median concentration of 42.2 µg/g. Twenty-eight emerging QACs were identified in these samples, and the composition of ∑emerging QAC (sum of emerging QACs) to ∑QAC (sum of traditional and emerging QACs) ranged from 19 to 42% across various microenvironments, indicating the widespread existence of emerging QACs in indoor environments. Additionally, dust samples from cinemas exhibited higher ∑QAC concentrations compared to homes (medians 65.9 µg/g vs 58.3 µg/g, respectively), indicating heavier emission sources of QACs in these places. Interestingly, significantly higher ∑QAC concentrations were observed in dust from the rooms with carpets than those without (medians 65.6 µg/g vs 32.6 µg/g, p < 0.05, respectively). Overall, this study sheds light on the ubiquitous occurrence of QACs in indoor environments in South China.

Detection of Pilot's Mental Workload Using a Wireless EEG Headset in Airfield Traffic Pattern Tasks.

Elevated mental workload (MWL) experienced by pilots can result in increased reaction times or incorrect actions, potentially compromising flight safety. This study aims to develop a functional system to assist administrators in identifying and detecting pilots' real-time MWL and evaluate its effectiveness using designed airfield traffic pattern tasks within a realistic flight simulator. The perceived MWL in various situations was assessed and labeled using NASA Task Load Index (NASA-TLX) scores. Physiological features were then extracted using a fast Fourier transformation with 2-s sliding time windows. Feature selection was conducted by comparing the results of the Kruskal-Wallis (K-W) test and Sequential Forward Floating Selection (SFFS). The results proved that the optimal input was all PSD features. Moreover, the study analyzed the effects of electroencephalography (EEG) features from distinct brain regions and PSD changes across different MWL levels to further assess the proposed system's performance. A 10-fold cross-validation was performed on six classifiers, and the optimal accuracy of 87.57% was attained using a multi-class K-Nearest Neighbor (KNN) classifier for classifying different MWL levels. The findings indicate that the wireless headset-based system is reliable and feasible. Consequently, numerous wireless EEG device-based systems can be developed for application in diverse real-driving scenarios. Additionally, the current system contributes to future research on actual flight conditions.

The early-stage triple-negative breast cancer landscape derives a novel prognostic signature and therapeutic target.

PURPOSE: Triple-negative breast cancer (TNBC) is a highly heterogeneous disease. Patients with early-stage TNBCs have distinct likelihood of distant recurrence. This study aimed to develop a prognostic signature of early-stage TNBC patients to improve risk stratification. METHODS: Using RNA-sequencing data, we analyzed 189 pathologically confirmed pT1-2N0M0 TNBC patients and identified 21 mRNAs that were highly expressed in tumor and related to relapse-free survival. All-subset regression program was used for constructing a 7-mRNA signature in the training set (n = 159); the accuracy and prognostic value were then validated using an independent validation set (n = 158). RESULTS: Here, we profiled the transcriptome data from 189 early-stage TNBC patients along with 50 paired normal tissues. Early-stage TNBCs mainly consisted of basal-like immune-suppressed subtype and had higher homologous recombination deficiency scores. We developed a prognostic signature including seven mRNAs (ACAN, KRT5, TMEM101, LCA5, RPP40, LAGE3, CDKL2). In both the training (n = 159) and validation set (n = 158), this signature could identify patients with relatively high recurrence risks and served as an independent prognostic factor. Time-dependent receiver operating curve showed that the signature had better prognostic value than traditional clinicopathological features in both sets. Functionally, we showed that TMEM101 promoted cell proliferation and migration in vitro, which represented a potential therapeutic target. CONCLUSIONS: Our 7-mRNA signature could accurately predict recurrence risks of early-stage TNBCs. This model may facilitate personalized therapy decision-making for early-stage TNBCs individuals.

Gut microbiome alterations and gut barrier dysfunction are associated with host immune homeostasis in COVID-19 patients.

BACKGROUND: COVID-19 is an infectious disease characterized by multiple respiratory and extrapulmonary manifestations, including gastrointestinal symptoms. Although recent studies have linked gut microbiota to infectious diseases such as influenza, little is known about the role of the gut microbiota in COVID-19 pathophysiology. METHODS: To better understand the host-gut microbiota interactions in COVID-19, we characterized the gut microbial community and gut barrier function using metagenomic and metaproteomic approaches in 63 COVID-19 patients and 8 non-infected controls. Both immunohematological parameters and transcriptional profiles were measured to reflect the immune response in COVID-19 patients. RESULTS: Altered gut microbial composition was observed in COVID-19 patients, which was characterized by decreased commensal species and increased opportunistic pathogenic species. Severe illness was associated with higher abundance of four microbial species (i.e., Burkholderia contaminans, Bacteroides nordii, Bifidobacterium longum, and Blautia sp. CAG 257), six microbial pathways (e.g., glycolysis and fermentation), and 10 virulence genes. These severity-related microbial features were further associated with host immune response. For example, the abundance of Bu. contaminans was associated with higher levels of inflammation biomarkers and lower levels of immune cells. Furthermore, human-origin proteins identified from both blood and fecal samples suggested gut barrier dysfunction in COVID-19 patients. The circulating levels of lipopolysaccharide-binding protein increased in patients with severe illness and were associated with circulating inflammation biomarkers and immune cells. Besides, proteins of disease-related bacteria (e.g., B. longum) were detectable in blood samples from patients. CONCLUSIONS: Our results suggest that the dysbiosis of the gut microbiome and the dysfunction of the gut barrier might play a role in the pathophysiology of COVID-19 by affecting host immune homeostasis.

Optimized preparation of activated carbon from furfural residue using response surface methodology and its application for bisphenol S adsorption.

Furfural residue (FR), a solid waste, was applied as the precursor to prepare activated carbon by steam activation. The Box-Behnken design (BBD) approach-based response surface methodology (RSM) was utilized to optimize the preparation conditions to evaluate their effects on the performance of activated carbon from furfural residue (FRAC). The optimum preparation conditions of FRAC were found as follows: activation temperature of 922 °C, activation time of 62 min, and the mass ratio of char to H2O of 1:4.5, resulting in 1,501.84 mg/g of iodine adsorption capacity and 1,662.41 m2/g of specific surface area. The FRAC was characterized and then the adsorption performance of bisphenol S (BPS) on FRAC was investigated. Langmuir and Koble-Corrigan isotherm models were well fitted to the experimental data, and the adsorption kinetics process was perfectly described by the pseudo-second-order model. Thermodynamic parameters showed that the adsorption of BPS was a spontaneous exothermic process. Besides, the regeneration efficiency of FRAC was over 97% after five consecutive cycles. The maximum monolayer adsorption capacity of FRAC for BPS was 3.2848 mmol/g at 298 K, indicating that the FRAC was an excellent adsorbent for the removal of BPS from aqueous solutions.

High specific surface area N-doped activated carbon from hydrothermal carbonization of shaddock peel for the removal of norfloxacin from aqueous solution.

A novel N-doped activated carbon (NAC) derived from shaddock peel was investigated to remove norfloxacin (NFX) from aqueous solution. The Box-Behnken central composite design (BBD) was used to optimize the preparation conditions of NAC. The specific surface area of NAC was 2,481.81 m2 g-1, which was obtained at 1,106 K activation temperature, 2.4 h residence time, and 2.3:1 mass ratio of KOH to hydrochar. Moreover, the equilibrium data were perfectly represented by Langmuir and Koble-Corrigan isotherms, and the adsorption process was precisely described by the pseudo-second-order kinetic model. Besides, the adsorption of NFX on NAC was mainly controlled by π-π electron-donor-acceptor (EDA) interaction, hydrophobic effect, hydrogen-bonding, electrostatic interaction and Lewis acid-base effect. The maximum monolayer adsorption capacity of NFX was 746.29 mg g-1 at 298 K, implying that NAC was a promising adsorbent for the removal of NFX from aqueous solution.

Comprehensive polychromatic integral diffraction efficiency sensitivity to tilt error for multilayer diffractive optical elements with oblique incidence.

Oblique incidence is the general working state for multilayer diffractive optical elements (MLDOEs) in an imaging optical system. The polychromatic integral diffraction efficiency (PIDE) is very sensitive to the incident angle. Therefore, it is necessary to analyze the effect of tilt error on diffraction efficiency/PIDE with oblique incidence. The theoretical model of the relationship between the diffraction efficiency and tilt error with oblique incidence is presented, and the effect of tilt error on diffraction efficiency/PIDE is analyzed. The analysis model of comprehensive PIDE for a certain range of incident angles and the tilt error for MLDOEs is established. The simulation results showed that the comprehensive PIDE is sensitive to tilt angle with oblique incidence, and the tolerance of the tilt error angle can be determined by the comprehensive PIDE. The tilt error tolerance is furthermore investigated with decenter error based on the maximum of comprehensive PIDE. The method and results can be used to guide the tolerance formulation of tilt error for MLDOEs in hybrid optical systems.

Identification of human circadian genes based on time course gene expression profiles by using a deep learning method.

Circadian genes express periodically in an approximate 24-h period and the identification and study of these genes can provide deep understanding of the circadian control which plays significant roles in human health. Although many circadian gene identification algorithms have been developed, large numbers of false positives and low coverage are still major problems in this field. In this study we constructed a novel computational framework for circadian gene identification using deep neural networks (DNN) - a deep learning algorithm which can represent the raw form of data patterns without imposing assumptions on the expression distribution. Firstly, we transformed time-course gene expression data into categorical-state data to denote the changing trend of gene expression. Two distinct expression patterns emerged after clustering of the state data for circadian genes from our manually created learning dataset. DNN was then applied to discriminate the aperiodic genes and the two subtypes of periodic genes. In order to assess the performance of DNN, four commonly used machine learning methods including k-nearest neighbors, logistic regression, naïve Bayes, and support vector machines were used for comparison. The results show that the DNN model achieves the best balanced precision and recall. Next, we conducted large scale circadian gene detection using the trained DNN model for the remaining transcription profiles. Comparing with JTK_CYCLE and a study performed by Möller-Levet et al. (doi: https://doi.org/10.1073/pnas.1217154110), we identified 1132 novel periodic genes. Through the functional analysis of these novel circadian genes, we found that the GTPase superfamily exhibits distinct circadian expression patterns and may provide a molecular switch of circadian control of the functioning of the immune system in human blood. Our study provides novel insights into both the circadian gene identification field and the study of complex circadian-driven biological control. This article is part of a Special Issue entitled: Accelerating Precision Medicine through Genetic and Genomic Big Data Analysis edited by Yudong Cai & Tao Huang.

Synergetic and Antagonistic Molecular Effects Mediated by the Feedback Loop of p53 and JNK between Saikosaponin D and SP600125 on Lung Cancer A549 Cells.

We jointly analyzed the changes in cell cycle arrest and distribution, the accumulation of subphase cells, apoptosis, and proliferation in A549 cells treated with Saikosaponin D (Ssd) and JNK inhibitor SP600125 alone or in combination. Our results indicated that cell cycle arrest at G0/G1, S, and G2/M phases was coupled with the accumulation of subG1, subS, and subG2 cells, corresponding to early apoptosis, DNA endoreplication, and later inhibitory proliferation, respectively. Analyzing the expression of 18 cell cycle regulatory genes and JNK and phosphorylated JNK (pJNK) levels revealed an enhancement in these factors by Ssd. Additional SP600125 weakened or eliminated the Ssd-induced increase of these factors except that p53/p21 and Rassfia levels were further improved. Ingenuity Pathway Analysis (IPA) of the interactions of these factors revealed a negative synergistic effect on apoptosis while a positive synergistic effect on proliferative inhibition of the two drugs: (1) Ssd induced apoptosis via the activation of two axes, TGFα-JNK-p53 and TGFα-Rassfia-Mst1. By eliminating the Ssd-induced increase of JNK/pJNK, additional SP600125 weakened the Ssd-induced apoptotic axis of TGFα-JNK-p53 and simultaneously abolished Ssd-induced apoptosis; (2) Ssd inhibited proliferation by the activation of two axes, TGFß-p53/p21/p27/p15/p16 and TGFα-Rassfia-cyclin D1. By improving the Ssd-induced increase of p53/p21 and Rassfia, additional SP600125 enhanced the two axes of Ssd-induced inhibitory proliferation. Analyzing JNK/pJNK, p53, phospho-p53, and TNF-α levels revealed an opposite association of JNK/pJNK with p53 while consistent with phospho-p53 and TNF-α, which supported the proposals that JNK/pJNK negatively regulated p53 level, while it mediated p53 phosphorylation to transcriptionally activate TNF-α expression of apoptotic gene and trigger apoptosis. With the multiple roles, JNK/pJNK forms a synergetic and antagonistic feedback loop with phospho-p53/p53. Within the feedback loop, (1) Ssd-induced apoptosis depended on JNK/pJNK activities mediating phospho-p53 that activated TNF-α expression; (2) by weakening the negative regulation of JNK/pJNK in p53, SP600125 enhanced p53 level and the Ssd-induced inhibitory proliferation axes of TGFß-p53/p21/p27/p15/p16. The results indicated the central coordinating roles of the feedback loop in the synergistic and antagonistic effects of the two drugs in A549 cells and provided a rationale for the combination of Ssd with SP600125 in the treatment of lung cancer.

Nanospikes functionalization as a universal strategy to disperse hydrophilic particles in non-polar media.

Dispersion of hydrophilic particles in non-polar media has many important applications yet remains difficult. Surfactant or amphiphilic functionalization was conventionally applied to disperse particles but is highly dependent on the particle/solvent system and may induce unfavorable effects and impact particle hydrophilic nature. Recently 2 µm size polystyrene microbeads coated with ZnO nanospikes have been reported to display anomalous dispersity in phobic media without using surfactant or amphiphilic functionalization. However, due to the lack of understanding whether this phenomenon was applicable to a wider range of conditions, little application has been derived from it. Here the anomalous dispersity phenomenons of hydrophilic microparticles covered with nanospikes were systematically assessed at various conditions including different particle sizes, material compositions, particle morphologies, solvent hydrophobicities, and surface polar groups. Microparticles were functionalized with nanospikes through hydrothermal route, followed by dispersity test in hydrophobic media. The results suggest nanospikes consistently prevent particle aggregation in various particle or solvent conditions, indicating the universal applicability of the anomalous dispersion phenomenons. This work provides insight on the anomalous dispersity of hydrophilic particles in various systems and offers potential application to use this method for surfactant-free dispersions.

Insight into the biological effects of acupuncture points by X-ray absorption fine structure.

Exploration of the biological effects of transition metal ions in acupuncture points is essential to clarify the functional mechanism of acupuncture treatment. Here we show that in the SP6 acupuncture point (Sanyinjiao) the Fe ions are in a high-spin state of approximately t2g4.5eg1.5 in an Fe-N(O) octahedral crystal field. The Fe K-edge synchrotron radiation X-ray absorption fine structure results reveal that the Fe-N and Fe-O bond lengths in the SP6 acupuncture point are 2.05 and 2.13 Å, respectively, and are 0.05-0.10 Å longer than those in the surrounding tissue. The distorted atomic structure reduces the octahedral symmetry and weakens the crystal field around the Fe ions by approximately 0.3 eV, leading to the high-spin configuration of the Fe ions, which is favorable for strengthening the magnetotransport and oxygen transportation properties in the acupuncture point by the enhanced spin coherence. This finding might provide some insight into the microscopic effect of the atomic and electronic interactions of transition metal ions in the acupuncture point. Graphical Abstract ᅟ.

Tunable broadband, wide-angle, and polarization-dependent perfect infrared absorber based on planar structure containing phase-change material.

A multilayer absorber composed of SiO2, Fe, Ge2Sb2Te5 (GST), and Al is designed, and the absorptive properties are theoretically investigated based on the Fresnel coefficients method in the wavelength range of 300-2500 nm by changing the thickness and crystallization rate of GST, the incident angle, and the polarization. The results show that the thin Fe layer plays a key role in obtaining an ultra-broadband perfect absorption. The absorption properties are polarization-dependent, and the perfect absorption can be nearly realized for a p-polarized wave at the incident angle smaller than 75° with the bandwidth larger than 316 nm at 90% of max absorption value. The absorptive peak of this absorber can be tuned with the crystallization rate of GST by temperature, and the peak wavelength moves from 1433 nm in the amorphous phase to 2051 nm in the crystalline phase. This structure can provide a feasible route to design the tunable broadband, wide-angle, and polarization-dependent perfect absorber without lithographic patterns in the infrared band.

Transcription factor and microRNA co-regulatory loops: important regulatory motifs in biological processes and diseases.

Transcription factors (TFs) and microRNAs (miRNAs) can jointly regulate target gene expression in the forms of feed-forward loops (FFLs) or feedback loops (FBLs). These regulatory loops serve as important motifs in gene regulatory networks and play critical roles in multiple biological processes and different diseases. Major progress has been made in bioinformatics and experimental study for the TF and miRNA co-regulation in recent years. To further speed up its identification and functional study, it is indispensable to make a comprehensive review. In this article, we summarize the types of FFLs and FBLs and their identified methods. Then, we review the behaviors and functions for the experimentally identified loops according to biological processes and diseases. Future improvements and challenges are also discussed, which includes more powerful bioinformatics approaches and high-throughput technologies in TF and miRNA target prediction, and the integration of networks of multiple levels.

Optimal design of depth-scaling error for multilayer diffractive optical elements with oblique incidence.

The mathematical analytic models of the relationship between depth-scaling error and diffraction efficiency/polychromatic integral diffraction efficiency (PIDE) for multilayer diffractive optical elements (MLDOEs) with oblique incidence are presented. A method for optimal design of the depth-scaling error for MLDOEs with consideration of comprehensive PIDE working within a range of incident angle is established. The effect of depth-scaling error on diffraction efficiency and PIDE of MLDOEs working in the visible wavelength with oblique incidence is analyzed. For the MLDOEs working within the range of incident angle 0-20°, the maximum comprehensive PIDE is 98.24%, and the optimal relative depth-scaling error is -6.55%. The analytic method and conclusion provide a theoretical basis for the determination of manufacturing tolerance of depth-scaling error for MLDOEs with oblique incidence.

Multivariate frequency analysis of urban rainfall characteristics using three-dimensional copulas.

Urban runoff is a major cause of urban flooding and is difficult to monitor in the long term. In contrast, long term continuous rainfall data are generally available for any given region. As a result, it has become customary to use design rainfall depth as a proxy for runoff in urban hydrological analyses, with an assumption of the same frequency for runoff and rainfall. However, this approach has lack of overall coordination and cannot fully reflect the variability of rainfall characteristics. To address this issue, this study presents a three-dimensional copula-based multivariate frequency analysis of rainfall characteristics based on a long term (1961-2012) rainfall data from Guangzhou, China. Firstly, continuous rainfall data were divided into individual rainfall events using the rainfall intensity method. Then the characteristic variables of rainfall (design rainfall depth, DRD; total rainfall depth, TRD; peak rainfall depth, PRD) were sampled using the annual maximum method. Finally, a copula method was used to develop the multivariate joint probability distribution and the conditional probability distribution of rainfall characteristics. The results showed that the copula-based method is easy to implement and can better reflect urban rainstorm characteristics. It can serve a scientific reference for urban flood control and drainage planning.

Noninvasive diagnosis and monitoring of mutations by deep sequencing of circulating tumor DNA in esophageal squamous cell carcinoma.

Circulating tumor DNA (ctDNA) is becoming an important biomarker in noninvasive diagnosis and monitoring of tumor dynamics. This study tested the feasibility of plasma ctDNA for the non-invasive analysis of tumor mutations in esophageal squamous cell carcinoma (ESCC) by sequencing of tumor, tumor-adjacent, and normal tissue, as well as pre-surgery and post-surgery plasma. Exome sequencing of eight patients identified between 29 and 134 somatic mutations in ESCCs, many of which were also determined in ctDNA. Comparison of pre-surgery and post-surgery plasma has shown that mutations had reduced frequency or disappeared after surgery treatment. We further evaluated the TruSight Cancer sequencing panel by using it to detect mutations in the plasma of three patients. Tumor mutations were only found in one of them. To design a sequencing panel with improved targeting, we identified significantly mutated genes by meta-analysis of 532 ESCC genomes. Our results confirmed the well-known driver genes and found several uncharacterized genes. The new panel consisted of 90 recurrent genes, which theoretically achieved 94% and 75% of sensitivity when detecting at least 1 and 2 mutant genes in ESCC patients, respectively. Our results demonstrate the feasibility of using ctDNA to detect ESCCs and monitor treatment effect. The low-cost and sensitive target panel could facilitate clinical usage of ctDNA as a noninvasive biomarker.

Dissecting Collective Cell Behavior in Polarization and Alignment on Micropatterned Substrates.

Pattern-dependent collective behaviors of cells have recently raised intensive attention. However, the underlying mechanisms that regulate these behaviors are largely elusive. Here, we report a quantitative study, combining experiment and modeling, on cell polarization and arrangement on a micropatterned substrate. We show that cells exhibit position-dependent collective behaviors that can be regulated by geometry and stiffness of the patterned substrate. We find that the driving force for these collective behaviors is the in-plane maximum shear stress in the cell layer that directs the arrangement of cells. The larger the shear stress, the more the cells preferentially align and polarize along the direction of the maximum principal stress. We also find that the aspect ratio of cell polarization shape and the degree to which cells preferentially align along the direction of maximum principal stress exhibit a biphasic dependence on substrate rigidity, corresponding to our quantitative predictions that the magnitude of the maximum shear stress is biphasically dependent on the stiffness of the substrate. As such, the driving force of these cell collective behaviors can be quantified using the maximum shear stress.