Accessing the electronic structure of liquid crystalline semiconductors with bottom-up electronic coarse-graining.

Understanding the relationship between multiscale morphology and electronic structure is a grand challenge for semiconducting soft materials. Computational studies aimed at characterizing these relationships require the complex integration of quantum-chemical (QC) calculations, all-atom and coarse-grained (CG) molecular dynamics simulations, and back-mapping approaches. However, these methods pose substantial computational challenges that limit their application to the requisite length scales of soft material morphologies. Here, we demonstrate the bottom-up electronic coarse-graining (ECG) of morphology-dependent electronic structure in the liquid-crystal-forming semiconductor, 2-(4-methoxyphenyl)-7-octyl-benzothienobenzothiophene (BTBT). ECG is applied to construct density functional theory (DFT)-accurate valence band Hamiltonians of the isotropic and smectic liquid crystal (LC) phases using only the CG representation of BTBT. By bypassing the atomistic resolution and its prohibitive computational costs, ECG enables the first calculations of the morphology dependence of the electronic structure of charge carriers across LC phases at the ∼20 nm length scale, with robust statistical sampling. Kinetic Monte Carlo (kMC) simulations reveal a strong morphology dependence on zero-field charge mobility among different LC phases as well as the presence of two-molecule charge carriers that act as traps and hinder charge transport. We leverage these results to further evaluate the feasibility of developing mesoscopic, field-based ECG models in future works. The fully CG approach to electronic property predictions in LC semiconductors opens a new computational direction for designing electronic processes in soft materials at their characteristic length scales.

Distilling coarse-grained representations of molecular electronic structure with continuously gated message passing.

Bottom-up methods for coarse-grained (CG) molecular modeling are critically needed to establish rigorous links between atomistic reference data and reduced molecular representations. For a target molecule, the ideal reduced CG representation is a function of both the conformational ensemble of the system and the target physical observable(s) to be reproduced at the CG resolution. However, there is an absence of algorithms for selecting CG representations of molecules from which complex properties, including molecular electronic structure, can be accurately modeled. We introduce continuously gated message passing (CGMP), a graph neural network (GNN) method for atomically decomposing molecular electronic structure sampled over conformational ensembles. CGMP integrates 3D-invariant GNNs and a novel gated message passing system to continuously reduce the atomic degrees of freedom accessible for electronic predictions, resulting in a one-shot importance ranking of atoms contributing to a target molecular property. Moreover, CGMP provides the first approach by which to quantify the degeneracy of "good" CG representations conditioned on specific prediction targets, facilitating the development of more transferable CG representations. We further show how CGMP can be used to highlight multiatom correlations, illuminating a path to developing CG electronic Hamiltonians in terms of interpretable collective variables for arbitrarily complex molecules.

Two-Step Machine Learning Approach for Charge-Transfer Coupling with Structurally Diverse Data.

Electronic coupling is important in determining charge-transfer rates and dynamics. Coupling strength is sensitive to both intermolecular, e.g., orientation or distance, and intramolecular degrees of freedom. Hence, it is challenging to build an accurate machine learning model to predict electronic coupling of molecular pairs, especially for those derived from the amorphous phase, for which intermolecular configurations are much more diverse than those derived from crystals. In this work, we devise a new prediction algorithm that employs two consecutive KRR models. The first model predicts molecular orbitals (MOs) from structural variation for each fragment, and coupling is further predicted by using the overlap integral included in a second model. With our two-step procedure, we achieved mean absolute errors of 0.27 meV for an ethylene dimer and 1.99 meV for a naphthalene pair, much improved accuracy amounting to 14-fold and 3-fold error reductions, respectively. In addition, MOs from the first model can also be the starting point to obtain other quantum chemical properties from atomistic structures. This approach is also compatible with a MO predictor with sufficient accuracy.

The biological functions and metabolic pathways of valine in swine.

Valine is an essential amino acid and a type of branched-chain amino acid. Due to the involvement of branched-chain amino acids in various metabolic pathways, there has been a surge of interests in valine nutrition and its role in animal physiology. In pigs, the interactions between valine and other branched-chain amino acids or aromatic amino acids are complex. In this review, we delve into the interaction mechanism, metabolic pathways, and biological functions of valine. Appropriate valine supplementation not only enhances growth and reproductive performances, but also modulates gut microbiota and immune functions. Based on past observations and interpretations, we provide recommended feed levels of valine for weaned piglets, growing pigs, gilts, lactating sows, barrows and entire males. The summarized valine nutrient requirements for pigs at different stages offer valuable insights for future research and practical applications in animal husbandry.

Machine-learned dynamic disorder of electron transfer coupling.

Electron transfer (ET) is a fundamental process in chemistry and biochemistry, and electronic coupling is an important determinant of the rate of ET. However, the electronic coupling is sensitive to many nuclear degrees of freedom, particularly those involved in intermolecular movements, making its characterization challenging. As a result, dynamic disorder in electron transfer coupling has rarely been investigated, hindering our understanding of charge transport dynamics in complex chemical and biological systems. In this work, we employed molecular dynamic simulations and machine-learning models to study dynamic disorder in the coupling of hole transfer between neighboring ethylene and naphthalene dimer. Our results reveal that low-frequency modes dominate these dynamics, resulting primarily from intermolecular movements such as rotation and translation. Interestingly, we observed an increasing contribution of translational motion as temperature increased. Moreover, we found that coupling is sub-Ohmic in its spectral density character, with cut-off frequencies in the range of 102 cm-1. Machine-learning models allow direct study of dynamics of electronic coupling in charge transport with sufficient ensemble trajectories, providing further new insights into charge transporting dynamics.

Identifying Coarse-Grained Representations for Electronic Predictions.

Coarse-grained (CG) simulations are an important computational tool in chemistry and materials science. Recently, systematic "bottom-up" CG models have been introduced to capture electronic structure variations of molecules and polymers at the CG resolution. However, the performance of these models is limited by the ability to select reduced representations that preserve electronic structure information, which remains a challenge. We propose two methods for (i) identifying important electronically coupled atomic degrees of freedom and (ii) scoring the efficacy of CG representations used in conjunction with CG electronic predictions. The first method is a physically motivated approach that incorporates nuclear vibrations and electronic structure derived from simple quantum chemical calculations. We complement this physically motivated approach with a machine learning technique based on the marginal contribution of nuclear degrees of freedom to electronic prediction accuracy using an equivariant graph neural network. By integrating these two approaches, we can both identify critical electronically coupled atomic coordinates and score the efficacy of arbitrary CG representations for making electronic predictions. We leverage this capability to make a connection between optimized CG representations and the future potential for "bottom-up" development of simplified model Hamiltonians incorporating nonlinear vibrational modes.

A 3-gene signature comprising CDH4, STAT4 and EBV-encoded LMP1 for early diagnosis and predicting disease progression of nasopharyngeal carcinoma.

PURPOSE: Nasopharyngeal carcinoma is highly metastatic but difficult to detect in its early stages. It is critical to develop a simple and highly efficient molecular diagnostic method for early detection of NPC in clinical biopsies. METHODS: The transcriptomic data of primary NPC cell strains were used as a discovery tool. Linear regression approach was used to define signatures distinctive between early and late stage of NPC. Expressions of candidates were validated with an independent set of biopsies (n = 39). Leave-one-out cross-validation technique was employed to estimate the prediction accuracy on stage classification. The clinical relevance of marker genes was verified using NPC bulk RNA sequencing data and IHC analysis. RESULTS: Three genes comprising CDH4, STAT4, and CYLD were found to have a significant differentiating power to separate NPC from normal nasopharyngeal samples and predicting disease malignancy. IHC analyses showed stronger CDH4, STAT4, and CYLD immunoreactivity in adjacent basal epithelium compared with that in tumor cells (p < 0.001). EBV-encoded LMP1 was exclusively expressed in NPC tumors. Using an independent set of biopsies, we showed that a model combining CDH4, STAT4, and LMP1 had a 92.86% of diagnostic accuracy, whereas a combination of STAT4 and LMP1 had a 70.59% accuracy for predicting advanced disease. Mechanistic studies suggested that promoter methylation, loss of DNA allele, and LMP1 contributed to the suppressive expression of CDH4, CYLD, and STAT4, respectively. CONCLUSION: A model combining CDH4 and STAT4 and LMP1 was proposed to be a feasible model for diagnosing NPC and predicting late stage of NPC.

MFI2 upregulation promotes malignant progression through EGF/FAK signaling in oral cavity squamous cell carcinoma.

Oral squamous cell carcinoma (OSCC) is the predominant histological type of the head and neck squamous cell carcinoma (HNSCC). By comparing the differentially expressed genes (DEGs) in OSCC-TCGA patients with copy number variations (CNVs) that we identify in OSCC-OncoScan dataset, we herein identified 37 dysregulated candidate genes. Among these potential candidate genes, 26 have been previously reported as dysregulated proteins or genes in HNSCC. Among 11 novel candidates, the overall survival analysis revealed that melanotransferrin (MFI2) is the most significant prognostic molecular in OSCC-TCGA patients. Another independent Taiwanese cohort confirmed that higher MFI2 transcript levels were significantly associated with poor prognosis. Mechanistically, we found that knockdown of MFI2 reduced cell viability, migration and invasion via modulating EGF/FAK signaling in OSCC cells. Collectively, our results support a mechanistic understanding of a novel role for MFI2 in promoting cell invasiveness in OSCC.

Research progress on anti-stress nutrition strategies in swine.

In swine production, stress is a common encounter that leads to serious bacterial infection and adverse effects on growth performance. Though antibiotics have been frequently used to control pathogen spread, sustained negative impacts from antibiotics have been found to affect intestinal integrity and the immune system. Multiple nutritional strategies have shown potential to counteract stress and replace antibiotics, including functional amino acids, low protein diet, plant extracts, organic acids, prebiotics, probiotics, minerals and vitamins. These additives relieve the stress response in swine via different mechanisms and signal transduction pathways. Based on the overview of signaling pathways and stress models, this review highlights the potential of nutritional strategies in swine for preventing or treating stress-related health problems. For wider application in the pig industry, the dose ranges measured require for further validation in different physiological contexts and formulations. In the future, microfluid devices and novel stress models are expected to enhance the efficiency of screening for new anti-stress candidates.

Anterior gradient 2 induces resistance to sorafenib via endoplasmic reticulum stress regulation in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) accounts for almost 80% of all liver cancer cases and is the sixth most common cancer and the second most common cause of cancer-related death worldwide. The survival rate of sorafenib-treated advanced HCC patients is still unsatisfactory. Unfortunately, no useful biomarkers have been verified to predict sorafenib efficacy in HCC. RESULTS: We assessed a sorafenib resistance-related microarray dataset and found that anterior gradient 2 (AGR2) is highly associated with overall and recurrence-free survival and with several clinical parameters in HCC. However, the mechanisms underlying the role of AGR2 in sorafenib resistance and HCC progression remain unknown. We found that sorafenib induces AGR2 secretion via posttranslational modification and that AGR2 plays a critical role in sorafenib-regulated cell viability and endoplasmic reticulum (ER) stress and induces apoptosis in sorafenib-sensitive cells. In sorafenib-sensitive cells, sorafenib downregulates intracellular AGR2 and conversely induces AGR2 secretion, which suppresses its regulation of ER stress and cell survival. In contrast, AGR2 is highly intracellularly expressed in sorafenib-resistant cells, which supports ER homeostasis and cell survival. We suggest that AGR2 regulates ER stress to influence HCC progression and sorafenib resistance. CONCLUSIONS: This is the first study to report that AGR2 can modulate ER homeostasis via the IRE1α-XBP1 cascade to regulate HCC progression and sorafenib resistance. Elucidation of the predictive value of AGR2 and its molecular and cellular mechanisms in sorafenib resistance could provide additional options for HCC treatment.

Biosynthetic Gene Clusters from Swine Gut Microbiome.

The abuse of antibiotics has become a serious health challenge in the veterinary field. It creates environmental selection pressure on bacteria and facilitates the rapid spread of antibiotic resistance genes. The speed of discovery and application of cost-effective alternatives to antibiotics is slow in pig production. Natural products from biosynthetic gene clusters (BGCs) represent promising therapeutic agents for animal and human health and have attracted extraordinary passion from researchers due to their ability to participate in biofilm inhibition, stress resistance, and the killing of competitors. In this study, we detected the presence of diverse secondary metabolite genes in porcine intestines through sequence alignment in the antiSMASH database. After comparing variations in microbial BGCs' composition between the ileum and the colon, it was found that the abundance of the resorcinol gene cluster was elevated in the ileal microbiome, whereas the gene cluster of arylpolyene was enriched in the colonic microbiome. The investigation of BGCs' diversity and composition differences between the ileal and colonic microbiomes provided novel insights into further utilizing BGCs in livestock. The importance of BGCs in gut microbiota deserves more attention for promoting healthy swine production.

Cisplatin or Doxorubicin Reduces Cell Viability via the PTPIVA3-JAK2-STAT3 Cascade in Hepatocellular Carcinoma.

Introduction: Hepatocellular carcinoma (HCC) accounts for 80% of all liver cancers and is the 2nd leading cause of cancer-related death in Taiwan. Various factors, including rapid cell growth, a high recurrence rate and drug resistance, make HCC difficult to cure. Moreover, the survival rate of advanced HCC patients treated with systemic chemotherapy remains unsatisfactory. Hence, the identification of novel molecular targets and the underlying mechanisms of chemoresistance in HCC and the development more effective therapeutic regimens are desperately needed. Methods: An MTT assay was used to determine the cell viability after cisplatin or doxorubicin treatment. Western blotting, qRT‒PCR and immunohistochemistry were utilized to examine the protein tyrosine phosphatase IVA3 (PTP4A3) level and associated signaling pathways. ELISA was utilized to analyze the levels of the inflammatory cytokine IL-6 influenced by cisplatin, doxorubicin and PTP4A3 silencing. Results: In this study, we found that PTP4A3 in the cisplatin/doxorubicin-resistant microarray was closely associated with the overall and recurrence-free survival rates of HCC patients. Cisplatin or doxorubicin significantly reduced cell viability and decreased PTP4A3 expression in hepatoma cells. IL-6 secretion increased with cisplatin or doxorubicin treatment and after PTP4A3 silencing. Furthermore, PTP4A3 was highly expressed in tumor tissues versus adjacent normal tissues from HCC patients. In addition, we evaluated the IL-6-associated signaling pathway involving STAT3 and JAK2, and the levels of p-STAT3, p-JAK2, STAT3 and JAK2 were obviously reduced with cisplatin or doxorubicin treatment in HCC cells using Western blotting and were also decreased after silencing PTP4A3. Collectively, we suggest that cisplatin or doxorubicin decreases HCC cell viability via downregulation of PTP4A3 expression through the IL-6R-JAK2-STAT3 cascade. Discussion: Therefore, emerging evidence provides a deep understanding of the roles of PTP4A3 in HCC cisplatin/doxorubicin chemoresistance, which can be applied to develop early diagnosis strategies and reveal prognostic factors to establish novel targeted therapeutics to specifically treat HCC.

Colicins of Escherichia coli Lead to Resistance against the Diarrhea-Causing Pathogen Enterotoxigenic E. coli in Pigs.

Gut microbes can affect host adaptation to various environment conditions. Escherichia coli is a common gut species, including pathogenic strains and nonpathogenic strains. This study was conducted to investigate the effects of different E. coli strains in the gut on the health of pigs. In this study, the complete genomes of two E. coli strains isolated from pigs were sequenced. The whole genomes of Y18J and the enterotoxigenic E. coli strain W25K were compared to determine their roles in pig adaptation to disease. Y18J was isolated from feces of healthy piglets and showed strong antimicrobial activity against W25K in vitro. Gene knockout experiments and complementation analysis followed by modeling the microbe-microbe interactions demonstrated that the antagonistic mechanism of Y18J against W25K relied on the bacteriocins colicin B and colicin M. Compared to W25K, Y18J is devoid of exotoxin-coding genes and has more secondary-metabolite-biosynthetic gene clusters. W25K carries more genes involved in genome replication, in accordance with a shorter cell cycle observed during a growth experiment. The analysis of gut metagenomes in different pig breeds showed that colicins B and M were enriched in Laiwu pigs, a Chinese local breed, but were scarce in boars and Duroc pigs. IMPORTANCE This study revealed the heterogeneity of E. coli strains from pigs, including two strains studied by both in silico and wet experiments in detail and 14 strains studied by bioinformatics analysis. E. coli Y18J may improve the adaptability of pigs toward disease resistance through the production of colicins B and M. Our findings could shed light on the pathogenic and harmless roles of E. coli in modern animal husbandry, leading to a better understanding of intestinal-microbe-pathogen interactions in the course of evolution.

Antioxidant potential of Pediococcus pentosaceus strains from the sow milk bacterial collection in weaned piglets.

BACKGROUND: In modern animal husbandry, breeders pay increasing attention to improving sow nutrition during pregnancy and lactation to favor the health of neonates. Sow milk is a main food source for piglets during their first three weeks of life, which is not only a rich repository of essential nutrients and a broad range of bioactive compounds, but also an indispensable source of commensal bacteria. Maternal milk microorganisms are important sources of commensal bacteria for the neonatal gut. Bacteria from maternal milk may confer a health benefit on the host. METHODS: Sow milk bacteria were isolated using culturomics followed by identification using 16S rRNA gene sequencing. To screen isolates for potential probiotic activity, the functional evaluation was conducted to assess their antagonistic activity against pathogens in vitro and evaluate their resistance against oxidative stress in damaged Drosophila induced by paraquat. In a piglet feeding trial, a total of 54 newborn suckling piglets were chosen from nine sows and randomly assigned to three treatments with different concentrations of a candidate strain. Multiple approaches were carried out to verify its antioxidant function including western blotting, enzyme activity analysis, metabolomics and 16S rRNA gene amplicon sequencing. RESULTS: The 1240 isolates were screened out from the sow milk microbiota and grouped into 271 bacterial taxa based on a nonredundant set of 16S rRNA gene sequencing. Among 80 Pediococcus isolates, a new Pediococcus pentosaceus strain (SMM914) showed the best performance in inhibition ability against swine pathogens and in a Drosophila model challenged by paraquat. Pretreatment of piglets with SMM914 induced the Nrf2-Keap1 antioxidant signaling pathway and greatly affected the pathways of amino acid metabolism and lipid metabolism in plasma. In the colon, the relative abundance of Lactobacillus was significantly increased in the high dose SMM914 group compared with the control group. CONCLUSION: P. pentosaceus SMM914 is a promising probiotic conferring antioxidant capacity by activating the Nrf2-Keap1 antioxidant signaling pathway in piglets. Our study provided useful resources for better understanding the relationships between the maternal microbiota and offspring. Video Abstract.

Genomic and Molecular Signatures of Successful Patient-Derived Xenografts for Oral Cavity Squamous Cell Carcinoma.

Background: Oral cavity squamous cell carcinoma (OSCC) is an aggressive malignant tumor with high recurrence and poor prognosis in the advanced stage. Patient-derived xenografts (PDXs) serve as powerful preclinical platforms for drug testing and precision medicine for cancer therapy. We assess which molecular signatures affect tumor engraftment ability and tumor growth rate in OSCC PDXs. Methods: Treatment-naïve OSCC primary tumors were collected for PDX models establishment. Comprehensive genomic analysis, including whole-exome sequencing and RNA-seq, was performed on case-matched tumors and PDXs. Regulatory genes/pathways were analyzed to clarify which molecular signatures affect tumor engraftment ability and the tumor growth rate in OSCC PDXs. Results: Perineural invasion was found as an important pathological feature related to engraftment ability. Tumor microenvironment with enriched hypoxia, PI3K-Akt, and epithelial-mesenchymal transition pathways and decreased inflammatory responses had high engraftment ability and tumor growth rates in OSCC PDXs. High matrix metalloproteinase-1 (MMP1) expression was found that have a great graft advantage in xenografts and is associated with pooled disease-free survival in cancer patients. Conclusion: This study provides a panel with detailed genomic characteristics of OSCC PDXs, enabling preclinical studies on personalized therapy options for oral cancer. MMP1 could serve as a biomarker for predicting successful xenografts in OSCC patients.

Enhancing Singlet Fission Coupling with Nonbonding Orbitals.

Singlet fission (SF) is a process where a singlet exciton is split into a pair of triplet excitons. The increase in the excitonic generation can be exploited to enhance the efficiency of solar cells. Molecules with conjugated π bonds are commonly developed for optoelectronic applications including SF, due to their low energy gaps. The electronic coupling for SF in such well-stacked π-conjugated molecule pairs can be rather limited due to the orthogonal π and π* orbital overlaps that are involved in the coupling elements, leading to a large cancellation in the coupling. In the present work, we show that such limits can be removed by involving triplet states of different origins, such as those with nonbonding n orbitals. We demonstrate such an effect for formaldehyde and methylenimine dimers, with a low-lying n-π* triplet state (T1) in addition to the π-π* triplet (T2). We show that the coupling can be enhanced by 40 times or more for the formaldehyde dimer, and 15 times or more for the methylenimine dimer, with the T1-T2 state as the end product of SF. With 1759 randomly oriented pairs of formaldehyde derived from a molecular dynamics simulation, the coupling from a singlet exciton to this T1-T2 state is, on an average, almost two times larger than that for a regular T1-T1 state. We investigated a few families that have been shown to be prospective candidates for SF, using our proposed strategy. However, our unfavorable results indicate that there are clear difficulties in fulfilling the ES1 ≳ ET1 + ET2 energy criterion. Nevertheless, our results provide a new molecular design concept for better SF (and triplet-triplet annihilation, TTA) materials that allows future development.

Nuclear accumulation of KPNA2 impacts radioresistance through positive regulation of the PLSCR1-STAT1 loop in lung adenocarcinoma.

Lung adenocarcinoma (ADC) is the predominant histological type of lung cancer, and radiotherapy is one of the current therapeutic strategies for lung cancer treatment. Unfortunately, biological complexity and cancer heterogeneity contribute to radioresistance development. Karyopherin α2 (KPNA2) is a member of the importin α family that mediates the nucleocytoplasmic transport of cargo proteins. KPNA2 overexpression is observed across cancer tissues of diverse origins. However, the role of KPNA2 in lung cancer radioresistance is unclear. Herein, we demonstrated that high expression of KPNA2 is positively correlated with radioresistance and cancer stem cell (CSC) properties in lung ADC cells. Radioresistant cells exhibited nuclear accumulation of KPNA2 and its cargos (OCT4 and c-MYC). Additionally, KPNA2 knockdown regulated CSC-related gene expression in radioresistant cells. Next-generation sequencing and bioinformatic analysis revealed that STAT1 activation and nuclear phospholipid scramblase 1 (PLSCR1) are involved in KPNA2-mediated radioresistance. Endogenous PLSCR1 interacting with KPNA2 and PLSCR1 knockdown suppressed the radioresistance induced by KPNA2 expression. Both STAT1 and PLSCR1 were found to be positively correlated with dysregulated KPNA2 in radioresistant cells and ADC tissues. We further demonstrated a potential positive feedback loop between PLSCR1 and STAT1 in radioresistant cells, and this PLSCR1-STAT1 loop modulates CSC characteristics. In addition, AKT1 knockdown attenuated the nuclear accumulation of KPNA2 in radioresistant lung cancer cells. Our results collectively support a mechanistic understanding of a novel role for KPNA2 in promoting radioresistance in lung ADC cells.

Chemotherapeutic Drug-Regulated Cytokines Might Influence Therapeutic Efficacy in HCC.

Hepatocellular carcinoma (HCC), the most common type of liver cancer, is the second leading cause of cancer-related mortality worldwide. Processes involved in HCC progression and development, including cell transformation, proliferation, metastasis, and angiogenesis, are inflammation-associated carcinogenic processes because most cases of HCC develop from chronic liver damage and inflammation. Inflammation has been demonstrated to be a crucial factor inducing tumor development in various cancers, including HCC. Cytokines play critical roles in inflammation to accelerate tumor invasion and metastasis by mediating the migration of immune cells into damaged tissues in response to proinflammatory stimuli. Currently, surgical resection followed by chemotherapy is the most common curative therapeutic regimen for HCC. However, after chemotherapy, drug resistance is clearly observed, and cytokine secretion is dysregulated. Various chemotherapeutic agents, including cisplatin, etoposide, and 5-fluorouracil, demonstrate even lower efficacy in HCC than in other cancers. Tumor resistance to chemotherapeutic drugs is the key limitation of curative treatment and is responsible for treatment failure and recurrence, thus limiting the ability to treat patients with advanced HCC. Therefore, the capability to counteract drug resistance would be a major clinical advancement. In this review, we provide an overview of links between chemotherapeutic agents and inflammatory cytokine secretion in HCC. These links might provide insight into overcoming inflammatory reactions and cytokine secretion, ultimately counteracting chemotherapeutic resistance.

Characterization of Recurrent Relevant Genes Reveals a Novel Role of RPL36A in Radioresistant Oral Squamous Cell Carcinoma.

Radioresistance is one of the major factors that contributes to radiotherapy failure in oral cavity squamous cell carcinoma (OSCC). By comparing the prognostic values of 20,502 genes expressed in patients in The Cancer Genome Atlas (TCGA)-OSCC cohort with (n = 162) and without radiotherapy (n = 118), herein identified 297 genes positively correlated with poor disease-free survival in OSCC patients with radiotherapy as the potential radioresistance-associated genes. Among the potential radioresistance-associated genes, 36 genes were upregulated in cancerous tissues relative to normal tissues. The bioinformatics analysis revealed that 60S ribosomal protein L36a (RPL36A) was the most frequently detected gene involved in radioresistance-associated gene-mediated biological pathways. Then, two independent cohorts (n = 162 and n = 136) were assessed to confirm that higher RPL36A transcript levels were significantly associated with a poor prognosis only in OSCC patients with radiotherapy. Mechanistically, we found that knockdown of RPL36A increased radiosensitivity via sensitizing cells to DNA damage and promoted G2/M cell cycle arrest followed by augmenting the irradiation-induced apoptosis pathway in OSCC cells. Taken together, our study supports the use of large-scale genomic data for identifying specific radioresistance-associated genes and suggests a regulatory role for RPL36A in the development of radioresistance in OSCC.

Irradiation Suppresses IFNγ-Mediated PD-L1 and MCL1 Expression in EGFR-Positive Lung Cancer to Augment CD8+ T Cells Cytotoxicity.

Tumor cells express immune checkpoints to exhaust CD8+ T cells. Irradiation damages tumor cells and augments tumor immunotherapy in clinical applications. However, the radiotherapy-mediated molecular mechanism affecting CD8+ T cell activity remains elusive. We aimed to uncover the mechanism of radiotherapy augmenting cytotoxic CD8+ T cells in non-small-cell lung cancer (NSCLC). EGFR-positive NSCLC cell lines were co-cultured with CD8+ T cells from healthy volunteers. Tumor cell viability and apoptosis were consequently measured. IFNγ was identified secreted by CD8+ T cells and PBMCs. Therefore, RNAseq was used to screen the IFNγ-mediated gene expression in A549 cells. The irradiation effect to IFNγ-mediated gene expression was investigated using qPCR and western blots. We found that the co-culture of tumor cells stimulated the increase of granzyme B and IFNγ in CD8+ T, but A549 exhibited resistance against CD8+ T cytotoxicity compared to HCC827. Irradiation inhibited A549 proliferation and enhanced apoptosis, augmenting PBMCs-mediated cytotoxicity against A549. We found that IFNγ simultaneously increased phosphorylation on STAT1 and STAT3 in EGFR-positive lung cancer, resulting in overexpression of PD-L1 (p < 0.05). In RNAseq analysis, MCL1 was identified and increased by the IFNγ-STAT3 axis (p < 0.05). We demonstrated that irradiation specifically inhibited phosphorylation on STAT1 and STAT3 in IFNγ-treated A549, resulting in reductions of PD-L1 and MCL1 (both p < 0.05). Moreover, knockdowns of STAT3 and MCL1 increased the PBMCs-mediated anti-A549 effect. This study demonstrated that A549 expressed MCL1 to resist CD8+ T cell-mediated tumor apoptosis. In addition, we found that irradiation suppressed IFNγ-mediated STAT3 phosphorylation and PD-L1 and MCL1 expression, revealing a potential mechanism of radiotherapy augmenting immune surveillance.