T-cell subsets and cytokines are indicative of neoadjuvant chemoimmunotherapy responses in NSCLC.

PURPOSE: Neoadjuvant PD-1 blockade combined with chemotherapy is a promising treatment for resectable non-small cell lung cancer (NSCLC), yet the immunological mechanisms contributing to tumor regression and biomarkers corresponding to different pathological responses remain unclear. METHODS: Using dynamic and paired blood samples from NSCLC patients receiving neoadjuvant chemoimmunotherapy, we analyzed the frequencies of CD8 + T-cell and Treg subsets and their dynamic changes during neoadjuvant treatment through flow cytometry. Cytokine profiles and function-related gene expression of CD8 + T cells and Tregs were analyzed through flow cytometry and mRNA-seq. Infiltrating T-cell subsets in resected tissues from patients with different pathological responses were analyzed through multiplex immunofluorescence. RESULTS: Forty-two NSCLC patients receiving neoadjuvant chemoimmunotherapy were enrolled and then underwent surgical resection and pathological evaluation. Nineteen patients had pCR (45%), 7 patients had MPR (17%), and 16 patients had non-MPR (38%). In patients with pCR, the frequencies of CD137 + CD8 + T cells (P = 0.0475), PD-1 + Ki-67 + CD8 + T cells (P = 0.0261) and Tregs (P = 0.0317) were significantly different from those of non-pCR patients before treatment. pCR patients usually had low frequencies of CD137 + CD8 + T cells, PD-1 + Ki-67 + CD8 + T cells and Tregs, and their AUCs were higher than that of tissue PD-L1 expression. Neoadjuvant chemoimmunotherapy markedly improved CD8 + T-cell proliferation and activation, especially in pCR patients, as the frequencies of CD137 + CD8 + (P = 0.0136) and Ki-67 + CD8 + (P = 0.0391) T cells were significantly increased. The blood levels of cytokines such as IL-2 (P = 0.0391) and CXCL10 (P = 0.0195) were also significantly increased in the pCR group, which is consistent with the high density of activated cytotoxic T cells at the tumor site (P < 0.0001). CONCLUSION: Neoadjuvant chemoimmunotherapy drives CD8 + T cells toward a proliferative and active profile. The frequencies of CD137 + CD8 + T cells, PD-1 + Ki-67 + CD8 + T cells and Tregs at baseline might predict the response to neoadjuvant chemoimmunotherapy in NSCLC patients. The increase in IL-2 and CXCL10 might reflect the chemotaxis and enrichment of cytotoxic T cells at the tumor site and a better response to neoadjuvant chemoimmunotherapy.

Easily applicable predictive score for MPR based on parameters before neoadjuvant chemoimmunotherapy in operable NSCLC: a single-center, ambispective, observational study.

BACKGROUND: Neoadjuvant chemoimmunotherapy (NACI) is promising for resectable nonsmall cell lung cancer (NSCLC), but predictive biomarkers are still lacking. The authors aimed to develop a model based on pretreatment parameters to predict major pathological response (MPR) for such an approach. METHODS: The authors enrolled operable NSCLC treated with NACI between March 2020 and May 2023 and then collected baseline clinical-pathology data and routine laboratory examinations before treatment. The efficacy and safety data of this cohort was reported and variables were screened by Logistic and Lasso regression and nomogram was developed. In addition, receiver operating characteristic curves, calibration curves, and decision curve analysis were used to assess its power. Finally, internal cross-validation and external validation was performed to assess the power of the model. RESULTS: In total, 206 eligible patients were recruited in this study and 53.4% (110/206) patients achieved MPR. Using multivariate analysis, the predictive model was constructed by seven variables, prothrombin time (PT), neutrophil percentage (NEUT%), large platelet ratio (P-LCR), eosinophil percentage (EOS%), smoking, pathological type, and programmed death ligand-1 (PD-L1) expression finally. The model had good discrimination, with area under the receiver operating characteristic curve (AUC) of 0.775, 0.746, and 0.835 for all datasets, cross-validation, and external validation, respectively. The calibration curves showed good consistency, and decision curve analysis indicated its potential value in clinical practice. CONCLUSION: This real world study revealed favorable efficacy in operable NSCLC treated with NACI. The proposed model based on multiple clinically accessible parameters could effectively predict MPR probability and could be a powerful tool in personalized medication.

Performance of SHOX2 and RASSF1A methylation assay in supernatants and matched cell pellets for the diagnosis of malignant pleural effusion.

BACKGROUND: It is difficult to distinguish between malignant pleural effusion (MPE) and benign pleural effusion (BPE). The purpose of this study was to determine the best specimen type by evaluating the DNA methylation status of SHOX2 and RASSF1A in 3 matched PE components. METHODS: In total, 94 patients were enrolled, including 45 MPE, 35 BPE, and 14 undefined PE (UPE) with malignancies. PE samples were processed into supernatants, fresh-cell pellets, and formalin-fixed and paraffin-embedded (FFPE) cell blocks, respectively. A quantitative real-time PCR was used to detect the methylation status of SHOX2 and RASSF1A. RESULTS: SHOX2 and RASSF1A methylation levels were significantly higher in the 3 MPE sample types than those of BPE (P < 0.05). The area under the curve using cell-free DNA (cf-DNA) was the highest. The detection sensitivity of SHOX2 and RASSF1A in fresh-cell DNA, cf-DNA and FFPE cell-block were 71.1% (32/45), 97.8% (44/45) and 66.7% (28/42), respectively, with specificities of 97.1% (34/35), 94.3% (33/35), and 96.9% (31/32). Notably, a combination of the cytological analysis and cf-DNA methylation assay showed an increase in positivity rate from 75.6% to 100%. CONCLUSIONS: The SHOX2 and RASSF1A methylation assay using cf-DNA, the primary recommended specimen type, can excellently increase the diagnostic sensitivity of MPE. A combination of methylation assay with cytological analysis can be used for auxiliary diagnosis of PE.

The expanding Pandora's toolbox of CD8+T cell: from transcriptional control to metabolic firing.

CD8+ T cells are the executor in adaptive immune response, especially in anti-tumor immunity. They are the subset immune cells that are of high plasticity and multifunction. Their development, differentiation, activation and metabolism are delicately regulated by multiple factors. Stimuli from the internal and external environment could remodel CD8+ T cells, and correspondingly they will also make adjustments to the microenvironmental changes. Here we describe the most updated progresses in CD8+ T biology from transcriptional regulation to metabolism mechanisms, and also their interactions with the microenvironment, especially in cancer and immunotherapy. The expanding landscape of CD8+ T cell biology and discovery of potential targets to regulate CD8+ T cells will provide new viewpoints for clinical immunotherapy.

Simultaneous diagnosis of tuberculous pleurisy and malignant pleural effusion using metagenomic next-generation sequencing (mNGS).

BACKGROUND: Metagenomic next-generation sequencing (mNGS) has become a powerful tool for pathogen detection, but the value of human sequencing reads generated from it is underestimated. METHODS: A total of 138 patients with pleural effusion (PE) were diagnosed with tuberculous pleurisy (TBP, N = 82), malignant pleural effusion (MPE, N = 35), or non-TB infection (N = 21), whose PE samples all underwent mNGS analysis. Clinical TB tests including culture, Acid-Fast Bacillus (AFB) test, Xpert, and T-SPOT, were performed. To utilize mNGS for MPE identification, 25 non-MPE samples (20 TBP and 5 non-TB infection) were randomly selected to set human chromosome copy number baseline and generalized linear modeling was performed using copy number variant (CNV) features of the rest 113 samples (35 MPE and 78 non-MPE). RESULTS: The performance of TB detection was compared among five methods. T-SPOT demonstrated the highest sensitivity (61% vs. culture 32%, AFB 12%, Xpert 35%, and mNGS 49%) but with the highest false-positive rate (10%) as well. In contrast, mNGS was able to detect TB-genome in nearly half (40/82) of the PE samples from TBP subgroup, with 100% specificity. To evaluate the performance of using CNV features of the human genome for MPE prediction, we performed the leave-one-out cross-validation (LOOCV) in the subcohort excluding the 25 non-MPE samples for setting copy number standards, which demonstrated 54.1% sensitivity, 80.8% specificity, 71.7% accuracy, and an AUC of 0.851. CONCLUSION: In summary, we exploited the value of human and non-human sequencing reads generated from mNGS, which showed promising ability in simultaneously detecting TBP and MPE.

Single-cell profiling reveals distinct immune response landscapes in tuberculous pleural effusion and non-TPE.

Background: Tuberculosis (TB) is caused by Mycobacterium tuberculosis (Mtb) and remains a major health threat worldwide. However, a detailed understanding of the immune cells and inflammatory mediators in Mtb-infected tissues is still lacking. Tuberculous pleural effusion (TPE), which is characterized by an influx of immune cells to the pleural space, is thus a suitable platform for dissecting complex tissue responses to Mtb infection. Methods: We employed singe-cell RNA sequencing to 10 pleural fluid (PF) samples from 6 patients with TPE and 4 non-TPEs including 2 samples from patients with TSPE (transudative pleural effusion) and 2 samples with MPE (malignant pleural effusion). Result: Compared to TSPE and MPE, TPE displayed obvious difference in the abundance of major cell types (e.g., NK, CD4+T, Macrophages), which showed notable associations with disease type. Further analyses revealed that the CD4 lymphocyte population in TPE favored a Th1 and Th17 response. Tumor necrosis factors (TNF)-, and XIAP related factor 1 (XAF1)-pathways induced T cell apoptosis in patients with TPE. Immune exhaustion in NK cells was an important feature in TPE. Myeloid cells in TPE displayed stronger functional capacity for phagocytosis, antigen presentation and IFN-γ response, than TSPE and MPE. Systemic elevation of inflammatory response genes and pro-inflammatory cytokines were mainly driven by macrophages in patients with TPE. Conclusion: We provide a tissue immune landscape of PF immune cells, and revealed a distinct local immune response in TPE and non-TPE (TSPE and MPE). These findings will improve our understanding of local TB immunopathogenesis and provide potential targets for TB therapy.

High accuracy epidermal growth factor receptor mutation prediction via histopathological deep learning.

BACKGROUND: The detection of epidermal growth factor receptor (EGFR) mutations in patients with non-small cell lung cancer is critical for tyrosine kinase inhibitor therapy. EGFR detection requires tissue samples, which are difficult to obtain in some patients, costing them the opportunity for further treatment. To realize EGFR mutation prediction without molecular detection, we aimed to build a high-accuracy deep learning model with only haematoxylin and eosin (H&E)-stained slides. METHODS: We collected 326 H&E-stained non-small cell lung cancer slides from Beijing Chest Hospital, China, and used 226 slides (88 with EGFR mutations) for model training. The remaining 100 images (50 with EGFR mutations) were used for testing. We trained a convolutional neural network based on ResNet-50 to classify EGFR mutation status on the slide level. RESULTS: The sensitivity and specificity of the model were 76% and 74%, respectively, with an area under the curve of 0.82. When applying the double-threshold approach, 33% of the patients could be predicted by the deep learning model as EGFR positive or negative with a sensitivity and specificity of 100.0% and 87.5%. The remaining 67% of the patients got an uncertain result and will be recommenced to perform further examination. By incorporating adenocarcinoma subtype information, we achieved 100% sensitivity in predicting EGFR mutations in 37.3% of adenocarcinoma patients. CONCLUSIONS: Our study demonstrates the potential of a deep learning-based EGFR mutation prediction model for rapid and cost-effective pre-screening. It could serve as a high-accuracy complement to current molecular detection methods and provide treatment opportunities for non-small cell lung cancer patients from whom limited samples are available.

Deep learning-based diagnosis of histopathological patterns for invasive non-mucinous lung adenocarcinoma using semantic segmentation.

OBJECTIVES: The application of artificial intelligence (AI) to the field of pathology has facilitated the development of digital pathology, hence, making AI-assisted diagnosis possible. Due to the variety of lung cancers and the subjectivity of manual evaluation, invasive non-mucinous lung adenocarcinoma (ADC) is difficult to diagnose. We aim to offer a deep learning solution that automatically classifies invasive non-mucinous lung ADC histological subtypes. DESIGN: For this investigation, 523 whole-slide images (WSIs) were obtained. We divided 376 of the WSIs at random for model training. According to WHO diagnostic criteria, six histological components of invasive non-mucinous lung ADC, comprising lepidic, papillary, acinar, solid, micropapillary and cribriform arrangements, were annotated at the pixel level and employed as the predicting target. We constructed the deep learning model using DeepLab v3, and used 27 WSIs for model validation and the remaining 120 WSIs for testing. The predictions were analysed by senior pathologists. RESULTS: The model could accurately predict the predominant subtype and the majority of minor subtypes and has achieved good performance. Except for acinar, the area under the curve of the model was larger than 0.8 for all the subtypes. Meanwhile, the model was able to generate pathological reports. The NDCG scores were greater than 75%. Through the analysis of feature maps and incidents of model misdiagnosis, we discovered that the deep learning model was consistent with the thought process of pathologists and revealed better performance in recognising minor lesions. CONCLUSIONS: The findings of the deep learning model for predicting the major and minor subtypes of invasive non-mucinous lung ADC are favourable. Its appearance and sensitivity to tiny lesions can be of great assistance to pathologists.

PCSK9 regulates the efficacy of immune checkpoint therapy in lung cancer.

Proprotein convertase subtilisin/kexin type 9 (PCSK9) secreted by tumors was reported as a deleterious factor that led to the reduction of lymphocyte infiltration and the poorer efficacy of ICIs in vivo. This study aimed to explore whether PCSK9 expression in tumor tissue could predict the response of advanced non-small cell lung cancer (NSCLC) to anti-PD-1 immunotherapy and the synergistic antitumor effect of the combination of the PCSK9 inhibitor with the anti-CD137 agonist. One hundred fifteen advanced NSCLC patients who received anti-PD-1 immunotherapy were retrospectively studied with PCSK9 expression in baseline NSCLC tissues detected by immunohistochemistry (IHC). The mPFS of the PCSK9lo group was significantly longer than that of the PCSK9hi group [8.1 vs. 3.6 months, hazard ratio (HR): 3.450; 95% confidence interval (CI), 2.166-5.496]. A higher objective response rate (ORR) and a higher disease control rate (DCR) were observed in the PCSK9lo group than in the PCSK9hi group (54.4% vs. 34.5%, 94.7% vs. 65.5%). Reduction and marginal distribution of CD8+ T cells were observed in PCSK9hi NSCLC tissues. Tumor growth was retarded by the PCSK9 inhibitor and the anti-CD137 agonist alone in the Lewis lung carcinoma (LLC) mice model and further retarded by the PCSK9 inhibitor in combination with the CD137 agonist with long-term survival of the host mice with noticeable increases of CD8+ and GzmB+ CD8+ T cells and reduction of Tregs. Together, these results suggested that high PCSK9 expression in baseline tumor tissue was a deleterious factor for the efficacy of anti-PD-1 immunotherapy in advanced NSCLC patients. The PCSK9 inhibitor in combination with the anti-CD137 agonist could not only enhance the recruitment of CD8+ and GzmB+ CD8+ T cells but also deplete Tregs, which may be a novel therapeutic strategy for future research and clinical practice.

Biomarkers Correlated with Tuberculosis Preventive Treatment Response: A Systematic Review and Meta-Analysis.

BACKGROUND: There is a need to identify alternative biomarkers to predict tuberculosis (TB) preventive treatment response because observing the incidence decline renders a long follow-up period. METHODS: We searched PubMed, Embase and Web of Science up to 9 February 2023. The biomarker levels during preventive treatment were quantitatively summarized by means of meta-analysis using the random-effect model. RESULTS: Eleven eligible studies, published during 2006-2022, were included in the meta-analysis, with frequently heterogeneous results. Twenty-six biomarkers or testing methods were identified regarding TB preventive treatment monitoring. The summarized standard mean differences of interferon-γ (INF-γ) were -1.44 (95% CI: -1.85, -1.03) among those who completed preventive treatment (τ2 = 0.21; I2 = 95.2%, p < 0.001) and -0.49 (95% CI: -1.05, 0.06) for those without preventive treatment (τ2 = 0.13; I2 = 82.0%, p < 0.001), respectively. Subgroup analysis showed that the INF-γ level after treatment decreased significantly from baseline among studies with high TB burden (-0.98, 95% CI: -1.21, -0.75) and among those with a history of Bacillus Calmette-Guérin vaccination (-0.87, 95% CI: -1.10, -0.63). CONCLUSIONS: Our results suggested that decreased INF-γ was observed among those who completed preventive treatment but not in those without preventive treatment. Further studies are warranted to explore its value in preventive treatment monitoring due to limited available data and extensive between-study heterogeneity.

Detection of antigen Ag85B expression is useful for the diagnosis of tuberculosis, especially for those with an antituberculosis treatment history.

OBJECTIVES: The present study used immunohistochemistry (IHC) to detect antigen Ag85B in tissue sections and aimed to evaluate its validity in histopathologic diagnosis of tuberculosis (TB). METHODS: In total, 204 patients with confirmed TB and 40 other diseases were included in the present study. Ziehl-Neelsen (Z-N) stains, IHC (anti-Ag85B), and quantitative fluorescence polymerase chain reaction were used to detect acid-fast bacilli, Mycobacterium tuberculosis (MTB) antigen, and MTB DNA. RESULTS: Immunohistochemistry was significantly more sensitive than Z-N stains (93.1% vs 67.2%; P < .001). The sensitivity of Z-N stains significantly correlated with anti-TB treatment history. The sensitivity of Z-N stains was lower in rifampicin (RIF)-resistant TB compared with RIF-sensitive TB (52.8% vs 69.0%; P = .091) and those without treatment history (52.8% vs 84.0%; P = .015). However, IHC was not significantly affected by treatment history (P = .410). Moreover, expression patterns of Ag85B were dependent on treatment history and commonly showed weak scattered spots in RIF-susceptible TB. Conversely, strong brown rods were often found in those with RIF-resistant TB. CONCLUSIONS: Immunohistochemistry is a simple, sensitive technique for the diagnosis of TB, especially for those patients with treatment history. The expression pattern of Ag85B is a potential marker for evaluating anti-TB treatment response.

DNA Methylation Analysis of the SHOX2 and RASSF1A Panel Using Cell-Free DNA in the Diagnosis of Malignant Pleural Effusion.

Objectives: The differential diagnosis of pleural effusion (PE) is a common but major challenge in clinical practice. This study aimed to establish a strategy based on a PE-cell-free DNA (cfDNA) methylation detection system for the differential diagnosis of malignant pleural effusion (MPE) and benign pleural effusion (BPE). Methods: A total of 104 patients with PE were enrolled in this study, among which 50 patients had MPE, 9 malignant tumor patients had PE of indefinite causes, and the other 45 patients were classified as benign controls. The methylation status of short stature homeobox 2 (SHOX2) and RAS association domain family 1, isoform A (RASSF1A) was detected using PE-cfDNA specimens by real-time fluorescence quantitative PCR. Total methylation (TM) was defined as the combination of the methylation levels of SHOX2 and RASSF1A. The electrochemiluminescence immunoassay was applied to evaluate the levels of multiple serum tumor markers. Results: The PE-cfDNA methylation status of either SHOX2 or RASSF1A was much higher in MPE samples than in benign controls. The combination of SHOX2 and RASSF1A methylation in PE yielded a diagnostic sensitivity of 96% and a specificity of 100%, respectively. When compared with the corresponding serum tumor marker detection results, TM showed the highest diagnostic efficiency (AUC = 0.985). Furthermore, the combination of the SHOX2 and RASSF1A methylation panels using PE-cfDNA could apparently improve the differential diagnostic efficacy of BPE and MPE and could help compensate for the deficiency of cytology. Conclusions: Our results indicated that SHOX2 and RASSF1A methylation panel detection could accurately classify BPE and MPE diseases and showed better diagnostic performance than traditional serum parameters. The SHOX2 and RASSF1A methylation detection of PE-cfDNA could be a potentially effective complementary tool for cytology in the process of differential diagnosis. In summary, PE-cfDNA could be used as a promising non-invasive analyte for the auxiliary diagnosis of MPE.

Real-world analysis of the prognostic value of EGFR mutation detection in plasma ctDNA from patients with advanced non-small cell lung cancer.

BACKGROUND: The plasma sample has emerged as a promising surrogate sample for EGFR mutation detection in advanced non-small cell lung cancer (NSCLC). In clinical practice, whether EGFR variants in baseline plasma ctDNA of advanced NSCLC can predict prognosis in addition to guiding targeted therapy remains to be further explored. MATERIAL AND METHODS: In total, 315 NSCLC patients were retrospectively enrolled. EGFR mutation data from tissue detected by ARMS-PCR and paired plasma samples within 1 month of admission detected by SuperARMS or ARMS-PCR were collected. The correlation between baseline plasma ctDNA EGFR mutation status and survival was compared. RESULTS: EGFR mutation detection rates in tumor samples and plasma samples were 65.1% (205/315) and 43.8% (138/315). Referred to tissue results, the consistent rate of test ctDNA EGFR alteration by SuperARMS was higher than that detected by ARMS (79.5% vs. 69.0%, p = 0.04), either in stage I-IIIA patients (85.7% vs. 50.0%, p = 0.4) or stage IIIB-IV patients (79.1% vs. 69.4%, p = 0.04). Patients' treatment status and pathological subtype were the two factors that affected plasma ctDNA EGFR alteration detection accuracy. The concordance in non-adenocarcinoma patients was obviously higher than that in adenocarcinoma (p = 0.02), and the concordance in treatment naïve patients was significantly higher than that in relapse patients (p = 0.047). In treatment naïve patients, the median PFS (mPFS) in plasma ctDNA EGFR-positive patients was shorter than that in plasma ctDNA EGFR negative patients (7.0 vs. 10.0 months, p = 0.01). In relapsed patients, the mPFS in plasma ctDNA EGFR-positive patients was 9.0 months versus 11.0 months in plasma ctDNA EGFR negative patients (p = 0.1). CONCLUSIONS: A plasma sample could be an alternative for a molecular test when tissue samples was unavailable. The SuperARMS-PCR detection method has high sensitivity in real-world clinical practice. Furthermore, in patients with stage IIIB-IV, baseline plasma ctDNA EGFR mutation positivity not only guides targeted therapy but also predicts a worse prognosis.

Weakly Supervised Deep Nuclei Segmentation With Sparsely Annotated Bounding Boxes for DNA Image Cytometry.

Nuclei segmentation is an essential step in DNA ploidy analysis by image-based cytometry (DNA-ICM) which is widely used in cytopathology and allows an objective measurement of DNA content (ploidy). The routine fully supervised learning-based method requires often tedious and expensive pixel-wise labels. In this paper, we propose a novel weakly supervised nuclei segmentation framework which exploits only sparsely annotated bounding boxes, without any segmentation labels. The key is to integrate the traditional image segmentation and self-training into fully supervised instance segmentation. We first leverage the traditional segmentation to generate coarse masks for each box-annotated nucleus to supervise the training of a teacher model, which is then responsible for both the refinement of these coarse masks and pseudo labels generation of unlabeled nuclei. These pseudo labels and refined masks along with the original manually annotated bounding boxes jointly supervise the training of student model. Both teacher and student share the same architecture and especially the student is initialized by the teacher. We have extensively evaluated our method with both our DNA-ICM dataset and public cytopathological dataset. Without bells and whistles, our method outperforms all existing weakly supervised entries on both datasets. Code and our DNA-ICM dataset are publicly available at https://github.com/CVIU-CSU/Weakly-Supervised-Nuclei-Segmentation.

Bacteriomes in lesions of pulmonary tuberculosis and its association with status of Mycobacterium tuberculosis excretion.

BACKGROUND: Bacteria in lung play an important role in sustaining lung health. Understanding the characteristics of bacteriomes in lesions of pulmonary tuberculosis (TB) patients, who excrete Mycobacterium tuberculosis (MTB), is important for TB prevention and effective treatment.  METHODS: In this study, bacteriomes in lesions from TB patients excreting bacteria (TB-E) and those from TB patients not excreting bacteria (TB-NE) with matched normal lung tissues (NT) were compared by 16S rRNA sequencing. Bacterial MetaCyc functions in TB lesions were also predicted by PICRUSt2 tool. RESULTS: Alpha diversity of bacteria, including Chao 1 and Shannon indexes, for TB-E was significantly higher than those in TB-NE and NT; while for TB-NE group, Chao 1 index was higher than that in NT group. Predominant phyla in TB lesions and NT were Proteobacteria, Actinobacteria, Firmicutes, and Bacteroidetes, but analysis of similarity (ANOSIM, p < 0.001) revealed significantly different bacterial compositions among TB-E, TB-NE and NT samples. As for bacteriomes in TB lesions, a strong association (ANOSIM, p < 0.001) was observed with the status of MTB excretion. Indicator genera identified in TB-E and TB-NE demonstrated distinctive micro-ecological environments of TB lesions from patients with different clinical manifestations. Co-occurrence analysis revealed a densely-linked bacterial community in TB-NE compared to that in TB-E. MetaCyc functions responsible for menaquinone synthesis and chorismate metabolism that could potentially impact the persistent-state and nutrient metabolism of MTB were enriched in TB-E samples. While in TB-NE samples, enrichment of bacterial MetaCyc function responsible for heme b synthesis might contribute to TB pathology through ferroptosis. CONCLUSION: Bacteriomes and their MetaCyc functions in TB lesions are elucidated, and they are associated with status of MTB excretion among pulmonary TB patients. These results serve as a basis for designing novel strategies for preventing and treating pulmonary TB disease.

Lentiviral vector-based xenograft tumors as candidate reference materials for detection of HER2-low breast cancer.

The human epidermal growth factor receptor 2 (HER2) is an important biomarker that plays a pivotal role in therapeutic decision-making for patients with breast cancer (BC). Patients with HER2-low BC can benefit from new HER2 targeted therapy. For ensuring the accurate and reproducible detection of HER2-low cancer, reliable reference materials are required for monitoring the sensitivity and specificity of detection assays. Herein, a lentiviral vector was used to transduce the HER2 gene into MDA-MB-231 cells that exhibited low HER2 density, and the cells were characterized by droplet digital PCR to accurately determine the copy number variation. Then, the formalin-fixed paraffin-embedded (FFPE) samples from xenografts were prepared and evaluated for suitability as candidate reference materials by immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH). The FFPE reference materials were selected on the basis of IHC score of 2+ and negative FISH result to meet the requirement for HER2-low BC detection. Furthermore, the FFPE reference materials exhibited typical histological structures that resembled the clinical BC specimens. These novel FFPE reference materials displayed the high stability and homogeneity, and they were produced in high quantity. In summary, we generated high-quality reference materials for internal quality control and proficiency testing in HER2-low detection.

Spatial bacterial subpopulations of a human lung lobe and their potential impact on the progression of pulmonary tuberculosis.

Better understanding the spatial variation in resident pulmonary bacteria can help to link the disease severity of pulmonary tuberculosis (TB) with lung bacteriomes. This study aimed to investigate bacterial compositions in subniches of a lung lobe from pulmonary TB patient with two separate visible lesions. There were no significant differences between the bacterial compositions in normal tissue and TB lesions, but the bacterial compositions of the two TB lesions differed significantly (P = 0.009). Interestingly, 52 OTUs (relative abundance >1%) that specifically inhabiting certain lung niches were observed and they were affiliated with five phyla. Specific OTUs affiliated with Firmicutes mainly inhabited normal tissues. The dominant phylum in the lung subniches was Proteobacteria, with a relative abundance between 67.03% and 99.99%. Ralstonia, Achromobacter, and Pseudomonas were the most abundant genera, collectively accounting for 34.02% of total bacterial species. A total of 667 of the 700 bacterial connections in a co-correlation network of 145 OTUs (Operational Taxonomic Unit) were positive, indicating a cooperative relationship between bacterial members. Using PICRUSt tool, we do predict bacterial MetaCyc functions responsible for lipid synthesis and heme biosynthesis across the lung lobe that are essential for generation of caseous necrosis and TB disease pathology. MetaCyc pathways responsible for the degradation of aromatic biogenic amines, sulfur oxidation, and denitrification were all related to M.tb growth status, and they were significantly enriched in the lesion with necrosis than that with inflammation. These results open a new insight for us to comprehend the spatial profile of bacteriomes in a pulmonary TB human lung lobe, and shed light on the design of future diagnosis and treatment for pulmonary TB disease.

Genomic and resistome analysis of Alcaligenes faecalis strain PGB1 by Nanopore MinION and Illumina Technologies.

BACKGROUND: Drug-resistant bacteria are important carriers of antibiotic-resistant genes (ARGs). This fact is crucial for the development of precise clinical drug treatment strategies. Long-read sequencing platforms such as the Oxford Nanopore sequencer can improve genome assembly efficiency particularly when they are combined with short-read sequencing data. RESULTS: Alcaligenes faecalis PGB1 was isolated and identified with resistance to penicillin and three other antibiotics. After being sequenced by Nanopore MinION and Illumina sequencer, its entire genome was hybrid-assembled. One chromosome and one plasmid was assembled and annotated with 4,433 genes (including 91 RNA genes). Function annotation and comparison between strains were performed. A phylogenetic analysis revealed that it was closest to A. faecalis ZD02. Resistome related sequences was explored, including ARGs, Insert sequence, phage. Two plasmid aminoglycoside genes were determined to be acquired ARGs. The main ARG category was antibiotic efflux resistance and ß-lactamase (EC 3.5.2.6) of PGB1 was assigned to Class A, Subclass A1b, and Cluster LSBL3. CONCLUSIONS: The present study identified the newly isolated bacterium A. faecalis PGB1 and systematically annotated its genome sequence and ARGs.

CD155 expression impairs anti-PD1 therapy response in non-small cell lung cancer.

CD155 is an immune checkpoint protein expressed in tumor cells that interacts with its ligand TIGIT, and inhibition of this point presents a new and novel way for cancer therapy. At present, whether the expression of CD155 affects the response to anti(α)-PD1 treatment in non-small cell lung cancer (NSCLC) patients is unclear. This observational study characterizes the expression of CD155 in NSCLC patients and its responses to PD1 inhibitors. We retrospectively detected the expression of CD155 and tumor-infiltrated lymphocyte (TIL) TIGIT by immunohistochemistry in advanced NSCLC patients who had received αPD1 therapy. The patients with CD155 positive had a significantly worse response to αPD1 therapy compared with CD155-negative patients (ORR: 25.6% vs 54.8%, P < 0.01; median PFS: 5.1 vs 7.1 months, HR = 2.322; 95% CI 1.396-3.861, P = 0.001). This effect is more prominent in PD-L1 positive patients. In PD-L1-positive patients, CD155 expression is associated with a poor response to αPD1 therapy in both LUAC (lung adenocarcinoma) and LUSC (lung squamous cell carcinoma); meanwhile, the expression of CD155 was associated with a poor response to the first-line αPD1 therapy, posterior-line αPD1 therapy, and αPD1 combination therapy. Furthermore, the expression of TIGIT was not correlated with the therapeutic effect of αPD1. Our pilot study suggests that CD155 expression attenuates the therapeutic effect of αPD1 therapy and is associated with a higher risk of progression. The CD155 pathway may be a promising immunotherapeutic target and simultaneously targeting CD155/TIGIT and PD1/PD-L1 can improve the effect of immunotherapy.

Clinicopathologic and molecular characteristics of Chinese lung adenocarcinoma patients with EGFR exon 20 insertion mutations.

Background: Epidermal growth factor receptor exon 20 insertions (EGFR ex20ins) occur in about 4-14% of lung adenocarcinoma (LUAD) patients with EGFR mutations. Recently some targeted drugs have been approved for the treatment of LUAD patients with EGFR ex20ins. However, the heterogeneity of EGFR ex20ins mutations and resultant challenges in identifying them have led to the underestimation of their frequency. Methods: We investigated the molecular and clinicopathologic features of EGFR ex20ins in 3,892 Chinese LUAD patients using next-generation sequencing (NGS). The frequency and distribution of EGFR ex20ins mutations between Chinese and Western LUAD patients were also compared by integrating the data of this study and the data of previous studies. Results: A total of 23 unique EGFR ex20ins were identified in 77 LUAD patients, accounting for 1.98% of all LUAD patients and 3.49% of EGFR mutant LUDA patients. The 2 most common EGFR ex20ins subtypes were S768_D770dup and A767_V769dup, which together accounted for 55.84% of the EGFR ex20ins cases. About 61% (14/23) of the EGFR ex20ins subtypes occurred only once. Additionally, 8 of the EGFR ex20ins subtypes were not recorded in the COSMIC database. These results showed that the EGFR ex20ins mutations were highly heterogeneous. There was no significant difference in the frequency and distribution of EGFR ex20ins mutations between Chinese and Western LUAD patients, but the frequency of EGFR ex20ins mutations was significantly lower in EGFR-mutant Chinese LUAD patients than Western LUAD patients. The co-mutation analysis showed that EGFR ex20ins occurred significantly and exclusively with certain driver genes in LUAD, including ALK fusion (χ2=7.133, P=0.008), KRAS (χ2=8.468, P=0.004), and PIK3CA (χ2=5.792, P=0.016). No gene was observed to be significantly co-mutated with EGFR ex20ins. In general, patients with EGFR ex20ins shared a similar age and gender to patients with other EGFR mutations or without EGFR ex20ins. Conclusions: Overall, our results revealed the molecular and clinicopathologic features of EGFR ex20ins in Chinese LUAD patients, which will be helpful for drug development and in clinical trials targeting EGFR ex20ins.