Short-term efficacy and safety of neoadjuvant pyrotinib plus taxanes for early HER2-positive breast cancer: a single-arm exploratory phase II trial.

Background: The effectiveness and safety of pyrotinib have been substantiated in human epidermal growth factor receptor 2 (HER2)-positive advanced breast cancer (BC). However, the role of pyrotinib as a single HER2 blockade in neoadjuvant setting among BC patients has not been studied. The objective of this study was to evaluate the efficacy and tolerability of pyrotinib plus taxanes as a novel neoadjuvant regimen in patients with HER2-positive early or locally advanced BC. Methods: In this single-arm exploratory phase II trial, patients with treatment-naïve HER2-positive BC (stage IIA-IIIC) received pyrotinib 400 mg once daily and taxanes [docetaxel 75 mg/m2 or nanoparticle albumin-bound (nab)-paclitaxel 260 mg/m2 every 3 weeks, or paclitaxel 80 mg/m2 weekly] for a total of four 21-day cycles before surgery. Efficacy assessment was based on pathological and clinical measurements. The primary endpoint of this study was the total pathological complete response (tpCR) rate. The secondary endpoints included breast pCR (bpCR) rate, investigator-assessed objective response rate (ORR) and adverse events (AEs) profiles. Results: From 1 September 2021 to 30 December 2022, a total of 31 patients were enrolled. One patient was withdrawn due to unbearable skin rash after the second cycle of neoadjuvant therapy. The majority of the intention-to-treat (ITT) population was premenopausal (54.8%), had large tumors (90.3%) and metastatic nodes (58.1%) at diagnosis and hormone-receptor positive tumors (64.5%). Most participants used nab-paclitaxel (74.2%) and received mastectomy (67.7%) after neoadjuvant treatment. The tpCR and bpCR rates were 48.4% [95% confidence interval (CI): 30.8-66%] and 51.6% (95% CI: 34-69.2%), respectively. Grade ≥3 treatment-related AEs were observed in 16.1% (5/31) of the ITT population, including diarrhea (n=2, 6.5%), hand and foot numbness (n=1, 3.2%), loss of appetite (n=1, 3.2%), and skin rash (n=1, 3.2%). AE related dose reduction or pyrotinib interruption was not required. Conclusions: In female patients with HER2-positive non-metastatic BC, neoadjuvant pyrotinib monotherapy plus taxanes appears to show promising clinical benefit and controllable AEs [Chinese Clinical Trial Registry (ChiCTR2100050870)]. The long-term efficacy and safety of this regime warrant further verification.

Patient-derived organoids: a promising tool for breast cancer research.

Breast cancer (BC) is the most prevalent malignancy among women worldwide. Traditional research models such as primary cancer cell and patient-derived tumor xenografts (PDTXs) have limitations. Cancer cells lack a tumor microenvironment (TME) and genetic diversity, whereas PDTXs are expensive and have a time-consuming preparation protocol. Therefore, alternative research models are warranted. Patient-derived organoids (PDOs) are a promising in vitro model. They mimic the TME, gene expression, and cell types of original cancer tissues. PDOs have been successfully developed from various cancers, including BC. In this review, we focused on the value and limitations of PDOs in BC research, including their characteristics and potential in drug development, personalized therapy, immunotherapy, and the application prospects of PDOs in drug testing and prognosis.

A radiogenomic multimodal and whole-transcriptome sequencing for preoperative prediction of axillary lymph node metastasis and drug therapeutic response in breast cancer: a retrospective, machine learning and international multicohort study.

BACKGROUND: Axillary lymph nodes (ALN) status serves as a crucial prognostic indicator in breast cancer (BC). The aim of this study was to construct a radiogenomic multimodal model, based on machine learning and whole-transcriptome sequencing (WTS), to accurately evaluate the risk of ALN metastasis (ALNM), drug therapeutic response and avoid unnecessary axillary surgery in BC patients. METHODS: In this study, conducted a retrospective analysis of 1078 BC patients from The Cancer Genome Atlas (TCGA), The Cancer Imaging Archive (TCIA), and Foshan cohort. These patients were divided into the TCIA cohort ( N =103), TCIA validation cohort ( N =51), Duke cohort ( N =138), Foshan cohort ( N =106), and TCGA cohort ( N =680). Radiological features were extracted from BC radiological images and differentially expressed gene expression was calibrated using technology. A support vector machine model was employed to screen radiological and genetic features, and a multimodal model was established based on radiogenomic and clinical pathological features to predict ALNM. The accuracy of the model predictions was assessed using the area under the curve (AUC) and the clinical benefit was measured using decision curve analysis. Risk stratification analysis of BC patients was performed by gene set enrichment analysis, differential comparison of immune checkpoint gene expression, and drug sensitivity testing. RESULTS: For the prediction of ALNM, rad-score was able to significantly differentiate between ALN- and ALN+ patients in both the Duke and Foshan cohorts ( P <0.05). Similarly, the gene-score was able to significantly differentiate between ALN- and ALN+ patients in the TCGA cohort ( P <0.05). The radiogenomic multimodal nomogram demonstrated satisfactory performance in the TCIA cohort (AUC 0.82, 95% CI: 0.74-0.91) and the TCIA validation cohort (AUC 0.77, 95% CI: 0.63-0.91). In the risk sub-stratification analysis, there were significant differences in gene pathway enrichment between high and low-risk groups ( P <0.05). Additionally, different risk groups may exhibit varying treatment responses ( P <0.05). CONCLUSION: Overall, the radiogenomic multimodal model employs multimodal data, including radiological images, genetic, and clinicopathological typing. The radiogenomic multimodal nomogram can precisely predict ALNM and drug therapeutic response in BC patients.

HSP90ß Impedes STUB1-Induced Ubiquitination of YTHDF2 to Drive Sorafenib Resistance in Hepatocellular Carcinoma.

YTH domain family 2 (YTHDF2) is the first identified N6-methyladenosine (m6 A) reader that regulates the status of mRNA. It has been reported that overexpressed YTHDF2 promotes carcinogenesis; yet, its role in hepatocellular carcinoma (HCC) is elusive. Herein, it is demonstrated that YTHDF2 is upregulated and can predict poor outcomes in HCC. Decreased ubiquitination levels of YTHDF2 contribute to the upregulation of YTHDF2. Furthermore, heat shock protein 90 beta (HSP90ß) and STIP1 homology and U-box-containing protein 1 (STUB1) physically interact with YTHDF2 in the cytoplasm. Mechanically, the large and small middle domain of HSP90ß is required for its interaction with STUB1 and YTHDF2. HSP90ß inhibits the STUB1-induced degradation of YTHDF2 to elevate the expression of YTHDF2 and to further boost the proliferation and sorafenib resistance of HCC. Moreover, HSP90ß and YTHDF2 are upregulated, while STUB1 is downregulated in HCC tissues. The expression of HSP90ß is positively correlated with the YTHDF2 protein level, whereas the expression of STUB1 is negatively correlated with the protein levels of YTHDF2 and HSP90ß. These findings deepen the understanding of how YTHDF2 is regulated to drive HCC progression and provide potential targets for treating HCC.

Nuclear transport maintenance of USP22-AR by Importin-7 promotes breast cancer progression.

The translocation of biological macromolecules between cytoplasm and nucleus is of great significance to maintain various life processes in both normal and cancer cells. Disturbance of transport function likely leads to an unbalanced state between tumor suppressors and tumor-promoting factors. In this study, based on the unbiased analysis of protein expression differences with a mass spectrometer between human breast malignant tumors and benign hyperplastic tissues, we identified that Importin-7, a nuclear transport factor, is highly expressed in breast cancer (BC) and predicts poor outcomes. Further studies showed that Importin-7 promotes cell cycle progression and proliferation. Mechanistically, through co-immunoprecipitation, immunofluorescence, and nuclear-cytoplasmic protein separation experiments, we discovered that AR and USP22 can bind to Importin-7 as cargoes to promote BC progression. In addition, this study provides a rationale for a therapeutic strategy to restream the malignant progression of AR-positive BC by inhibiting the high expression state of Importin-7. Moreover, the knockdown of Importin-7 increased the responsiveness of BC cells to the AR signaling inhibitor, enzalutamide, suggesting that targeting Importin-7 may be a potential therapeutic strategy.

SNS-023 sensitizes hepatocellular carcinoma to sorafenib by inducing degradation of cancer drivers SIX1 and RPS16.

Hepatocellular carcinoma (HCC) remains challenging due to the lack of efficient therapy. Promoting degradation of certain cancer drivers has become an innovative therapy. The nuclear transcription factor sine oculis homeobox 1 (SIX1) is a key driver for the progression of HCC. Here, we explored the molecular mechanisms of ubiquitination of SIX1 and whether targeting SIX1 degradation might represent a potential strategy for HCC therapy. Through detecting the ubiquitination level of SIX1 in clinical HCC tissues and analyzing TCGA and GEPIA databases, we found that ubiquitin specific peptidase 1 (USP1), a deubiquitinating enzyme, contributed to the lower ubiquitination and high protein level of SIX1 in HCC tissues. In HepG2 and Hep3B cells, activation of EGFR-AKT signaling pathway promoted the expression of USP1 and the stability of its substrates, including SIX1 and ribosomal protein S16 (RPS16). In contrast, suppression of EGFR with gefitinib or knockdown of USP1 restrained EGF-elevated levels of SIX1 and RPS16. We further revealed that SNS-023 (formerly known as BMS-387032) induced degradation of SIX1 and RPS16, whereas this process was reversed by reactivation of EGFR-AKT pathway or overexpression of USP1. Consequently, inactivation of the EGFR-AKT-USP1 axis with SNS-032 led to cell cycle arrest, apoptosis, and suppression of cell proliferation and migration in HCC. Moreover, we showed that sorafenib combined with SNS-032 or gefitinib synergistically inhibited the growth of Hep3B xenografts in vivo. Overall, we identify that both SIX1 and RPS16 are crucial substrates for the EGFR-AKT-USP1 axis-driven growth of HCC, suggesting a potential anti-HCC strategy from a novel perspective.

Noninvasive prediction of axillary lymph node status in breast cancer using promoter profiling of circulating cell-free DNA.

BACKGROUND: Lymph node metastasis (LNM) is one of the most important factors affecting the prognosis of breast cancer. The accurate evaluation of lymph node status is useful to predict the outcomes of patients and guide the choice of cancer treatment. However, there is still lack of a low-cost non-invasive method to assess the status of axillary lymph node (ALN). Gene expression signature has been used to assess lymph node metastasis status of breast cancer. In addition, nucleosome footprint of cell-free DNA (cfDNA) carries gene expression information of its original tissues, so it may be used to evaluate the axillary lymph node status in breast cancer. METHODS: In this study, we found that the cfDNA nucleosome footprints between the ALN-positive patients and ALN-negative patients showed different patterns by implementing whole-genome sequencing (WGS) to detect 15 ALN-positive and 15 ALN-negative patients. In order to further evaluate its potential for assessing ALN status, we developed a classifier with multiple machine learning models by using 330 WGS data of cfDNA from 162 ALN-positive and 168 ALN-negative samples to distinguish these two types of patients. RESULTS: We found that the promoter profiling between the ALN-positive patients and ALN-negative patients showed distinct patterns. In addition, we observed 1071 genes with differential promoter coverage and their functions were closely related to tumorigenesis. We found that the predictive classifier based on promoter profiling with a support vector machine model, named PPCNM, produced the largest area under the curve of 0.897 (95% confidence interval 0.86-0.93). CONCLUSIONS: These results indicate that promoter profiling can be used to distinguish ALN-positive patients from ALN-negative patients, which may be helpful to guide the choice of cancer treatment.

A comparison of Chinese multicenter breast cancer database and SEER database.

There are different characteristics of BC in developing countries and developed countries. We intended to study the factors which influence the survival and prognosis of BC between southern China and the United States. (a) To study the two groups BC patients in southern China from 2001 to 2016 and SEER database from 1975 to 2016. (b) To register, collect and analyze the clinicopathological features and treatment information. Our study found that there are significant differences in tumor size, positive lymph node status and KI-67 between southern China and SEER cohort (P < 0.000). The positive lymph node status may be one of the causes of difference of morbidity and mortality of BC patients in China. Furthermore, the differences in treatment methods may also account for the differences between China and seer databases.

ARV-771 Acts as an Inducer of Cell Cycle Arrest and Apoptosis to Suppress Hepatocellular Carcinoma Progression.

Hepatocellular carcinoma (HCC) is the most commonly diagnosed liver cancer with limited treatment options and extremely poor prognosis worldwide. Recently, the proteolysis targeting chimeras (PROTACs), which aim to induce proteasome-mediated degradation of interesting proteins via recruiting E3 ligases, have become the advanced tools and attractive molecules for cancer treatment. However, the anticancer effects of PROTACs in HCC remain to be clarified. Here, we evaluate the anticancer activity of ARV-771, a previously reported PROTAC compound designed for bromodomain and extra-terminal domain (BET) proteins, in HCC. We show that ARV-771 suppresses the cell viability and colony formation of HCC cells via arresting cell cycle progression and triggering apoptosis. Further investigations reveal that ARV-771 notably downregulates multiple non-proteasomal deubiquitinases which are critical to the development of cancers. Additionally, HCC cells can decrease their sensitivity to ARV-771 via activating the MEK/ERK and p38 MAPKs. ARV-771 also inhibits HCC progression in vivo. Moreover, we show that ARV-771 and sorafenib, a Raf inhibitor that clinically used for targeted therapy of liver cancer, can synergistically inhibit the growth of HCC cells. Overall, this study not only explores the anticancer activity of ARV-771 and its underlying mechanisms in HCC, but also deepens our understanding of deubiquitinases, MAPKs, cell cycle, and apoptosis induction in cancer therapy.

Circulating T-Cell Repertoires Correlate With the Tumor Response in Patients With Breast Cancer Receiving Neoadjuvant Chemotherapy.

PURPOSE: Neoadjuvant chemotherapy (NAC) has been widely used in patients with breast cancer to minish tumor burden and increase resection rate of cancer. T-cell repertoire has been believed to be able to monitor antitumor immune responses. This study aimed to explore the dynamic change of T-cell repertoire and its clinical value in evaluating the tumor response in patients with breast cancer receiving NAC. MATERIALS AND METHODS: Ninety-four patients who underwent NAC before surgery were recruited, and peripheral blood samples were collected at multiple time points during NAC. High-throughput T-cell receptor (TCR)-ß sequencing was used to characterize the T-cell repertoire of every sample and analyzed the changes in circulating T-cell repertoire during NAC. RESULTS: We found that the diversity of TCR repertoires was associated with age and clinical stage of the patients with breast cancer. The distribution of Vß and Jß genes in TCR repertoires was skewed in patients with human epidermal growth factor receptor 2-positive (HER2+) breast cancer. Vß20.1 and Vß30 expression levels before NAC correlate with tumor response after all cycles of NAC in HER2- and HER2+ patients, respectively. Some CDR3 motifs that correlated with clinical response in either HER2+ or HER2- patients were identified. Besides, TCR repertoire evolved during NAC and the diversity of TCR repertoire decreased more after two cycles of NAC in patients with good tumor response after all cycles of NAC (P = .0061). CONCLUSION: Our results demonstrated that TCR repertoire correlated with the characteristics of the tumor, such as the expression status of HER2. Moreover, some characteristics of TCR repertoires that correlated with clinical response were identified and they might provide useful information to tailor therapeutic regimens at the early cycle of NAC.

Plasma-Derived Extracellular Vesicles Circular RNAs Serve as Biomarkers for Breast Cancer Diagnosis.

Breast cancer is the second cause of cancer-associated death among women and seriously endangers women's health. Therefore, early identification of breast cancer would be beneficial to women's health. At present, circular RNA (circRNA) not only exists in the extracellular vesicles (EVs) in plasma, but also presents distinct patterns under different physiological and pathological conditions. Therefore, we assume that circRNA could be used for early diagnosis of breast cancer. Here, we developed classifiers for breast cancer diagnosis that relied on 259 samples, including 144 breast cancer patients and 115 controls. In the discovery stage, we compared the genome-wide long RNA profiles of EVs in patients with breast cancer (n=14) and benign breast (n=6). To further verify its potential in early diagnosis of breast cancer, we prospectively collected plasma samples from 259 individuals before treatment, including 144 breast cancer patients and 115 controls. Finally, we developed and verified the predictive classifies based on their circRNA expression profiles of plasma EVs by using multiple machine learning models. By comparing their circRNA profiles, we found 439 circRNAs with significantly different levels between cancer patients and controls. Considering the cost and practicability of the test, we selected 20 candidate circRNAs with elevated levels and detected their levels by quantitative real-time polymerase chain reaction. In the training cohort, we found that BCExoC, a nine-circRNA combined classifier with SVM model, achieved the largest AUC of 0.83 [95% CI 0.77-0.88]. In the validation cohort, the predictive efficacy of the classifier achieved 0.80 [0.71-0.89]. Our work reveals the application prospect of circRNAs in plasma EVs as non-invasive liquid biopsies in the diagnosis and management of breast cancer.

A Deep-Learning Pipeline for TSS Coverage Imputation From Shallow Cell-Free DNA Sequencing.

Cell-free DNA (cfDNA) serves as a footprint of the nucleosome occupancy status of transcription start sites (TSSs), and has been subject to wide development for use in noninvasive health monitoring and disease detection. However, the requirement for high sequencing depth limits its clinical use. Here, we introduce a deep-learning pipeline designed for TSS coverage profiles generated from shallow cfDNA sequencing called the Autoencoder of cfDNA TSS (AECT) coverage profile. AECT outperformed existing single-cell sequencing imputation algorithms in terms of improvements to TSS coverage accuracy and the capture of latent biological features that distinguish sex or tumor status. We built classifiers for the detection of breast and rectal cancer using AECT-imputed shallow sequencing data, and their performance was close to that achieved by high-depth sequencing, suggesting that AECT could provide a broadly applicable noninvasive screening approach with high accuracy and at a moderate cost.

A plasma-derived extracellular vesicle mRNA classifier for the detection of breast cancer.

BACKGROUND: According to the global cancer burden data released in 2020, breast cancer (BC) has become the most common cancer in the world. Similar to those of other cancers, the present methods used in clinic for diagnosing early BC are invasive, inaccurate, and insensitive. Hence, new non-invasive methods capable of early diagnosis are needed. METHODS: We applied next-generation sequencing and analyzed the messenger RNA (mRNA) profiles of plasma extracellular vesicles (EVs) derived from 14 BC patients and 6 patients with benign breast lesions. We used 3 regression models, namely support vector machine (SVM), linear discriminate analysis (LDA), and logistic regression (LR), to develop classifiers for use in making predictive BC diagnoses; and used 259 plasma samples, including those obtained from 144 patients with BC, 72 patients with benign breast lesions, and 43 healthy women, which were divided into training groups and validation groups to verify their performances as classifiers by quantitative reverse transcription polymerase chain reaction (RT-qPCR). The area under the curve (AUC) and accuracy, sensitivity, and specificity of the classifiers were cross-validated with the leave-1-out cross-validation (LOOCV) method. RESULTS: Among all combinations assessed with the 3 different regression models, an 8-mRNA combination, named EXOBmRNA, exhibited high performance [accuracy =71.9% and AUC =0.718, 95% confidence interval (CI): 0.652 to 0.784] in the training cohort after LOOCV was performed, showing the largest AUC in the SVM model. The mRNAs in EXOBmRNA were HLA-DRB1, HAVCR1, ENPEP, TIMP1, CD36, MARCKS, DAB2, and CXCL14. In the validation cohort, the AUC of EXOBmRNA was 0.737 (95% CI: 0.636 to 0.837). In addition, gene function and pathway analyses revealed that different levels of gene expression were associated with cancer. CONCLUSIONS: We developed a high-performing predictive classifiers including 8 mRNAs from plasma extracellular vesicles for diagnosing breast cancer.

Noninvasive discrimination of benign and malignant breast lesions using genome-wide nucleosome profiles of plasma cell-free DNA.

BACKGROUND: Breast malignancy is the most frequently diagnosed malignancy in women worldwide, and the diagnosis relies on invasive examinations. However, most clinical breast changes in women are benign, and invasive diagnostic approaches cause unnecessary suffering for the patients. Thus, a novel noninvasive approach for discriminating malignant breast lesions from benign lesions is needed. METHODS: We performed cell-free DNA (cfDNA) sequencing on plasma samples from 173 malignant breast lesion patients, 158 benign breast lesion patients, and 102 healthy women. We then analyzed the cfDNA-based nucleosome profiles, which reflect the various tissues of origin and transcription factor activities. Moreover, by using machine learning classifiers along with the cfDNA sequencing data, we built classifiers for discriminating benign from malignant breast lesions. Receiver operating characteristic curve analyses were used to evaluate the performance of the classifiers. RESULTS: cfDNA-based nucleosome profiles reflected the various tissues of origin and transcription factor activities in benign and malignant breast lesions. The cfDNA-based transcription factor activities and breast malignancy-specific transcription factor-binding site accessibility profiles could accurately distinguish benign and malignant breast lesions, with area under the curve values of 0.777 and 0.824, respectively. CONCLUSIONS: Our proof-of-principle study established a methodology for noninvasively discriminating benign from malignant breast lesions.

Association between the nucleosome footprint of plasma DNA and neoadjuvant chemotherapy response for breast cancer.

Gene expression signatures have been used to predict the outcome of chemotherapy for breast cancer. The nucleosome footprint of cell-free DNA (cfDNA) carries gene expression information of the original tissues and thus may be used to predict the response to chemotherapy. Here we carried out the nucleosome positioning on cfDNA from 85 breast cancer patients and 85 healthy individuals and two cancer cell lines T-47D and MDA-MB-231 using low-coverage whole-genome sequencing (LCWGS) method. The patients showed distinct nucleosome footprints at Transcription Start Sites (TSSs) compared with normal donors. In order to identify the footprints of cfDNA corresponding with the responses to neoadjuvant chemotherapy in patients, we mapped on nucleosome positions on cfDNA of patients with different responses: responders (pretreatment, n = 28; post-1 cycle, post-3/4 cycles, and post-8 cycles of treatment, n = 12) and nonresponders (pretreatment, n = 10; post-1 cycle, post-3/4 cycles, and post-8 cycles of treatment, n = 10). The coverage depth near TSSs in plasma cfDNA differed significantly between responders and nonresponders at pretreatment, and also after neoadjuvant chemotherapy treatment cycles. We identified 232 TSSs with differential footprints at pretreatment and 321 after treatment and found enrichment in Gene Ontology terms such as cell growth inhibition, tumor suppressor, necrotic cell death, acute inflammatory response, T cell receptor signaling pathway, and positive regulation of vascular endothelial growth factor production. These results suggest that cfDNA nucleosome footprints may be used to predict the efficacy of neoadjuvant chemotherapy for breast cancer patients and thus may provide help in decision making for individual patients.

SELER: a database of super-enhancer-associated lncRNA- directed transcriptional regulation in human cancers.

Super-enhancers (SEs) are enriched with a cluster of mediator binding sites, which are major contributors to cell-type-specific gene expression. Currently, a large quantity of long non-coding RNAs has been found to be transcribed from or to interact with SEs, which constitute super-enhancer associated long non-coding RNAs (SE-lncRNAs). These SE-lncRNAs play essential roles in transcriptional regulation through controlling SEs activity to regulate a broad range of physiological and pathological processes, especially tumorigenesis. However, the pathological functions of SE-lncRNAs in tumorigenesis are still obscure. In this paper, we characterized 5056 SE-lncRNAs and their associated genes by analysing 102 SE data sets. Then, we analysed their expression profiles and prognostic information derived from 19 cancer types to identify cancer-related SE-lncRNAs and to explore their potential functions. In total, 436 significantly differentially expressed SE-lncRNAs and 2035 SE-lncRNAs with high prognostic values were identified. Additionally, 3935 significant correlations between SE-lncRNAs and their regulatory genes were further validated by calculating their correlation coefficients in each cancer type. Finally, the SELER database incorporating the aforementioned data was provided for users to explore their physiological and pathological functions to comprehensively understand the blocks of living systems.

Chronic hepatitis B infection and risk of preterm labor: a meta-analysis of observational studies.

Many epidemiological studies have found a positive association between chronic hepatitis B virus (CHB) infection and the risk of preterm labor, but the magnitude of this association varies and independent studies have reported conflicting findings. We performed a meta-analysis to ascertain the relationship between CHB infection and preterm labor. The PubMed and Embase databases were searched up to May 1st, 2014, for relevant observational studies on an association between CHB infection and the risk of preterm labor. Data were extracted and analyzed independently by two authors. The meta-analysis was performed using Stata version 10.0 software. Six observational case-control studies and 4 cohort studies, involving 6781 women with preterm labor, were identified. Based on a random-effects meta-analysis, no association between CHB infection and preterm labor was identified (odds ratio=1.12, 95% confidence interval CI, 0.94-1.33). Our meta-analysis suggested that CHB infection is not associated with an increased risk of preterm labor.