DeepCG: A cell graph model for predicting prognosis in lung adenocarcinoma.

Lung cancer is the first leading cause of cancer-related death in the United States, with lung adenocarcinoma as the major subtype accounting for 40% of all cases. To improve patient survival, image-based prognostic models were developed due to the ready availability of pathological images at diagnosis. However, the application of these models is hampered by two main challenges: the lack of publicly available image datasets with high-quality survival information and the poor interpretability of conventional convolutional neural network models. Here, we integrated matched transcriptomic and H&E staining data from TCGA (The Cancer Genome Atlas) to develop an image-based prognostic model, termed Deep-learning based Cell Graph (DeepCG) model. Instead of survival data, we used a gene signature to predict patient prognostic risks, which was then used as labels for training DeepCG. Importantly, by employing graph structures to capture cell patterns, DeepCG can provide cell-level interpretation, which was more biologically relevant than previous region-level insights. We validated the prognostic values of DeepCG in independent datasets and demonstrated its ability to identify prognostically informative cells in images.

PhasiHunter: a robust phased siRNA regulatory cascade mining tool based on multiple reference sequences.

SUMMARY: In recent years, phased small interfering RNA has been found to play crucial roles in many biological processes in plants. However, efficiently predicting phasiRNA regulatory cascades with computational methods is still challenging. Here, we introduce PhasiHunter, a phasiRNA regulatory network prediction tool that has several distinctive features compared to existing tools: (i) PhasiHunter employs two major phasiRNA prediction algorithms, namely phase score and hypergeometric distribution-based methods, to ensure the integrity and accuracy of prediction; (ii) PhasiHunter can identify phasiRNAs and their regulatory networks based on multiple reference sequences and the predicted results can be automatically integrated; (iii) PhasiHunter can efficiently identify the phasiRNAs generated through alternative splicing events; and (iv) the excellent data structure and parallel computing architecture allow PhasiHunter to predict phasiRNAs and their regulatory pathways with high efficiency. AVAILABILITY AND IMPLEMENTATION: PhasiHunter is an open-source tool that is available at https://github.com/HuangLab-CBI/PhasiHunter.

Binding peptide generation for MHC Class I proteins with deep reinforcement learning.

MOTIVATION: MHC Class I protein plays an important role in immunotherapy by presenting immunogenic peptides to anti-tumor immune cells. The repertoires of peptides for various MHC Class I proteins are distinct, which can be reflected by their diverse binding motifs. To characterize binding motifs for MHC Class I proteins, in vitro experiments have been conducted to screen peptides with high binding affinities to hundreds of given MHC Class I proteins. However, considering tens of thousands of known MHC Class I proteins, conducting in vitro experiments for extensive MHC proteins is infeasible, and thus a more efficient and scalable way to characterize binding motifs is needed. RESULTS: We presented a de novo generation framework, coined PepPPO, to characterize binding motif for any given MHC Class I proteins via generating repertoires of peptides presented by them. PepPPO leverages a reinforcement learning agent with a mutation policy to mutate random input peptides into positive presented ones. Using PepPPO, we characterized binding motifs for around 10 000 known human MHC Class I proteins with and without experimental data. These computed motifs demonstrated high similarities with those derived from experimental data. In addition, we found that the motifs could be used for the rapid screening of neoantigens at a much lower time cost than previous deep-learning methods. AVAILABILITY AND IMPLEMENTATION: The software can be found in https://github.com/minrq/pMHC. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Effect of telehealth interventions on adherence to endocrine therapy among patients with breast cancer: a systematic review and meta-analysis.

PURPOSE: To evaluate the effect of telehealth interventions on adherence to endocrine therapy among patients with breast cancer. METHODS: A systematic search of five English databases (PubMed, Web of Science, Embase, the American Psychological Association PsycNet, and the Cochrane Library) and four Chinese databases (Chinese National Knowledge Infrastructure, SinoMed, WanFang Data, and WeiPu Data) was performed from inception to March 31, 2023. Two investigators independently screened the available studies for eligibility and extracted relevant data. Quality assessment was conducted using the Cochrane Risk of Bias Tool. The effect size was computed based on the risk ratio for dichotomous data and standardized mean difference for continuous data using Review Manager 5.4. RESULTS: A total of 1,780 participants from eight randomized controlled trials were included. These studies involved treatment with aromatase inhibitors only (n = 3) or aromatase inhibitors plus tamoxifen (n = 5). Telehealth interventions involved web-based interventions, telephone-based interventions, interventions via mobile applications, and interventions based on technology. In three studies, subjective measures were used, while objective measures were utilized in another three. Two studies incorporated a combination of both subjective and objective measures. The duration of the interventions varied among studies, ranging from a week to 36 months. The follow-up duration ranged from 4 weeks to 36 months. The quality of included studies was moderate to high. The meta-analysis of the five studies reporting dichotomous data showed that telehealth interventions had a significant effect on adherence to endocrine therapy (RR = 0.86, 95% CI = 0.76-0.97). Moreover, four studies reported continuous data. The meta-analysis demonstrated that telehealth interventions significantly improved adherence to endocrine therapy at 1 month (SMD = 0.50, 95% CI = 0.10-0.90), 3 months (SMD = 0.58, 95% CI = 0.17-0.99), and 6 months (SMD = 0.27, 95% CI = 0.08-0.47) of follow-up. CONCLUSION: Telehealth interventions may facilitate adherence to endocrine therapy among patients with breast cancer. Further research should adopt a theory-based design and explore the longer-term effects.

Odorant Receptors Expressing and Antennal Lobes Architecture Are Linked to Caste Dimorphism in Asian Honeybee, Apis cerana (Hymenoptera: Apidae).

Insects heavily rely on the olfactory system for food, mating, and predator evasion. However, the caste-related olfactory differences in Apis cerana, a eusocial insect, remain unclear. To explore the peripheral and primary center of the olfactory system link to the caste dimorphism in A. cerana, transcriptome and immunohistochemistry studies on the odorant receptors (ORs) and architecture of antennal lobes (ALs) were performed on different castes. Through transcriptomesis, we found more olfactory receptor genes in queens and workers than in drones, which were further validated by RT-qPCR, indicating caste dimorphism. Meanwhile, ALs structure, including volume, surface area, and the number of glomeruli, demonstrated a close association with caste dimorphism. Particularly, drones had more macroglomeruli possibly for pheromone recognition. Interestingly, we found that the number of ORs and glomeruli ratio was nearly 1:1. Also, the ORs expression distribution pattern was very similar to the distribution of glomeruli volume. Our results suggest the existence of concurrent plasticity in both the peripheral olfactory system and ALs among different castes of A. cerana, highlighting the role of the olfactory system in labor division in insects.

The phosphoproteomic and interactomic landscape of qGL3/OsPPKL1-mediated brassinosteroid signaling in rice.

Oryza sativa L. (rice) is one of the most important crops in the world, and grain size is a major component determining rice yield. Recent studies have identified a number of grain size regulators, which are involved in phytohormone signaling, G protein signaling, the mitogen-activated protein kinase signaling pathway, the ubiquitin-proteasome pathway or transcriptional regulation. In a previous study, we cloned qGL3/OsPPKL1 encoding a rice protein phosphatase that negatively modulates brassinosteroid (BR) signaling and grain length. Here, to further explore the qGL3-mediated BR signaling network, we performed phosphoproteomic screenings using two pairs of rice materials: the indica rice cultivar 9311 and its near-isogenic line NILqgl3 and the japonica rice cultivar Dongjin and its qGL3 knockout mutant m-qgl3. Together with qGL3-interacting proteins, we constructed the qGL3-mediated network, which reveals the relationships between BR signaling and other critical signaling pathways. Transgenic plants of these network components showed BR-related alterations in plant architecture. From this network, we validated a qGL3-interacting protein, O. sativa VERNALIZATION INSENSITIVE 3-LIKE 1 (OsVIL1), and demonstrated that qGL3 dephosphorylates OsVIL1 to modulate BR signaling. The qGL3-dependent network uncovered in this study increases our understanding of BR signaling and provides a profound foundation for addressing how BR modulates plant architecture in rice.

Tumor cell intrinsic and extrinsic features predict prognosis in estrogen receptor positive breast cancer.

Although estrogen-receptor-positive (ER+) breast cancer is generally associated with favorable prognosis, clinical outcome varies substantially among patients. Genomic assays have been developed and applied to predict patient prognosis for personalized treatment. We hypothesize that the recurrence risk of ER+ breast cancer patients is determined by both genomic mutations intrinsic to tumor cells and extrinsic immunological features in the tumor microenvironment. Based on the Cancer Genome Atlas (TCGA) breast cancer data, we identified the 72 most common genomic aberrations (including gene mutations and indels) in ER+ breast cancer and defined sample-specific scores that systematically characterized the deregulated pathways intrinsic to tumor cells. To further consider tumor cell extrinsic features, we calculated immune infiltration scores for six major immune cell types. Many individual intrinsic features are predictive of patient prognosis in ER+ breast cancer, and some of them achieved comparable accuracy with the Oncotype DX assay. In addition, statistical learning models that integrated these features predicts the recurrence risk of patients with significantly better performance than the Oncotype DX assay (our optimized random forest model AUC = 0.841, Oncotype DX model AUC = 0.792, p = 0.04). As a proof-of-concept, our study indicates the great potential of genomic and immunological features in prognostic prediction for improving breast cancer precision medicine. The framework introduced in this work can be readily applied to other cancers.

Expression and significance of SOX B1 genes in glioblastoma multiforme patients.

The overall survival of glioblastoma multiforme (GBM) patients remains poor. To improve patient outcomes, effective diagnostic and prognostic biomarkers for GBM are needed. In this study, we first applied bioinformatic analyses to identify biomarkers for GBM, focusing on SOX (sex-determining region on the Y chromosome (SRY)-related high mobility group (HMG) box) B1 family members. The ONCOMINE, GEPIA, LinkedOmics and CCLE databases were used to assess mRNA expression levels of the SOX B1 family members in different cancers and normal tissue. Further bioinformatic analysis was performed using the ONCOMINE database in combination with the LinkedOmics data set to identify the prognostic value of SOX B1 family members for GBM. We found mRNA expression levels of all tested SOX B1 genes were significantly increased in GBM. In the LinkedOmics database, increased expression of SOX3 indicated a better overall survival. In GEPIA databases, increased expression of all SOX B1 family members suggested an improved overall survival, but none of them were statistically different. Then, Transwell assays and wound healing were employed to evaluate the motility and invasive captivity of U251 cells when silencing SOX2 and SOX3. We found exogenous inhibition of SOX2 appeared to reduce the migration and invasion of U251 cells in vitro. Collectively, our research suggested that SOX2 might serve as a cancer-promoting gene to identify high-risk GBM patients, and SOX3 had the potential to be a prognostic biomarker for GBM patients.

RiceNCexp: a rice non-coding RNA co-expression atlas based on massive RNA-seq and small-RNA seq data.

Non-coding RNAs (ncRNAs) play important roles in regulating expression of protein-coding genes. Although gene expression databases have emerged in a timely manner, a comprehensive expression database for ncRNAs is still lacking. Herein, we constructed a rice ncRNA co-expression atlas (RiceNCexp), based on 491 RNA-seq and 274 small RNA (sRNA)-seq datasets. RiceNCexp hosts four types of ncRNAs, namely lncRNAs, PHAS genes, miRNAs, and phasiRNAs. RiceNCexp provides comprehensive expression information for rice ncRNAs in 22 tissues/organs, an efficient tau-based mining tool for tissue-specific ncRNAs, and the robust co-expression analysis among ncRNAs or between ncRNAs and protein-coding genes, based on 116 pairs of RNA-seq and sRNA-seq libraries from the same experiments. In summary, RiceNCexp is a user-friendly and comprehensive rice ncRNA co-expression atlas and can be freely accessed at https://cbi.njau.edu.cn/RiceNCexp/.

Resveratrol Ameliorates High Altitude Hypoxia-Induced Osteoporosis by Suppressing the ROS/HIF Signaling Pathway.

Hypoxia at high-altitude leads to osteoporosis. Resveratrol (RES), as an antioxidant, has been reported to promote osteoblastogenesis and suppress osteoclastogenesis. However, the therapeutic effect of RES against osteoporosis induced by high-altitude hypoxia remains unclear. Thus, this study was intended to investigate the potential effects of RES on high-altitude hypoxia-induced osteoporosis both in vivo and in vitro. Male Wistar rats were given RES (400 mg/kg) once daily for nine weeks under hypoxia, while the control was allowed to grow under normoxia. Bone mineral density (BMD), the levels of bone metabolism-related markers, and the changes on a histological level were measured. Bone marrow-derived mesenchymal stem cells (BMSCs) and RAW264.7 were incubated with RES under hypoxia, with a control growing under normoxia, followed by the evaluation of proliferation and differentiation. The results showed that RES inhibited high-altitude hypoxia-induced reduction in BMD, enhanced alkaline phosphatase (ALP), osteocalcin (OCN), calcitonin (CT) and runt-related transcription factor 2 (RUNX2) levels, whereas it reduced cross-linked carboxy-terminal telopeptide of type I collagen (CTX-I) levels and tartrate-resistant acid phosphatase (TRAP) activity in vivo. In addition, RES attenuated histological deteriorations in the femurs. In vitro, RES promoted osteoblastogenesis and mineralization in hypoxia-exposed BMSCs, along with promotion in RUNX2, ALP, OCN and osteopontin (OPN) levels, and inhibited the proliferation and osteoclastogenesis of RAW264.7. The promotion effects of RES on osteoblastogenesis were accompanied by the down-regulation of reactive oxygen species (ROS) and hypoxia inducible factor-1α (HIF-1α) induced by hypoxia. These results demonstrate that RES can alleviate high-altitude hypoxia-induced osteoporosis via promoting osteoblastogenesis by suppressing the ROS/HIF-1α signaling pathway. Thus, we suggest that RES might be a potential treatment with minimal side effects to protect against high-altitude hypoxia-induced osteoporosis.

Impact of Oncotype DX testing on ER+ breast cancer treatment and survival in the first decade of use.

BACKGROUND: The Oncotype DX breast recurrence score has been introduced more than a decade ago to aid physicians in determining the need for systemic adjuvant chemotherapy in patients with early-stage, estrogen receptor (ER)+, lymph node-negative breast cancer. METHODS: In this study, we utilized data from The Surveillance, Epidemiology, and End Results (SEER) Program to investigate temporal trends in Oncotype DX usage among US breast cancer patients in the first decade after the introduction of the Oncotype DX assay. RESULTS: We found that the use of Oncotype DX has steadily increased in the first decade of use and that this increase is associated with a decreased usage of chemotherapy. Patients who utilized the Oncotype DX test tended to have improved survival compared to patients who did not use the assay even after adjusting for clinical variables associated with prognosis. In addition, chemotherapy usage in patients with high-risk scores is associated with significantly longer overall and breast cancer-specific survival compared to high-risk patients who did not receive chemotherapy. On the contrary, patients with low-risk scores who were treated with chemotherapy tended to have shorter overall survival compared to low-risk patients who forwent chemotherapy. CONCLUSION: We have provided a comprehensive temporal overview of the use of Oncotype DX in breast cancer patients in the first decade after Oncotype DX was introduced. Our results suggest that the use of Oncotype DX is increasing in ER+ breast cancer and that the Oncotype DX test results provide valuable information for patient treatment and prognosis.

PhasiRNAnalyzer: an integrated analyser for plant phased siRNAs.

Phased siRNAs (phasiRNAs) are a class of small interfering RNAs (siRNAs) which play essential roles in plant development and defence. However, only a few phasiRNAs have been extensively studied due to the difficulties in identifying and characterizing plant phasiRNAs by plant biologists. Herein, we describe a comprehensive and multi-functional web server termed PhasiRNAnalyzer, which is able to identify all crucial components in plant phasiRNA's regulatory pathway (phase-initiator→PHAS gene→phasiRNA cluster→target gene). Currently, PhasiRNAnalyzer exhibits the following advantages: I) It is the most comprehensive platform which hosts 170 plant species with 256 genome data, 438 cDNA data and 271 degradome data. II) It can identify all crucial components in phasiRNA's regulatory pathway, and verify the interactions between phasiRNAs and their target genes based on degradome data. III) It can perform differential expression analysis of phasiRNAs on each PHAS gene locus between different samples conveniently. IV) It provides the user-friendly interfaces and introduces several improvements, primarily by making more accurate and efficient analysis when dealing with deep sequencing data. In summary, PhasiRNAnalyzer is a comprehensive and systemic phasiRNA analysis server with high sensitivity and efficiency. It can be freely accessed at https://cbi.njau.edu.cn/PPSA/.

Carboxymethyl chitosan and dialdehyde cellulose nanocrystal based injectable self-healing emulsion gel.

The study aims to demonstrate a general method for producing emulsion gels with self-healing properties. Specifically, the self-healing emulsion gels were fabricated by crosslinking carboxymethyl chitosan (CMC) stabilized emulsion with dialdehyde cellulose nanocrystal (DACNC). The reversible imine bonds between primary amino groups from CMC and aldehyde groups from DACNC endow the emulsion gel with self-healing properties. The compressive strength of the emulsion gels was greatly increased from 37.43 kPa 83.7 kPa by encapsulating emulsion droplets (φ = 0 %-40 %.) in the gel matrix. Moreover, the emulsion gels exhibited much better self-healing and injectability ability compared to hydrogel because the emulsion droplets interacted with the 3D gel matrix, which were observed by cryo-SEM and CLSM. The emulsion droplets distributed in the gel matrix improved the mobility and interfacial contact area of CMC and DACNC. Water contact measurement confirmed that the CMC/DACNC self-healing emulsion gels showed a hydrophilic surface. The CMC/DACNC emulsion gels could maintain a good structural stability as the oil loss was <1 % after centrifugation. This research provides a method to keep the structural stability of emulsion gels by inducing self-healing ability and modified cellulose nanocrystals, which could extend the shelf life and application area of emulsion gels.

Sex-Based Differences in Melanoma Survival Improvement from 2004 to 2018.

Background: Melanoma is the deadliest form of skin cancer and its incidence and mortality vary by sex, age, race, and socioeconomic status. Relatively few studies, however, have characterized disparities in survival improvement across these demographic groups in melanoma. METHODS: Survival data from the Surveillance, Epidemiology, and End Results (SEER) database were obtained from 2004 to 2018. The compiled data were analyzed for cancer-specific survival (CSS) to produce multivariable Cox regressions that estimate sex-based survival disparities across patient demographic groups. Additionally, time-to-progression and survival analyses were conducted for a cohort of patients with carcinoma-in situ (CIS) that developed into melanoma. RESULTS: In both female and male patients, melanoma diagnosis in more recent years (2014-2018 versus 2004-2008) was associated with an improved CSS, with females demonstrating an HR of 0.55 (95% CI: 0.49-0.60) and males demonstrating an HR of 0.49 (0.46-0.53). The trend remained consistent upon analyzing the effects of both sex and race on survival improvement for White and Hispanic males and females, but the results were not significant for Black and Asian patients. Joint sex and age analysis demonstrated significant reductions in HR across all age groups for female and male patients with a diagnosis in more recent years. Analysis of lesions progressing from CIS to melanoma (high-risk CIS) demonstrated an increased OR for males over females (OR: 1.70; 95% CI: 1.55-1.85), while survival analysis demonstrated no difference between sexes in the HR. Finally, for male patients, high-risk CIS demonstrated worse CSS compared to female patients with high-risk CIS (OR: 1.43; 95% CI: 1.15-1.79). CONCLUSION: Overall, melanoma survival has improved in recent years, though some patient subgroups have experienced a lower improvement in survival from 2004 to 2018.

Small molecule tyrosine kinase inhibitors approved for systemic therapy of advanced hepatocellular carcinoma: recent advances and future perspectives.

Liver cancer is the sixth most commonly diagnosed cancer and the third leading cause of cancer death in the world, and hepatocellular carcinoma (HCC) is the most common form of liver cancer. More than half of the HCC patients are diagnosed at an advanced stage and often require systemic therapy. Dysregulation of the activity of receptor tyrosine kinases (RTKs) is involved in the development and progress of HCC, RTKs are therefore the potential targets for systemic therapy of advanced HCC (aHCC). Currently, a total of six small molecule tyrosine kinase inhibitors (TKIs) have been approved for aHCC, including first-line sorafenib, lenvatinib, and donafenib, and second-line regorafenib, cabozantinib, and apatinib. These TKIs improved patients survival, which are associated with disease stage, etiology, liver function, tumor burden, baseline levels of alpha-fetoprotein, and treatment history. This review focuses on the clinical outcomes of these TKIs in key clinical trials, retrospective and real-world studies and discusses the future perspectives of TKIs for aHCC, with an aim to provide up-to-date evidence for decision-making in the treatment of aHCC.

The protein phosphatase qGL3/OsPPKL1 self-regulates its degradation to orchestrate brassinosteroid signaling in rice.

Brassinosteroids (BRs) are a class of phytohormones that regulate plant growth and development. In previous studies, we cloned and identified PROTEIN PHOSPHATASE WITH KELCH-LIKE1 (OsPPKL1) as the causal gene for the quantitative trait locus GRAIN LENGTH3 (qGL3) in rice (Oryza sativa). We also showed that qGL3/OsPPKL1 is mainly located in the cytoplasm and nucleus and negatively regulates BR signaling and grain length. Because qGL3 is a negative regulator of BR signaling, its turnover is critical for rapid response to changes in BRs. Here, we demonstrate that qGL3 interacts with the WD40-domain-containing protein WD40-REPEAT PROTEIN48 (OsWDR48), which contains a nuclear export signal (NES). The NES signal is crucial for the cytosolic localization of OsWDR48 and also functions in the self-turnover of qGL3. We show that OsWDR48 physically interacts with and genetically acts through qGL3 to modulate BR signaling. Moreover, qGL3 may indirectly promote the phosphorylation of OsWDR48 at the Ser-379 and Ser-386 sites. Substitutions of both phosphorylation sites in OsWDR48 to non-phosphorylatable alanine enhanced the strength of the OsWDR48-qGL3 interaction. Furthermore, we found that brassinolide can promote the accumulation of non-phosphorylated OsWDR48, leading to strong interaction intensity between qGL3 and OsWDR48. Taken together, our results show that OsWDR48 facilitates qGL3 retention and induces degradation of qGL3 in the cytoplasm. These findings suggest that qGL3 self-modulates its turnover by binding to OsWDR48 to regulate its cytoplasmic localization and stability, leading to efficient orchestration of BR signal transduction in rice.

The trajectories of psychosocial adjustment among young to middle-aged women with breast cancer: A prospective longitudinal study.

PURPOSE: This study aims to explore heterogeneous trajectories of psychosocial adjustment among young to middle-aged women with breast cancer and determine the predictive factors influencing these trajectories. METHODS: This study was conducted from October 2019 to October 2022 across two hospitals in Guangzhou. Demographic and disease characteristics, psychosocial adjustment, self-efficacy, social support, and coping modes were collected at baseline. Follow-up evaluations of psychosocial adjustment occurred at 1, 3, and 6 months post-surgery. Latent class growth modeling identified distinct patterns of psychosocial adjustment trajectories. Logistic regression analysis determined the predictive factors. RESULTS: A total of 377 young to middle-aged women with breast cancer participated in this study, with 289 participants completing the 6-month follow-up. Three distinct trajectories of psychosocial adjustment were identified including a "sustained severe maladjustment" trajectory, comprising 22.5% of participants, a "sustained moderate maladjustment" trajectory, comprising 50.4% of participants, and a "well-adjusted class" trajectory, comprising 27.1% of participants. Predictors of psychosocial adjustment trajectories included affected side, surgical type, chemotherapy, self-efficacy, social support, and coping modes. CONCLUSIONS: This study revealed three distinct trajectories of psychosocial adjustment among young to middle-aged women with breast cancer. Those with right-sided breast cancer, undergoing total mastectomy, receiving chemotherapy, low self-efficacy, limited social support, and relying on confrontation or avoidance coping modes may experience sustained maladjustment.

Corrigendum: Sestrin2 protects against hypoxic nerve injury by regulating mitophagy through SESN2/AMPK pathway.

[This corrects the article DOI: 10.3389/fmolb.2023.1266243.].