The Expression of TMEM74 in Liver Cancer and Lung Cancer Correlating With Survival Outcomes

Characterization of the Clinical Significance and Immunological Landscapes of a Novel TMEMs Signature in Hepatocellular Carcinoma and the Contribution of TMEM201 to Hepatocarcinogenesis

Aberrant transmembrane protein (TMEM) expression is implicated in tumor progression, but its functional role in hepatocellular carcinoma (HCC) is unclear. Thus, we aim to characterize the functional contributions of TMEM in HCC. In this study, four novel TMEM-family genes (TMEMs), TMEM106C, TMEM201, TMEM164, and TMEM45A, were screened to create a TMEMs signature. These candidate genes are distinguished between patients with varying survival statuses. High-risk HCC patients had a significantly worse prognosis and more advanced clinicopathological characteristics in both the training and validation groups. The GO and KEGG analyses unveiled that the TMEMs signature might play a crucial role in cell-cycle-relevant and immune-related pathways. We found that the high-risk patients had lower stromal scores and a more immunosuppressive tumor microenvironment with massive infiltration of macrophages and Treg cells, whereas the low-risk group had higher stromal scores and gamma delta T-cell infiltration. Moreover, the expression level of suppressive immune checkpoints increased as the TMEM-signature scores increased. Furthermore, the in vitro experiments validated TMEM201, one feature of the TMEMs signature, and facilitated HCC proliferation, survival, and migration. The TMEMs signature provided a more precise prognostic evaluation of HCC and reflected the immunological status of HCC. Of the TMEMs signature studied, TMEM201 was found to significantly promote HCC progression.

Advancement in Human Face Prediction Using DNA

The rapid improvements in identifying the genetic factors contributing to facial morphology have enabled the early identification of craniofacial syndromes. Similarly, this technology can be vital in forensic cases involving human identification from biological traces or human remains, especially when reference samples are not available in the deoxyribose nucleic acid (DNA) database. This review summarizes the currently used methods for predicting human phenotypes such as age, ancestry, pigmentation, and facial features based on genetic variations. To identify the facial features affected by DNA, various two-dimensional (2D)- and three-dimensional (3D)-scanning techniques and analysis tools are reviewed. A comparison between the scanning technologies is also presented in this review. Face-landmarking techniques and face-phenotyping algorithms are discussed in chronological order. Then, the latest approaches in genetic to 3D face shape analysis are emphasized. A systematic review of the current markers that passed the threshold of a genome-wide association (GWAS) of single nucleotide polymorphism (SNP)-face traits from the GWAS Catalog is also provided using the preferred reporting items for systematic reviews and meta-analyses (PRISMA), approach. Finally, the current challenges in forensic DNA phenotyping are analyzed and discussed.

Behavioral innovation and genomic novelty are associated with the exploitation of a challenging dietary opportunity by an avivorous bat

Foraging on nocturnally migrating birds is one of the most challenging foraging tasks in the animal kingdom. Only three bat species (e.g., Ia io) known to date can prey on migratory birds. However, how these bats have exploited this challenging dietary niche remains unknown. Here, we demonstrate that I. io hunts at the altitude of migrating birds during the bird migration season. The foraging I. io exhibited high flight altitudes (up to 4945 m above sea level) and high flight speeds (up to 143.7 km h⁻¹). I. io in flight can actively prey on birds in the night sky via echolocation cues. Genes associated with DNA damage repair, hypoxia adaptation, biting and mastication, and digestion and metabolism have evolved to adapt to this species’ avivorous habits. Our results suggest that the evolution of behavioral innovation and genomic novelty are associated with the exploitation of challenging dietary opportunities.

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Predation on nocturnally migrating birds is rare and challenging in nature

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Bats exhibit high flight altitude and speed associated with foraging on migrating birds

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Bats can actively prey on birds in the night sky via echolocation cues

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The adaptive evolution of genes enables bats to adapt to the avivorous habits

Construction and Validation of a Prognostic Risk Model for Triple-Negative Breast Cancer Based on Autophagy-Related Genes

Background

Autophagy plays an important role in triple-negative breast cancer (TNBC). However, the prognostic value of autophagy-related genes (ARGs) in TNBC remains unknown. In this study, we established a survival model to evaluate the prognosis of TNBC patients using ARGs signature.

Methods

A total of 222 autophagy-related genes were downloaded from The Human Autophagy Database. The RNA-sequencing data and corresponding clinical data of TNBC were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed autophagy-related genes (DE-ARGs) between normal samples and TNBC samples were determined by the DESeq2 package. Then, univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were performed. According to the LASSO regression results based on univariate Cox, we identified a prognostic signature for overall survival (OS), which was further validated by using the Gene Expression Omnibus (GEO) cohort. We also found an independent prognostic marker that can predict the clinicopathological features of TNBC. Furthermore, a nomogram was drawn to predict the survival probability of TNBC patients, which could help in clinical decision for TNBC treatment. Finally, we validated the requirement of an ARG in our model for TNBC cell survival and metastasis.

Results

There are 43 DE-ARGs identified between normal and tumor samples. A risk model for OS using CDKN1A, CTSD, CTSL, EIF4EBP1, TMEM74, and VAMP3 was established based on univariate Cox regression and LASSO regression analysis. Overall survival of TNBC patients was significantly shorter in the high-risk group than in the low-risk group for both the training and validation cohorts. Using the Kaplan–Meier curves and receiver operating characteristic (ROC) curves, we demonstrated the accuracy of the prognostic model. Multivariate Cox regression analysis was used to verify risk score as an independent predictor. Subsequently, a nomogram was proposed to predict 1-, 3-, and 5-year survival for TNBC patients. The calibration curves showed great accuracy of the model for survival prediction. Finally, we found that depletion of EIF4EBP1, one of the ARGs in our model, significantly reduced cell proliferation and metastasis of TNBC cells.

Conclusion

Based on six ARGs (CDKN1A, CTSD, CTSL, EIF4EBP1, TMEM74, and VAMP3), we developed a risk prediction model that can help clinical doctors effectively predict the survival status of TNBC patients. Our data suggested that EIF4EBP1 might promote the proliferation and migration in TNBC cell lines. These findings provided a novel insight into the vital role of the autophagy-related genes in TNBC and may provide new therapeutic targets for TNBC.

Development and Validation of an Autophagy-Related Gene Signature for Predicting the Prognosis of Hepatocellular Carcinoma

Purpose

Autophagy is a lysosomal degradation pathway that is essential for maintaining the homeostasis of the intracellular environment. Mounting evidence indicates that autophagy plays an essential role in the occurrence and development of hepatocellular cancer (HCC). This research is aimed at exploring the prognostic value of autophagy-related genes (ARGs) in HCC patients.

Methods

The Wilcoxon test was used to identify differentially expressed ARGs in The Cancer Genome Atlas (TCGA) HCC cohort. Then, the TCGA cohort was randomly divided into training and testing groups. Cox and LASSO regression models were used to screen for autophagy-related genes that affect overall survival (OS) in the TCGA training group. Based on the coefficient of risk genes, we constructed an autophagy-related gene signature for predicting the prognosis of HCC patients. Finally, we validated the prognostic significance of autophagy-related gene signature using the TCGA testing group and three external datasets.

Results

ATG10, BIRC5, GAPDH, and TMEM74 are risk genes for OS. According to the optimal cutoff value of risk score in each HCC dataset, HCC patients can divide into high- and low-risk groups. ARG risk score can significantly distinguish HCC patients with different survival outcomes. Meanwhile, the ARG risk score is independently correlated with OS in multiple HCC cohorts.

Conclusions

The autophagy-related risk score can effectively screen high-risk HCC patients and provide guidance for clinical prevention and treatment of HCC.

Functional coupling of Tmem74 and HCN1 channels regulates anxiety-like behavior in BLA neurons

Anxiety disorders are the most prevalent psychiatric disorders, but their pathogenic mechanism remains poorly understood. Here, we report that transmembrane protein 74 (TMEM74), which contains two putative transmembrane domains and exhibits high levels of mRNA in the brain, is closely associated with the pathogenesis of anxiety disorders. TMEM74 was decreased in the serum of patients with anxiety and the basolateral amygdaloid nucleus (BLA) in chronic stress mice. Furthermore, genetic deletion of Tmem74 or selective knockdown of Tmem74 in BLA pyramidal neurons resulted in anxiety-like behaviors in mice. Whole-cell recordings in BLA pyramidal neurons revealed lower hyperpolarization-activated cation current (I_h) and greater input resistance and excitability in Tmem74^-/- neurons than in wild-type neurons. Accordingly, surface expression of hyperpolarization-activated cyclic nucleotide-gated 1 (HCN1) channels was also lower in the BLA of Tmem74^-/- mice. The I_h current blocker ZD7288 mimicked these effects in BLA pyramidal neurons in wild-type mice but not in Tmem74^-/- mice. Consistent with the improvement in anxiety-like behaviors, Tmem74 overexpression restored HCN1 channel trafficking and pyramidal neuron excitability in the BLA of Tmem74^-/- and chronic stress mice. Mechanistically, we demonstrate that interactions between Tmem74 and HCN1 are physiologically relevant and that transmembrane domain 1 (TM1) is essential for the cellular membrane localization of Tmem74 to enhance I_h. Together, our findings suggest that Tmem74 coupling with HCN1 acts as a critical component in the pathophysiology of anxiety and is a potential target for new treatments of anxiety disorders.