RhoB is regulated by hypoxia and modulates metastasis in breast cancer

Single-cell transcriptome analysis of macrophage subpopulations contributing to chemotherapy resistance in ovarian cancer

BACKGROUND

Ovarian cancer, a fatal gynecological malignancy, is primarily managed through surgery and chemotherapy. However, a significant challenge arises as patients frequently experience relapse due to chemotherapy resistance. This study delves into the complex functions and underlying mechanisms of macrophages in chemotherapy resistance in ovarian cancer.

METHOD

The single-cell transcriptome sequencing data of ovarian cancer with or without chemotherapy were analyzed. Then, corresponding cell types were identified, and macrophages were extracted from all cells. Following the standardized single-cell analysis using the Seurat package, 15 distinct macrophage clusters were found and differentially expressed genes among them were analyzed. Moreover, their association with chemotherapy resistance was explored through cell proportions and gene expression.

RESULT

In the single-cell transcriptomic analysis of ovarian cancer tissues before and after chemotherapy, the cellular proportion of CXCL5+ macrophages, THBS1+ macrophages, and MMP9+ macrophages were significantly increased following chemotherapy. Further investigation revealed that these macrophage subpopulations upregulated the expression of multiple pro-tumorigenic angiogenic or invasive factors, in addition to CXCL5, THBS1, and MMP9, including CTSL, CXCL1, and CCL18. Finally, pathway enrichment analysis revealed the significant activation of signaling pathways, such as NOD-like receptor, MAPK, and TNF in these macrophage subpopulations, which provides direction for studying the mechanism of these subpopulations.

CONCLUSION

CXCL5+, THBS1+, and MMP9+ macrophage subpopulations exhibit an increased cellular prevalence post-chemotherapy and pro-tumorigenic molecular expression profiles, suggesting a close association with chemoresistance in ovarian cancer. These findings contribute to our understanding of the roles and mechanisms of macrophages in ovarian cancer chemoresistance, providing a theoretical basis and direction for the development of therapies targeting macrophages in overcoming ovarian cancer chemoresistance.

Unsupervised spatially embedded deep representation of spatial transcriptomics

Optimal integration of transcriptomics data and associated spatial information is essential towards fully exploiting spatial transcriptomics to dissect tissue heterogeneity and map out inter-cellular communications. We present SEDR, which uses a deep autoencoder coupled with a masked self-supervised learning mechanism to construct a low-dimensional latent representation of gene expression, which is then simultaneously embedded with the corresponding spatial information through a variational graph autoencoder. SEDR achieved higher clustering performance on manually annotated 10 × Visium datasets and better scalability on high-resolution spatial transcriptomics datasets than existing methods. Additionally, we show SEDR's ability to impute and denoise gene expression (URL: https://github.com/JinmiaoChenLab/SEDR/ ).

Identifying the driver miRNAs with somatic copy number alterations driving dysregulated ceRNA networks in cancers

BACKGROUND

MicroRNAs (miRNAs) play critical roles in cancer initiation and progression, which were critical components to maintain the dynamic balance of competing endogenous RNA (ceRNA) networks. Somatic copy number alterations (SCNAs) in the cancer genome could disturb the transcriptome level of miRNA to deregulate this balance. However, the driving effects of SCNAs of miRNAs were insufficiently understood.

METHODS

In this study, we proposed a method to dissect the functional roles of miRNAs under different copy number states and identify driver miRNAs by integrating miRNA SCNAs profile, miRNA-target relationships and expression profiles of miRNA, mRNA and lncRNA.

RESULTS

Applying our method to 813 TCGA breast cancer (BRCA) samples, we identified 29 driver miRNAs whose SCNAs significantly and concordantly regulated their own expression levels and further inversely dysregulated expression levels of their targets or disturbed the miRNA-target networks they directly involved. Based on miRNA-target networks, we further constructed dynamic ceRNA networks driven by driver SCNAs of miRNAs and identified three different patterns of SCNA interference in the miRNA-mediated dynamic ceRNA networks. Survival analysis of driver miRNAs showed that high-level amplifications of four driver miRNAs (including has-miR-30d-3p, has-mir-30b-5p, has-miR-30d-5p and has-miR-151a-3p) in 8q24 characterized a new BRCA subtype with poor prognosis and contributed to the dysfunction of cancer-associated hallmarks in a complementary way. The SCNAs of driver miRNAs across different cancer types contributed to the cancer development by dysregulating different components of the same cancer hallmarks, suggesting the cancer specificity of driver miRNA.

CONCLUSIONS

These results demonstrate the efficacy of our method in identifying driver miRNAs and elucidating their functional roles driven by endogenous SCNAs, which is useful for interpreting cancer genomes and pathogenic mechanisms.

Tensor Decomposition of Largest Convolutional Eigenvalues Reveals Pathologic Predictive Power of RhoB in Rectal Cancer Biopsy

RhoB protein belongs to the Rho GTPase family, which plays an important role in governing cell signaling and tissue morphology. RhoB expression is known to have implications in pathologic processes of diseases. Investigation in the regulation and communication of this protein, detected by immunohistochemical staining on the microscope, is worth exploring to gain insightful information that may lead to identifying optimal disease treatment options. In particular, the role of RhoB in rectal cancer is not well discovered. Here, we report that methods of deep learning-based image analysis and the decomposition of multiway arrays discover the predictive factor of RhoB in two cohorts of patients with rectal cancer having survival rates of <5 and >5 years. The analysis results show distinctions between the tensor decomposition factors of the two cohorts.

RhoB Promotes Endometrial Stromal Cells Decidualization Via Semaphorin3A/PlexinA4 Signaling in Early Pregnancy

Endometrial decidualization refers to a series of morphological changes and functional remodeling of the uterine endometrium to accept the embryo under the effect of estrogen and progesterone secreted by ovaries after ovulation. During decidualization, endometrial stromal cells (ESCs) proliferate and differentiate into decidual stromal cells, undergoing cytoskeletal rearrangement-mediated morphological changes and expressing decidualization markers, such as insulin-like growth factor-binding protein-1 and prolactin. Ras homology (Rho) proteins, a family of small G proteins, are well known as regulators of cellular morphology and involved in multiple other cellular processes. In this study, we found ras homolog family member B (RHOB) was the most significantly upregulated gene in the Rho protein family after the in vitro decidualization of human primary ESCs. RhoB expression was induced mainly by 3',5'-cyclic adenosine 5'-monophosphate (cAMP) / protein kinase A (PKA) / cyclic adenosine monophosphate-response element binding protein signaling and partly by progesterone signaling. Knockdown of RhoB in ESCs greatly inhibited actin cytoskeletal rearrangement, cell morphological transformation, and upregulation of insulin-like growth factor-binding protein-1, suggesting an indispensable role of RhoB in decidualization. Mechanistically, the downstream target of RhoB was semaphorin3A (Sema3A), which mediated its signaling via interacting with the receptor, plexinA4. More importantly, decreased expression of RhoB, Sema3A, and plexinA4 were detected in deciduas from patients with unexplained spontaneous miscarriage. Collectively, our results indicate that RhoB/Sema3A/plexinA4 signaling plays a positive role in endometrial decidualization and relates to unexplained spontaneous miscarriage, which is worthy of further exploration so as to provide new insights into therapeutic strategies for pregnancy diseases associated with poor decidualization.

MetastaSite: Predicting metastasis to different sites using deep learning with gene expression data

Deep learning has massive potential in predicting phenotype from different omics profiles. However, deep neural networks are viewed as black boxes, providing predictions without explanation. Therefore, the requirements for these models to become interpretable are increasing, especially in the medical field. Here we propose a computational framework that takes the gene expression profile of any primary cancer sample and predicts whether patients’ samples are primary (localized) or metastasized to the brain, bone, lung, or liver based on deep learning architecture. Specifically, we first constructed an AutoEncoder framework to learn the non-linear relationship between genes, and then DeepLIFT was applied to calculate genes’ importance scores. Next, to mine the top essential genes that can distinguish the primary and metastasized tumors, we iteratively added ten top-ranked genes based upon their importance score to train a DNN model. Then we trained a final multi-class DNN that uses the output from the previous part as an input and predicts whether samples are primary or metastasized to the brain, bone, lung, or liver. The prediction performances ranged from AUC of 0.93–0.82. We further designed the model’s workflow to provide a second functionality beyond metastasis site prediction, i.e., to identify the biological functions that the DL model uses to perform the prediction. To our knowledge, this is the first multi-class DNN model developed for the generic prediction of metastasis to various sites.

Detection of Hypoxia in Cancer Models: Significance, Challenges, and Advances

The rapid proliferation of cancer cells combined with deficient vessels cause regions of nutrient and O₂ deprivation in solid tumors. Some cancer cells can adapt to these extreme hypoxic conditions and persist to promote cancer progression. Intratumoral hypoxia has been consistently associated with a worse patient prognosis. In vitro, 3D models of spheroids or organoids can recapitulate spontaneous O₂ gradients in solid tumors. Likewise, in vivo murine models of cancer reproduce the physiological levels of hypoxia that have been measured in human tumors. Given the potential clinical importance of hypoxia in cancer progression, there is an increasing need to design methods to measure O₂ concentrations. O₂ levels can be directly measured with needle-type probes, both optical and electrochemical. Alternatively, indirect, noninvasive approaches have been optimized, and include immunolabeling endogenous or exogenous markers. Fluorescent, phosphorescent, and luminescent reporters have also been employed experimentally to provide dynamic measurements of O₂ in live cells or tumors. In medical imaging, modalities such as MRI and PET are often the method of choice. This review provides a comparative overview of the main methods utilized to detect hypoxia in cell culture and preclinical models of cancer.

RHO GTPase-Related Long Noncoding RNAs in Human Cancers

RHO GTPases are critical signal transducers that regulate cell adhesion, polarity, and migration through multiple signaling pathways. While all these cellular processes are crucial for the maintenance of normal cell homeostasis, disturbances in RHO GTPase-associated signaling pathways contribute to different human diseases, including many malignancies. Several members of the RHO GTPase family are frequently upregulated in human tumors. Abnormal gene regulation confirms the pivotal role of lncRNAs as critical gene regulators, and thus, they could potentially act as oncogenes or tumor suppressors. lncRNAs most likely act as sponges for miRNAs, which are known to be dysregulated in various cancers. In this regard, the significant role of miRNAs targeting RHO GTPases supports the view that the aberrant expression of lncRNAs may reciprocally change the intensity of RHO GTPase-associated signaling pathways. In this review article, we summarize recent advances in lncRNA research, with a specific focus on their sponge effects on RHO GTPase-targeting miRNAs to crucially mediate gene expression in different cancer cell types and tissues. We will focus in particular on five members of the RHO GTPase family, including RHOA, RHOB, RHOC, RAC1, and CDC42, to illustrate the role of lncRNAs in cancer progression. A deeper understanding of the widespread dysregulation of lncRNAs is of fundamental importance for confirmation of their contribution to RHO GTPase-dependent carcinogenesis.

A persistent invasive phenotype in post-hypoxic tumor cells is revealed by fate mapping and computational modeling

Hypoxia is a critical factor in solid tumors that has been associated with cancer progression and aggressiveness. We recently developed a hypoxia fate mapping system to trace post-hypoxic cells within a tumor for the first time. This approach uses an oxygen-dependent fluorescent switch and allowed us to measure key biological features such as oxygen distribution, cell proliferation, and migration. We developed a computational model to investigate the motility and phenotypic persistence of hypoxic and post-hypoxic cells during tumor progression. The cellular behavior was defined by phenotypic persistence time, cell movement bias, and the fraction of cells that respond to an enhanced migratory stimulus. This work combined advanced cell tracking and imaging techniques with mathematical modeling, to reveal that a persistent invasive migratory phenotype that develops under hypoxia is required for cellular escape into the surrounding tissue, promoting the formation of invasive structures (“plumes”) that expand toward the oxygenated tumor regions.

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A fluorescent fate mapping system allows tracking of hypoxic and post-hypoxic cells

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Computational modeling predicts the formation of post-hypoxic invasive plumes

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Simulations show post-hypoxic cells must maintain persistant migration to form plumes

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Tracking cells exposed to intratumoral hypoxia confirms persistent migration

Rho GTPases: Big Players in Breast Cancer Initiation, Metastasis and Therapeutic Responses

Rho GTPases, a family of the Ras GTPase superfamily, are key regulators of the actin cytoskeleton. They were originally thought to primarily affect cell migration and invasion; however, recent advances in our understanding of the biology and function of Rho GTPases have demonstrated their diverse roles within the cell, including membrane trafficking, gene transcription, migration, invasion, adhesion, survival and growth. As these processes are critically involved in cancer initiation, metastasis and therapeutic responses, it is not surprising that studies have demonstrated important roles of Rho GTPases in cancer. Although the majority of data indicates an oncogenic role of Rho GTPases, tumor suppressor functions of Rho GTPases have also been revealed, suggesting a context and cell-type specific function for Rho GTPases in cancer. This review aims to summarize recent progresses in our understanding of the regulation and functions of Rho GTPases, specifically in the context of breast cancer. The potential of Rho GTPases as therapeutic targets and prognostic tools for breast cancer patients are also discussed.

RhoB is regulated by hypoxia and modulates metastasis in breast cancer

BACKGROUND

RhoB is a Rho family GTPase that is highly homologous to RhoA and RhoC. RhoA and RhoC have been shown to promote tumor progression in many cancer types; however, a distinct role for RhoB in cancer has not been delineated. Additionally, several well-characterized studies have shown that small GTPases such as RhoA, Rac1, and Cdc42 are induced in vitro under hypoxia, but whether and how hypoxia regulates RhoB in breast cancer remains elusive.

AIMS

To determine whether and how hypoxia regulates RhoB expression and to understand the role of RhoB in breast cancer metastasis.

METHODS

We investigated the effects of hypoxia on the expression and activation of RhoB using real-time quantitative polymerase chain reaction and western blotting. We also examined the significance of both decreased and increased RhoB expression in breast cancer using CRISPR depletion of RhoB or a vector overexpressing RhoB in 3D in vitro migration models and in an in vivo mouse model.

RESULTS

We found that hypoxia significantly upregulated RhoB mRNA and protein expression resulting in increased levels of activated RhoB. Both loss of RhoB and gain of RhoB expression led to reduced migration in a 3D collagen matrix and invasion within a multicellular 3D spheroid. We showed that neither the reduction nor overexpression of RhoB affected tumor growth in vivo. While the loss of RhoB had no effect on metastasis, RhoB overexpression led to decreased metastasis to the lungs, liver, and lymph nodes of mice.

CONCLUSION

Our results suggest that RhoB may have an important role in suppressing breast cancer metastasis.