Detection of fusion gene transcripts in the blood samples of prostate cancer patients

Immuno-targeting the ectopic phosphorylation sites of PDGFRA generated by MAN2A1-FER fusion in HCC

BACKGROUND

HCC is one of the most lethal cancers for humans. Mannosidase alpha class 2A member 1 (MAN2A1)-FER is one of the most frequent oncogenic fusion genes in HCC. In this report, we showed that MAN2A1-FER ectopically phosphorylated the extracellular domains of PDGFRA, MET, AXL, and N-cadherin. The ectopic phosphorylation of these transmembrane proteins led to the activation of their kinase activities and initiated the activation cascades of their downstream signaling molecules.

METHODS

A panel of mouse monoclonal antibodies was developed to recognize the ectopic phosphorylation sites of PDGFRA.

RESULTS AND CONCLUSIONS

The analyses showed that these antibodies bound to the specific phosphotyrosine epitopes in the extracellular domain of PDGFRA with high affinity and specificity. The treatment of MAN2A1-FER-positive cancer HUH7 with one of the antibodies called 2-3B-G8 led to the deactivation of cell growth signaling pathways and cell growth arrest while having minimal impact on HUH7ko cells where MAN2A1-FER expression was disrupted. The treatment of 2-3B-G8 antibody also led to a large number of cell deaths of MAN2A1-FER-positive cancer cells such as HUH7, HEPG2, SNU449, etc., while the same treatment had no impact on HUH7ko cells. When severe combined immunodeficiency mice xenografted with HEPG2 or HUH7 were treated with monomethyl auristatin E-conjugated 2-3B-G8 antibody, it slowed the progression of tumor growth, eliminated the metastasis, and reduced the mortality, in comparison with the controls. Targeting the cancer-specific ectopic phosphorylation sites of PDGFRA induced by MAN2A1-FER may hold promise as an effective treatment for liver cancer.

IFDlong: an isoform and fusion detector for accurate annotation and quantification of long-read RNA-seq data

Advancements in long-read transcriptome sequencing (long-RNA-seq) technology have revolutionized the study of isoform diversity. These full-length transcripts enhance the detection of various transcriptome structural variations, including novel isoforms, alternative splicing events, and fusion transcripts. By shifting the open reading frame or altering gene expressions, studies have proved that these transcript alterations can serve as crucial biomarkers for disease diagnosis and therapeutic targets. In this project, we proposed IFDlong, a bioinformatics and biostatistics tool to detect isoform and fusion transcripts using bulk or single-cell long-RNA-seq data. Specifically, the software performed gene and isoform annotation for each long-read, defined novel isoforms, quantified isoform expression by a novel expectation-maximization algorithm, and profiled the fusion transcripts. For evaluation, IFDlong pipeline achieved overall the best performance when compared with several existing tools in large-scale simulation studies. In both isoform and fusion transcript quantification, IFDlong is able to reach more than 0.8 Spearman's correlation with the truth, and more than 0.9 cosine similarity when distinguishing multiple alternative splicing events. In novel isoform simulation, IFDlong can successfully balance the sensitivity (higher than 90%) and specificity (higher than 90%). Furthermore, IFDlong has proved its accuracy and robustness in diverse in-house and public datasets on healthy tissues, cell lines and multiple types of diseases. Besides bulk long-RNA-seq, IFDlong pipeline has proved its compatibility to single-cell long-RNA-seq data. This new software may hold promise for significant impact on long-read transcriptome analysis. The IFDlong software is available at https://github.com/wenjiaking/IFDlong.

Integration of single-cell RNA-seq and bulk RNA-seq data to construct and validate a cancer-associated fibroblast-related prognostic signature for patients with ovarian cancer

BACKGROUND

To establish a prognostic risk profile for ovarian cancer (OC) patients based on cancer-associated fibroblasts (CAFs) and gain a comprehensive understanding of their role in OC progression, prognosis, and therapeutic efficacy.

METHODS

Data on OC single-cell RNA sequencing (scRNA-seq) and total RNA-seq were collected from the GEO and TCGA databases. Seurat R program was used to analyze scRNA-seq data and identify CAFs clusters corresponding to CAFs markers. Differential expression analysis was performed on the TCGA dataset to identify prognostic genes. A CAF-associated risk signature was designed using Lasso regression and combined with clinicopathological variables to develop a nomogram. Functional enrichment and the immune landscape were also analyzed.

RESULTS

Five CAFs clusters were identified in OC using scRNA-seq data, and 2 were significantly associated with OC prognosis. Seven genes were selected to develop a CAF-based risk signature, primarily associated with 28 pathways. The signature was a key independent predictor of OC prognosis and relevant in predicting the results of immunotherapy interventions. A novel nomogram combining CAF-based risk and disease stage was developed to predict OC prognosis.

CONCLUSION

The study highlights the importance of CAFs in OC progression and suggests potential for innovative treatment strategies. A CAF-based risk signature provides a highly accurate prediction of the prognosis of OC patients, and the developed nomogram shows promising results in predicting the OC prognosis.

Roles of transmembrane protein 135 in mitochondrial and peroxisomal functions - implications for age-related retinal disease

Aging is the most significant risk factor for age-related diseases in general, which is true for age-related diseases in the eye including age-related macular degeneration (AMD). Therefore, in order to identify potential therapeutic targets for these diseases, it is crucial to understand the normal aging process and how its mis-regulation could cause age-related diseases at the molecular level. Recently, abnormal lipid metabolism has emerged as one major aspect of age-related symptoms in the retina. Animal models provide excellent means to identify and study factors that regulate lipid metabolism in relation to age-related symptoms. Central to this review is the role of transmembrane protein 135 (TMEM135) in the retina. TMEM135 was identified through the characterization of a mutant mouse strain exhibiting accelerated retinal aging and positional cloning of the responsible mutation within the gene, indicating the crucial role of TMEM135 in regulating the normal aging process in the retina. Over the past decade, the molecular functions of TMEM135 have been explored in various models and tissues, providing insights into the regulation of metabolism, particularly lipid metabolism, through its action in multiple organelles. Studies indicated that TMEM135 is a significant regulator of peroxisomes, mitochondria, and their interaction. Here, we provide an overview of the molecular functions of TMEM135 which is crucial for regulating mitochondria, peroxisomes, and lipids. The review also discusses the age-dependent phenotypes in mice with TMEM135 perturbations, emphasizing the importance of a balanced TMEM135 function for the health of the retina and other tissues including the heart, liver, and adipose tissue. Finally, we explore the potential roles of TMEM135 in human age-related retinal diseases, connecting its functions to the pathobiology of AMD.

Decoding Oncofusions: Unveiling Mechanisms, Clinical Impact, and Prospects for Personalized Cancer Therapies

Cancer-associated gene fusions, also known as oncofusions, have emerged as influential drivers of oncogenesis across a diverse range of cancer types. These genetic events occur via chromosomal translocations, deletions, and inversions, leading to the fusion of previously separate genes. Due to the drastic nature of these mutations, they often result in profound alterations of cellular behavior. The identification of oncofusions has revolutionized cancer research, with advancements in sequencing technologies facilitating the discovery of novel fusion events at an accelerated pace. Oncofusions exert their effects through the manipulation of critical cellular signaling pathways that regulate processes such as proliferation, differentiation, and survival. Extensive investigations have been conducted to understand the roles of oncofusions in solid tumors, leukemias, and lymphomas. Large-scale initiatives, including the Cancer Genome Atlas, have played a pivotal role in unraveling the landscape of oncofusions by characterizing a vast number of cancer samples across different tumor types. While validating the functional relevance of oncofusions remains a challenge, even non-driver mutations can hold significance in cancer treatment. Oncofusions have demonstrated potential value in the context of immunotherapy through the production of neoantigens. Their clinical importance has been observed in both treatment and diagnostic settings, with specific fusion events serving as therapeutic targets or diagnostic markers. However, despite the progress made, there is still considerable untapped potential within the field of oncofusions. Further research and validation efforts are necessary to understand their effects on a functional basis and to exploit the new targeted treatment avenues offered by oncofusions. Through further functional and clinical studies, oncofusions will enable the advancement of precision medicine and the drive towards more effective and specific treatments for cancer patients.

Characterization and evaluation of gene fusions as a measure of genetic instability and disease prognosis in prostate cancer

BACKGROUND

Prostate cancer (PCa) is one of the most prevalent cancers worldwide. The clinical manifestations and molecular characteristics of PCa are highly variable. Aggressive types require radical treatment, whereas indolent ones may be suitable for active surveillance or organ-preserving focal therapies. Patient stratification by clinical or pathological risk categories still lacks sufficient precision. Incorporating molecular biomarkers, such as transcriptome-wide expression signatures, improves patient stratification but so far excludes chromosomal rearrangements. In this study, we investigated gene fusions in PCa, characterized potential novel candidates, and explored their role as prognostic markers for PCa progression.

METHODS

We analyzed 630 patients in four cohorts with varying traits regarding sequencing protocols, sample conservation, and PCa risk group. The datasets included transcriptome-wide expression and matched clinical follow-up data to detect and characterize gene fusions in PCa. With the fusion calling software Arriba, we computationally predicted gene fusions. Following detection, we annotated the gene fusions using published databases for gene fusions in cancer. To relate the occurrence of gene fusions to Gleason Grading Groups and disease prognosis, we performed survival analyses using the Kaplan-Meier estimator, log-rank test, and Cox regression.

RESULTS

Our analyses identified two potential novel gene fusions, MBTTPS2,L0XNC01::SMS and AMACR::AMACR. These fusions were detected in all four studied cohorts, providing compelling evidence for the validity of these fusions and their relevance in PCa. We also found that the number of gene fusions detected in a patient sample was significantly associated with the time to biochemical recurrence in two of the four cohorts (log-rank test, p-value < 0.05 for both cohorts). This was also confirmed after adjusting the prognostic model for Gleason Grading Groups (Cox regression, p-values < 0.05).

CONCLUSIONS

Our gene fusion characterization workflow revealed two potential novel fusions specific for PCa. We found evidence that the number of gene fusions was associated with the prognosis of PCa. However, as the quantitative correlations were only moderately strong, further validation and assessment of clinical value is required before potential application.

Identification of leucine-rich repeat-containing protein 59 (LRRC59) located in the endoplasmic reticulum as a novel prognostic factor for urothelial carcinoma

BACKGROUND

Urothelial carcinoma (UC) is one of the most common cancers worldwide. The biological heterogeneity of UCs causes considerable difficulties in predicting treatment outcomes and usually leads to clinical mismanagement. The identification of more sensitive and efficient predictive biomarkers is important in the diagnosis and classification of UCs. Herein, we report leucine-rich repeat-containing protein 59 (LRRC59) located in the endoplasmic reticulum as a novel predictive factor and potential therapeutic target for UCs.

METHODS

Using whole-slide image analysis in our cohort of 107 UC samples, we performed immunohistochemistry to evaluate the prognostic value of LRRC59 expression in UCs. In vitro experiments using RNAi were conducted to explore the role of LRRC59 in promoting UC cell proliferation and migration.

RESULTS

A significant correlation between LRRC59 and unfavorable prognosis of UCs in our cohort was demonstrated. Subsequent clinical analysis also revealed that elevated expression levels of LRRC59 were significantly associated with higher pathological grades and advanced stages of UC. Subsequently, knockdown of LRRC59 in UM-UC-3 and T24 cells using small interfering RNA significantly inhibited cell proliferation and migration, resulting in cell cycle arrest at the G1 phase. Conversely, the overexpression of LRRC59 in UC cells enhanced cell proliferation and migration. An integrated bioinformatics analysis revealed a significant functional network of LRRC59 involving protein misfolding, ER stress, and ubiquitination. Finally, in vitro experiments demonstrated that LRRC59 modulates ER stress signaling.

CONCLUSIONS

LRRC59 expression was significantly correlated with UC prognosis. LRRC59 might not only serve as a novel prognostic biomarker for risk stratification of patients with UC but also exhibit as a potential therapeutic target in UC that warrants further investigation.