Meta-analysis of RNA interaction profiles of RNA-binding protein using the RBPInper tool

Motivation Recent RNA-centric experimental methods have significantly expanded our knowledge of proteins with known RNA-binding functions. However, the complete regulatory network and pathways for many of these RNA-binding proteins (RBPs) in different cellular contexts remain unknown. Although critical to understanding the role of RBPs in health and disease, experimentally mapping the RBP–RNA interactomes in every single context is an impossible task due the cost and manpower required. Additionally, identifying relevant RNAs bound by RBPs is challenging due to their diverse binding modes and function. Results To address these challenges, we developed RBP interaction mapper RBPInper an integrative framework that discovers global RBP interactome using statistical data fusion. Experiments on splicing factor proline and glutamine rich (SFPQ) datasets revealed cogent global SFPQ interactome. Several biological processes associated with this interactome were previously linked with SFPQ function. Furthermore, we conducted tests using independent dataset to assess the transferability of the SFPQ interactome to another context. The results demonstrated robust utility in generating interactomes that transfers to unseen cellular context. Overall, RBPInper is a fast and user-friendly method that enables a systems-level understanding of RBP functions by integrating multiple molecular datasets. The tool is designed with a focus on simplicity, minimal dependencies, and straightforward input requirements. This intentional design aims to empower everyday biologists, making it easy for them to incorporate the tool into their research

SFPQ promotes an oncogenic transcriptomic state in melanoma.

The multifunctional protein, splicing factor, proline- and glutamine-rich (SFPQ) has been implicated in numerous cancers often due to interaction with coding and non-coding RNAs, however, its role in melanoma remains unclear. We report that knockdown of SFPQ expression in melanoma cells decelerates several cancer-associated cell phenotypes, including cell growth, migration, epithelial to mesenchymal transition, apoptosis, and glycolysis. RIP-seq analysis revealed that the SFPQ-RNA interactome is reprogrammed in melanoma cells and specifically enriched with key melanoma-associated coding and long non-coding transcripts, including SOX10, AMIGO2 and LINC00511 and in most cases SFPQ is required for the efficient expression of these genes. Functional analysis of two SFPQ-enriched lncRNA, LINC00511 and LINC01234, demonstrated that these genes independently contribute to the melanoma phenotype and a more detailed analysis of LINC00511 indicated that this occurs in part via modulation of the miR-625-5p/PKM2 axis. Importantly, analysis of a large clinical cohort revealed that elevated expression of SFPQ in primary melanoma tumours may have utility as a prognostic biomarker. Together, these data suggest that SFPQ is an important driver of melanoma, likely due to SFPQ-RNA interactions promoting the expression of numerous oncogenic transcripts

Platelet-derived microvesicles isolated from type-2 diabetes mellitus patients harbour an altered miRNA signature and drive MDA-MB-231 triple-negative breast cancer cell invasion

The underlying causes of breast cancer are diverse, however, there is a striking association between type 2 diabetes and poor patient outcomes. Platelet activation is a common feature of both type 2 diabetes and breast cancer and has been implicated in tumourigenesis through a multitude of pathways. Here transcriptomic analysis of type 2 diabetes patient-derived platelet microvesicles revealed an altered miRNA signature compared with normoglycaemic control patients. Interestingly, interrogation of these data identifies a shift towards an oncogenic signature in type 2 diabetes-derived platelet microvesicles, with increased levels of miRNAs implicated in breast cancer progression and poor prognosis. Functional studies demonstrate that platelet microvesicles isolated from type 2 diabetes patient blood are internalised by triple-negative breast cancer cells in vitro, and that co-incubation with type 2 diabetes patient-derived platelet microvesicles led to significantly increased expression of epithelial to mesenchymal transition markers and triple-negative breast cancer cell invasion compared with platelet microvesicles from healthy volunteers. Together, these data suggest that circulating PMVs in type 2 diabetes patients may contribute to the progression of triple-negative breast cancer

Transcriptomic analysis of cutaneous squamous cell carcinoma reveals a multi-gene prognostic signature associated with metastasis.

BACKGROUND: Metastasis of cutaneous squamous cell carcinoma (cSCC) is uncommon. Current staging methods are reported to have sub-optimal performances in metastasis prediction. Accurate identification of patients with tumours at high risk of metastasis would have a significant impact on management. OBJECTIVE: To develop a robust and validated gene expression profile (GEP) signature for predicting primary cSCC metastatic risk using an unbiased whole transcriptome discovery-driven approach. METHODS: Archival formalin-fixed paraffin-embedded primary cSCC with perilesional normal tissue from 237 immunocompetent patients (151 non-metastasising and 86 metastasising) were collected retrospectively from four centres. TempO-seq was used to probe the whole transcriptome and machine learning algorithms were applied to derive predictive signatures, with a 3:1 split for training and testing datasets. RESULTS: A 20-gene prognostic model was developed and validated, with an accuracy of 86.0%, sensitivity of 85.7%, specificity of 86.1%, and positive predictive value of 78.3% in the testing set, providing more stable, accurate prediction than pathological staging systems. A linear predictor was also developed, significantly correlating with metastatic risk. LIMITATIONS: This was a retrospective 4-centre study and larger prospective multicentre studies are now required. CONCLUSION: The 20-gene signature prediction is accurate, with the potential to be incorporated into clinical workflows for cSCC

The Hippo pathway transcription factors YAP and TAZ play HPV-type dependent roles in cervical cancer

Human papillomaviruses (HPVs) cause most cervical cancers and an increasing number of anogenital and oral carcinomas, with most cases caused by HPV16 or HPV18. HPV hijacks host signalling pathways to promote carcinogenesis. Understanding these interactions could permit identification of much-needed therapeutics for HPV-driven malignancies. The Hippo signalling pathway is important in HPV+ cancers, with the downstream effector YAP playing a pro-oncogenic role. In contrast, the significance of its paralogue TAZ remains largely uncharacterised in these cancers. We demonstrate that TAZ is dysregulated in a HPV-type dependent manner by a distinct mechanism to that of YAP and controls proliferation via alternative cellular targets. Analysis of cervical cancer cell lines and patient biopsies revealed that TAZ expression was only significantly increased in HPV18+ and HPV18-like cells and TAZ knockdown reduced proliferation, migration and invasion only in HPV18+ cells. RNA-sequencing of HPV18+ cervical cells revealed that YAP and TAZ have distinct targets, suggesting they promote carcinogenesis by different mechanisms. Thus, in HPV18+ cancers, YAP and TAZ play non-redundant roles. This analysis identified TOGARAM2 as a previously uncharacterised TAZ target and demonstrates its role as a key effector of TAZ-mediated proliferation, migration and invasion in HPV18+ cancers

Transcriptomic analysis of cutaneous squamous cell carcinoma reveals a multi-gene prognostic signature associated with metastasis.

BackgroundMetastasis of cutaneous squamous cell carcinoma (cSCC) is uncommon. Current staging methods are reported to have sub-optimal performances in metastasis prediction. Accurate identification of patients with tumours at high risk of metastasis would have a significant impact on management.ObjectiveTo develop a robust and validated gene expression profile (GEP) signature for predicting primary cSCC metastatic risk using an unbiased whole transcriptome discovery-driven approach.MethodsArchival formalin-fixed paraffin-embedded primary cSCC with perilesional normal tissue from 237 immunocompetent patients (151 non-metastasising and 86 metastasising) were collected retrospectively from four centres. TempO-seq was used to probe the whole transcriptome and machine learning algorithms were applied to derive predictive signatures, with a 3:1 split for training and testing datasets.ResultsA 20-gene prognostic model was developed and validated, with an accuracy of 86.0%, sensitivity of 85.7%, specificity of 86.1%, and positive predictive value of 78.3% in the testing set, providing more stable, accurate prediction than pathological staging systems. A linear predictor was also developed, significantly correlating with metastatic risk.LimitationsThis was a retrospective 4-centre study and larger prospective multicentre studies are now required.ConclusionThe 20-gene signature prediction is accurate, with the potential to be incorporated into clinical workflows for cSCC

The integrated molecular and histological analysis defines subtypes of esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is highly heterogeneous. Our understanding of full molecular and immune landscape of ESCC remains limited, hindering the development of personalised therapeutic strategies. To address this, we perform genomic-transcriptomic characterizations and AI-aided histopathological image analysis of 120 Chinese ESCC patients. Here we show that ESCC can be categorized into differentiated, metabolic, immunogenic and stemness subtypes based on bulk and single-cell RNA-seq, each exhibiting specific molecular and histopathological features based on an amalgamated deep-learning model. The stemness subgroup with signature genes, such as WFDC2, SFRP1, LGR6 and VWA2, has the poorest prognosis and is associated with downregulated immune activities, a high frequency of EP300 mutation/activation, functional mutation enrichment in Wnt signalling and the highest level of intratumoural heterogeneity. The immune profiling by transcriptomics and immunohistochemistry reveals ESCC cells overexpress natural killer cell markers XCL1 and CD160 as immune evasion. Strikingly, XCL1 expression also affects the sensitivity of ESCC cells to common chemotherapy drugs. This study opens avenues for ESCC treatment and provides a valuable public resource to better understand ESCC

The role of CAF derived exosomal microRNAs in the tumour microenvironment of melanoma.

Exosomes play a crucial role in the crosstalk between cancer associated fibroblasts (CAFs) and cancer cells, contributing to carcinogenesis and the tumour microenvironment. Recent studies have revealed that CAFs, normal fibroblasts and cancer cells all secrete exosomes that contain miRNA, establishing a cell-cell communication network within the tumour microenvironment. For example, miRNA dysregulation in melanoma has been shown to promote CAF activation via induction of epithelial-mesenchymal transition (EMT), which in turn alters the secretory phenotype of CAFs in the stroma. This review assesses the roles of melanoma exosomal miRNAs in CAF formation and how CAF exosome-mediated feedback signalling to melanoma lead to tumour progression and metastasis. Moreover, efforts to exploit exosomal miRNA-mediated network communication between tumour cells and their microenvironment, and their potential as prognostic biomarkers or novel therapeutic targets in melanoma will also be considered