Extracellular vesicles released following heat stress induce bystander effects in unstressed populations

Cells naïve to stress can display the effects of stress, such as DNA damage and apoptosis when they are exposed to signals from stressed cells; this phenomenon is known as the bystander effect. We previously showed that bystander effects induced by ionising radiation are mediated by extracellular vesicles (EVs). Bystander effect can also be induced by other types of stress, including heat shock, but it is unclear whether EVs are involved. Here we show that EVs released from heat shocked cells are also able to induce bystander damage in un-stressed populations. Naïve cells treated with media conditioned by heat shocked cells showed higher levels of DNA damage and apoptosis than cells treated with media from control cells. Treating naïve cells with EVs derived from media conditioned by heat shocked cells also induced a bystander effect when compared to control, with DNA damage and apoptosis increasing whilst the level of cell viability was reduced. We demonstrate that treatment of naïve cells with heat shocked cell-derived EVs leads to greater invasiveness in a trans-well matrigel assay. Finally, we show that naïve cells treated with EVs from heat-shocked cells are more likely to survive a subsequent heat shock, suggesting that these EVs mediate an adaptive response. We propose that EVs released following stress mediate an intercellular response that leads to apparent stress in neighbouring cells but also greater robustness in the face of a subsequent insult

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

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

Meta-analysis using a novel database, miRStress, reveals miRNAs that are frequently associated with the radiation and hypoxia stress-responses.

Organisms are often exposed to environmental pressures that affect homeostasis, so it is important to understand the biological basis of stress-response. Various biological mechanisms have evolved to help cells cope with potentially cytotoxic changes in their environment. miRNAs are small non-coding RNAs which are able to regulate mRNA stability. It has been suggested that miRNAs may tip the balance between continued cytorepair and induction of apoptosis in response to stress. There is a wealth of data in the literature showing the effect of environmental stress on miRNAs, but it is scattered in a large number of disparate publications. Meta-analyses of this data would produce added insight into the molecular mechanisms of stress-response. To facilitate this we created and manually curated the miRStress database, which describes the changes in miRNA levels following an array of stress types in eukaryotic cells. Here we describe this database and validate the miRStress tool for analysing miRNAs that are regulated by stress. To validate the database we performed a cross-species analysis to identify miRNAs that respond to radiation. The analysis tool confirms miR-21 and miR-34a as frequently deregulated in response to radiation, but also identifies novel candidates as potentially important players in this stress response, including miR-15b, miR-19b, and miR-106a. Similarly, we used the miRStress tool to analyse hypoxia-responsive miRNAs. The most frequently deregulated miRNAs were miR-210 and miR-21, as expected. Several other miRNAs were also found to be associated with hypoxia, including miR-181b, miR-26a/b, miR-106a, miR-213 and miR-192. Therefore the miRStress tool has identified miRNAs with hitherto unknown or under-appreciated roles in the response to specific stress types. The miRStress tool, which can be used to uncover new insight into the biological roles of miRNAs, and also has the potential to unearth potential biomarkers for therapeutic response, is freely available at http://mudshark.brookes.ac.uk/MirStress

Longitudinal expression profiling identifies a poor risk subset of patients with ABC-type Diffuse Large B Cell Lymphoma.

Despite the effectiveness of immuno-chemotherapy, 40% of patients with diffuse large B-cell lymphoma (DLBCL) experience relapse or refractory disease. Longitudinal studies have previously focused on the mutational landscape of relapse but falling short of providing a consistent relapse-specific genetic signature. In our study, we have focussed attention on the changes in gene expression profile accompanying DLBCL relapse using archival paired diagnostic/relapse specimens from 38 de novo DLBCL patients. Cell of origin remained stable from diagnosis to relapse in 84% of patients, with only a single patient showing COO switching from ABC to GCB. Analysis of the transcriptomic changes that occur following relapse suggest ABC and GCB relapses are mediated via different mechanisms. We developed a 30-gene discriminator for ABC-DLBCLs derived from relapse-associated genes, that defined clinically distinct high and low risk subgroups in ABC-DLBCLs at diagnosis in datasets comprising both population-based and clinical trial cohorts. This signature also identified a population of <60-year-old patients with superior PFS and OS treated with Ibrutinib-R-CHOP as part of the PHOENIX trial. Altogether this new signature adds to the existing toolkit of putative genetic predictors now available in DLBCL that can be readily assessed as part of prospective clinical trials

Longitudinal expression profiling identifies a poor risk subset of patients with ABC-type diffuse large B-cell lymphoma

Despite the effectiveness of immuno-chemotherapy, 40% of patients with diffuse large B-cell lymphoma (DLBCL) experience relapse or refractory disease. Longitudinal studies have previously focused on the mutational landscape of relapse but fell short of providing a consistent relapse-specific genetic signature. In our study, we have focused attention on the changes in GEP accompanying DLBCL relapse using archival paired diagnostic/relapse specimens from 38 de novo patients with DLBCL. COO remained stable from diagnosis to relapse in 80% of patients, with only a single patient showing COO switching from activated B-cell–like (ABC) to germinal center B-cell–like (GCB). Analysis of the transcriptomic changes that occur following relapse suggest ABC and GCB relapses are mediated via different mechanisms. We developed a 30-gene discriminator for ABC–DLBCLs derived from relapse-associated genes that defined clinically distinct high- and low-risk subgroups in ABC–DLBCLs at diagnosis in datasets comprising both population-based and clinical trial cohorts. This signature also identified a population of <60-year–old patients with superior PFS and OS treated with ibrutinib–R-CHOP as part of the PHOENIX trial. Altogether this new signature adds to the existing toolkit of putative genetic predictors now available in DLBCL that can be readily assessed as part of prospective clinical trials

Extracellular vesicles released following heat stress induce bystander effect in unstressed populations

Cells naïve to stress can display the effects of stress, such as DNA damage and apoptosis, when they are exposed to signals from stressed cells; this phenomenon is known as the bystander effect. We previously showed that bystander effect induced by ionising radiation are mediated by extracellular vesicles (EVs). Bystander effect can also be induced by other types of stress, including heat shock, but it is unclear whether EVs are involved. Here we show that EVs released from heat shocked cells are also able to induce bystander damage in unstressed populations. Naïve cells treated with media conditioned by heat shocked cells showed higher levels of DNA damage and apoptosis than cells treated with media from control cells. Treating naïve cells with EVs derived from media conditioned by heat shocked cells also induced a bystander effect when compared to control, with DNA damage and apoptosis increasing whilst the level of cell viability was reduced. We demonstrate that treatment of naïve cells with heat shocked cell-derived EVs leads to greater invasiveness in a trans-well Matrigel assay. Finally, we show that naïve cells treated with EVs from heat-shocked cells are more likely to survive a subsequent heat shock, suggesting that these EVs mediate an adaptive response. We propose that EVs released following stress mediate an intercellular response that leads to apparent stress in neighbouring cells but also greater robustness in the face of a subsequent insult