A genomics approach to identify susceptibilities of breast cancer cells to "fever-range" hyperthermia

NINJ1 mediates inflammatory cell death, PANoptosis, and lethality during infection conditions and heat stress

Innate immunity provides the first line of defense through multiple mechanisms, including pyrogen production and cell death. While elevated body temperature during infection is beneficial to clear pathogens, heat stress (HS) can lead to inflammation and pathology. Links between pathogen exposure, HS, cytokine release, and inflammation have been observed, but fundamental innate immune mechanisms driving pathology during pathogen exposure and HS remain unclear. Here, we use multiple genetic approaches to elucidate innate immune pathways in infection or LPS and HS models. Our results show that bacteria and LPS robustly increase inflammatory cell death during HS that is dependent on caspase-1, caspase-11, caspase-8, and RIPK3 through the PANoptosis pathway. Caspase-7 also contributes to PANoptosis in this context. Furthermore, NINJ1 is an important executioner of this cell death to release inflammatory molecules, independent of other pore-forming executioner proteins, gasdermin D, gasdermin E, and MLKL. In an in vivo HS model, mortality is reduced by deleting NINJ1 and fully rescued by deleting key PANoptosis molecules. Our findings suggest that therapeutic strategies blocking NINJ1 or its upstream regulators to prevent PANoptosis may reduce the release of inflammatory mediators and benefit patients.

Nanoparticle-based immunotherapeutics: from the properties of nanocores to the differential effects of administration routes

The engagement with the immune system is one of the main cornerstones in the development of nanotechnologies for therapy and diagnostics. Recent advances have made possible the tuning of features like size, shape and biomolecular modifications that influence such interactions, however, the capabilities for immune modulation of nanoparticles are still not well defined and exploited. This review focuses on recent advances made in preclinical research for the application of nanoparticles to modulate immune responses, and the main features making them relevant for such applications. We review and discuss newest evidence in the field, which include in vivo experiments with an extensive physicochemical characterization as well as detailed study of the induced immune response. We emphasize the need of incorporating knowledge about immune response development and regulation in the design and application of nanoparticles, including the effect by parameters such as the administration route and the differential interactions with immune subsets.

The Effects of Heat Stress on the Transcriptome of Human Cancer Cells: A Meta-Analysis

Hyperthermia is clinically applied cancer treatment in conjunction with radio- and/or chemotherapy, in which the tumor volume is exposed to supraphysiological temperatures. Since cells can effectively counteract the effects of hyperthermia by protective measures that are commonly known as the heat stress response, the identification of cellular processes that are essential for surviving hyperthermia could lead to novel treatment strategies that improve its therapeutic effects. Here, we apply a meta-analytic approach to 18 datasets that capture hyperthermia-induced transcriptome alterations in nine different human cancer cell lines. We find, in line with previous reports, that hyperthermia affects multiple processes, including protein folding, cell cycle, mitosis, and cell death, and additionally uncover expression changes of genes involved in KRAS signaling, inflammatory responses, TNF-a signaling and epithelial-to-mesenchymal transition (EMT). Interestingly, however, we also find a considerable inter-study variability, and an apparent absence of a 'universal' heat stress response signature, which is likely caused by the differences in experimental conditions. Our results suggest that gene expression alterations after heat stress are driven, to a large extent, by the experimental context, and call for a more extensive, controlled study that examines the effects of key experimental parameters on global gene expression patterns.

Network analysis with biological data of cancer patients: A scoping review

BACKGROUND & OBJECTIVE

Network Analysis (NA) is a mathematical method that allows exploring relations between units and representing them as a graph. Although NA was initially related to social sciences, the past two decades was introduced in Bioinformatics. The recent growth of the networks' use in biological data analysis reveals the need to further investigate this area. In this work, we attempt to identify the use of NA with biological data, and specifically: (a) what types of data are used and whether they are integrated or not, (b) what is the purpose of this analysis, predictive or descriptive, and (c) the outcome of such analyses, specifically in cancer diseases.

METHODS & MATERIALS

The literature review was conducted on two databases, PubMed & IEEE, and was restricted to journal articles of the last decade (January 2010 - December 2019). At a first level, all articles were screened by title and abstract, and at a second level the screening was conducted by reading the full text article, following the predefined inclusion & exclusion criteria leading to 131 articles of interest. A table was created with the information of interest and was used for the classification of the articles. The articles were initially classified to analysis studies and studies that propose a new algorithm or methodology. Each one of these categories was further screened by the following clustering criteria: (a) data used, (b) study purpose, (c) study outcome. Specifically for the studies proposing a new algorithm, the novelty presented in each one was detected.

RESULTS

& Conclusions: In the past five years researchers are focusing on creating new algorithms and methodologies to enhance this field. The articles' classification revealed that only 25% of the analyses are integrating multi-omics data, although 50% of the new algorithms developed follow this integrative direction. Moreover, only 20% of the analyses and 10% of the newly developed methodologies have a predictive purpose. Regarding the result of the works reviewed, 75% of the studies focus on identifying, prognostic or not, gene signatures. Concluding, this review revealed the need for deploying predictive and multi-omics integrative algorithms and methodologies that can be used to enhance cancer diagnosis, prognosis and treatment.

CDK6 is stimulated by hyperthermia and protects gastric cancer cells from hyperthermia‑induced damage

Hyperthermia is one of the most widely employed adjuvant treatments for cancer, especially for hyperthermic intraperitoneal chemotherapy, and has few side effects. Gastric cancer has various hyperthermia sensitivities, but the exact molecular mechanisms remain to be elucidated. In the present study, western blotting was performed to detect differential expression of proteins that have been reported to be upregulated in gastric cancer. Following knockdown of these proteins, apoptosis was measured by Annexin V-FITC/propidium iodide (PI) double staining and hyperthermia treatment was applied. To evaluate the effect of cyclin-dependent kinase 6 (CDK6) on hyperthermia-induced apoptosis, CDK6 was knocked down or inhibited by the addition of a specific inhibitor and subsequent PI staining and cell proliferation, migration and invasion assays were performed. Hyperthermia-induced protein kinase B (AKT) expression and phosphorylation inhibition were detected. As demonstrated in the present study, the hyperthermia-induced proteins kinesin family member 11 (KIF11), cyclin-dependent kinase 6 (CDK6), stromal antigen 2, NIMA-related kinase 2 and karyopherin subunit α 4 were highly expressed in gastric cancer cells, including SH-10-TC and HGC-27 cells. Knockdown of KIF11 significantly increased apoptosis without hyperthermia treatment and CDK6 significantly increased hyperthermia-induced apoptosis, prompting the present study to focus on CDK6. It was further confirmed that CDK6 activity was critical for decreasing hyperthermia-induced apoptosis and for cell proliferation. Hyperthermia-induced AKT expression and phosphorylation inhibition is potentially the main cause of CDK6 transcriptional upregulation. Taken together, these findings demonstrated that CDK6 is upregulated via hyperthermia-induced AKT inhibition and subsequently protected gastric cancer cells from hyperthermia-induced apoptosis, indicating that it is a potential therapeutic target to sensitize gastric cancer cells to hyperthermia-based therapy.

Optimization of microbubble enhancement of hyperthermia for cancer therapy in an in vivo breast tumour model

We have demonstrated that exposing human breast tumour xenografts to ultrasound-stimulated microbubbles enhances tumour cell death and vascular disruption resulting from hyperthermia treatment. The aim of this study was to investigate the effect of varying the hyperthermia and ultrasound-stimulated microbubbles treatment parameters in order to optimize treatment bioeffects. Human breast cancer (MDA-MB-231) tumour xenografts in severe combined immunodeficiency (SCID) mice were exposed to varying microbubble concentrations (0%, 0.1%, 1% or 3% v/v) and ultrasound sonication durations (0, 1, 3 or 5 min) at 570 kPa peak negative pressure and central frequency of 500 kHz. Five hours later, tumours were immersed in a 43°C water bath for varying hyperthermia treatment durations (0, 10, 20, 30, 40, 50 or 60 minutes). Results indicated a significant increase in tumour cell death reaching 64 ± 5% with combined treatment compared to 11 ± 3% and 26 ± 5% for untreated and USMB-only treated tumours, respectively. A similar but opposite trend was observed in the vascular density of the tumours receiving the combined treatment. Optimal treatment parameters were found to consist of 40 minutes of heat with low power ultrasound treatment microbubble parameters of 1 minute of sonification and a 1% microbubble concentration.

Cancer cells resist hyperthermia due to its obstructed activation of caspase 3

Aim

It is well known that inducing hyperthermia is a type of cancer treatment but some research groups indicate that this treatment is not effective. This article finds and explains the mechanism of this treatment and its possible problems.

Background

Hyperthermia is commonly known as a state when the temperature of the body rises to a level that can threaten one's health. Hyperthermia is a type of cancer treatment in which body tissue is exposed to high temperatures (up to 45 °C). Research has shown that high temperatures can damage and kill cancer cells, usually with minimal injury to normal tissues. However, this mechanism is not known.

Materials and Methods

We recently treated cancer cells with different temperatures ranging from 37 °C to 47 °C and further measured their caspase 3 secretion by ELISA, western blot and cell survival rate by microscope.

Results

We found that most cancer cells are able to resist hyperthermia more than normal cells most likely via non-activation of caspase3. We also found that hyperthermia-treated (≥41°) cancer cells extend a long pseudopod-like extension in comparison to the same cancer cells under normal conditions.

Conclusion

Our data here indicates that cancer cells have resistance to higher temperatures compared to normal cells via non-activation of caspase 3. This is a significant issue that needs to be brought to attention as the medical community has always believed that a high temperature treatment can selectively kill cancer/tumor cells. Additionally, we believe that the pseudopod-like extensions of hyperthermia-treated cancer cells must be related to its resistance to hyperthermia.

Thermal Bioprinting Causes Ample Alterations of Expression of LUCAT1, IL6, CCL26, and NRN1L Genes and Massive Phosphorylation of Critical Oncogenic Drug Resistance Pathways in Breast Cancer Cells

Bioprinting technology merges engineering and biological fields and together, they possess a great translational potential, which can tremendously impact the future of regenerative medicine and drug discovery. However, the molecular effects elicited by thermal inkjet bioprinting in breast cancer cells remains elusive. Previous studies have suggested that bioprinting can be used to model tissues for drug discovery and pharmacology. We report viability, apoptosis, phosphorylation, and RNA sequence analysis of bioprinted MCF7 breast cancer cells at separate timepoints post-bioprinting. An Annexin A5-FITC apoptosis stain was used in combination with flow cytometry at 2 and 24 h post-bioprinting. Antibody arrays using a Human phospho-MAPK array kit was performed 24 h post-bioprinting. RNA sequence analysis was conducted in samples collected at 2, 7, and 24 h post-bioprinting. The post-bioprinting cell viability averages were 77 and 76% at 24 h and 48 h, with 31 and 64% apoptotic cells at 2 and 24 h after bioprinting. A total of 21 kinases were phosphorylated in the bioprinted cells and 9 were phosphorylated in the manually seeded controls. The RNA seq analysis in the bioprinted cells identified a total of 12,235 genes, of which 9.7% were significantly differentially expressed. Using a ±2-fold change as the cutoff, 266 upregulated and 206 downregulated genes were observed in the bioprinted cells, with the following 5 genes uniquely expressed NRN1L, LUCAT1, IL6, CCL26, and LOC401585. This suggests that thermal inkjet bioprinting is stimulating large scale gene alterations that could potentially be utilized for drug discovery. Moreover, bioprinting activates key pathways implicated in drug resistance, cell motility, proliferation, survival, and differentiation.

hTERT promotes tumor progression by enhancing TSPAN13 expression in osteosarcoma cells

Telomerase complex maintains the length of the telome, cbre, and protects erosion of the physical ends of the eukaryotic chromosome in all actively dividing cells including cancer cells. Telomerase activation extends the lifespan of cells in culture by maintaining the length of the telomere. Compared to terminally differentiated somatic cells, telomerase activity remains high in over 90% of cancer cells. It has now become clear that the role of telomerase is much more complex than just telomere lengthening. The remaining 10% of cancers deploy ALT (alternative lengthening of telomeres) pathway to maintain telomere length. Telomerase inhibitors offer a good therapeutic option. Also, telomerase-associated molecules can be targeted provided their roles are clearly established. In any case, it is necessary to understand the major role of telomerase in cancer cells. Many studies have already been done to explore gene profiling of a telomerase positive cell by knocking down expression of hTERT (telomerase reverse transcriptase). To complement these studies, we performed global gene profiling of a telomerase negative cell by ectopically expressing hTERT and studied changes in the global gene expression patterns. Analysis of microarray data for telomerase negative cells ectopically expressing telomerase showed 76 differentially regulated genes, out of which 39 genes were upregulated, and 37 were downregulated. Three upregulated genes such as TSPAN13, HMGCS2, DLX5, and three downregulated genes like DHRS2, CRYAB, and PDLIM1 were validated by real-time PCR. Knocking down of TSAPN13 in hTERT overexpressing U2OS cells enhanced the apoptosis of the cells. TSPAN13 knockdown in these cells suppressed mesenchymal properties and enhanced epithelial character.

Identifying subtype-specific associations between gene expression and DNA methylation profiles in breast cancer

BACKGROUND

Breast cancer is a complex disease in which different genomic patterns exists depending on different subtypes. Recent researches present that multiple subtypes of breast cancer occur at different rates, and play a crucial role in planning treatment. To better understand underlying biological mechanisms on breast cancer subtypes, investigating the specific gene regulatory system via different subtypes is desirable.

METHODS

Gene expression, as an intermediate phenotype, is estimated based on methylation profiles to identify the impact of epigenomic features on transcriptomic changes in breast cancer. We propose a kernel weighted l1-regularized regression model to incorporate tumor subtype information and further reveal gene regulations affected by different breast cancer subtypes. For the proper control of subtype-specific estimation, samples from different breast cancer subtype are learned at different rate based on target estimates. Kolmogorov Smirnov test is conducted to determine learning rate of each sample from different subtype.

RESULTS

It is observed that genes that might be sensitive to breast cancer subtype show prediction improvement when estimated using our proposed method. Comparing to a standard method, overall performance is also enhanced by incorporating tumor subtypes. In addition, we identified subtype-specific network structures based on the associations between gene expression and DNA methylation.

CONCLUSIONS

In this study, kernel weighted lasso model is proposed for identifying subtype-specific associations between gene expressions and DNA methylation profiles. Identification of subtype-specific gene expression associated with epigenomic changes might be helpful for better planning treatment and developing new therapies.