glioblastoma Archives | Mikhail Blagosklonny Oncotarget

In this research perspective, researchers discuss causal and correlative approaches to identify potential biomarkers for predicting paclitaxel response.

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Cancer therapy has come a long way from its one-size-fits-all beginning to the awakening era of personalized medicine. This change has been largely driven by the discovery of biomarkers. Biomarkers can help refine patient selection for specific therapies. A blend of causal and correlative approaches is needed to elucidate the full potential of biomarkers in cancer research. This fusion of methodologies allows for a comprehensive exploration of biomarker efficacy, leading to more accurate predictions of drug response.

In a new paper, researchers Alberto Moscona-Nissan, Karl J. Habashy, Victor A. Arrieta, Adam M. Sonabend, and Crismita Dmello from the Universidad Panamericana School of Medicine, Northwestern University and Universidad Nacional Autónoma de México discuss causal and correlative approaches to identify potential biomarkers for predicting response to paclitaxel — a commonly used chemotherapeutic agent. On February 8, 2024, their research perspective was published in Oncotarget’s Volume 15, entitled, “Combining causal and correlative approaches to discover biomarkers of response to paclitaxel.”

“[…] studying the combination of non-overlapping biomarkers’ expression, in addition to clinical and sociodemographic data could generate predictive models for paclitaxel susceptibility.”

Combining Causal and Correlative Approaches

Paclitaxel is a mainstay of treatment for various cancers, including breast, pancreatic, ovarian, and non-small cell lung carcinomas. However, the benefit derived from paclitaxel treatment varies across patients, and a significant proportion does not receive therapeutic benefit and experiences unnecessary toxicity. The variability in response to paclitaxel underscores the need for predictive biomarkers. Predictive biomarkers of response to paclitaxel can lead to improved treatment efficacy, less unnecessary toxicity, and potentially better health outcomes.

In a recent study, researchers used a whole-genome CRISPR/Cas9 knockout to identify genes that influence paclitaxel susceptibility in gliomas. They identified 51 genes that have implications in pathways such as NFkB, toll-like receptor, and MAPK signaling, transcriptional misregulation, and apoptosis. The team also identified the signal sequence receptor 3 (SSR3) gene as a predictive biomarker for paclitaxel susceptibility.

The SSR3 gene encodes the gamma subunit of the signal sequence receptor (SSR) complex, a glycosylated membrane receptor located at the endoplasmic reticulum (ER). This complex is involved in protein translocation across the ER membrane. In the study, it was found that higher SSR3 expression correlated with increased paclitaxel susceptibility in cancer cell lines. SSR3 knockout cells showed decreased susceptibility to paclitaxel, while cells overexpressing SSR3 had increased susceptibility.

The study also revealed a link between SSR3 and the unfolded protein response (UPR) pathway, which reduces the amount of unfolded proteins in the cell under stressful conditions. A positive correlation was found between SSR3 expression and IRE1a levels in glioma PDX cells. IRE1a is a serine/threonine kinase that is involved in the UPR pathway and has been implicated in various disorders.

Conclusions & Future Directions

A significant challenge in the treatment of glioblastoma is the blood-brain barrier which limits the efficacy of paclitaxel. However, innovative strategies like convection-enhanced delivery, biodegradable wafers, peptide-drug conjugates, and low-intensity pulsed ultrasound administered with microbubbles are being developed to overcome this barrier.

The researchers also wrote in their research perspective that, after identifying a potential predictive biomarker in a training cohort of patients, it is vital to validate the finding in an independent cohort. The correlation between patients’ overall survival and SSR3 expression is currently being studied in a phase 2 trial at Northwestern University. Based on the outcomes of these validations, the predictive models can be further refined by incorporating other non-overlapping histologic and molecular biomarkers along with patient demographics. The discovery of predictive biomarkers for paclitaxel response, such as SSR3, promises to significantly impact cancer treatment.

“Precision and personalized medicine can lead to a transition from a stochastic treatment response into predictable scenarios. Further identification of predictive biomarkers, validation, and study of combinations as predictive models is critical to generate a greater impact that can be translated to the bedside of patients.”

Click here to read the full research paper in Oncotarget.

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In a new study, researchers investigated the activity of gartisertib, a potent ATR inhibitor, alone and in combination with standard therapy in multiple glioblastoma cell lines.

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Glioblastoma is a type of brain cancer that is very aggressive and difficult to treat. The current standard treatment involves surgery, radiation therapy, and chemotherapy with a drug called temozolomide (TMZ). However, many glioblastoma cells can resist the DNA-damaging effects of TMZ and radiation by activating a mechanism called the DNA damage response (DDR). This mechanism, while beneficial in normal cells, is detrimental to cancer therapy because it allows cancer cells to repair damage and continue to grow and divide. There is a need to counteract this mechanism in glioblastoma cancer cells.

In a new study, researchers Mathew Lozinski, Nikola A. Bowden, Moira C. Graves, Michael Fay, Bryan W. Day, Brett W. Stringer, and Paul A. Tooney from University of Newcastle, Hunter Medical Research Institute, GenesisCare, QIMR Berghofer Medical Research Institute, and Griffith University found that a drug called gartisertib may overcome this resistance by inhibiting a key protein involved in the DDR, called ataxia-telangiectasia and Rad3-Related protein (ATR). On January 16, 2024, the researchers published their new research paper in Oncotarget’s Volume 15, entitled, “ATR inhibition using gartisertib enhances cell death and synergises with temozolomide and radiation in patient-derived glioblastoma cell lines.”

“Here, we investigated the activity of gartisertib, a potent ATR inhibitor, alone and in combination with TMZ and/or RT in 12 patient-derived glioblastoma cell lines.”

The Study

In this study, the team tested the effects of gartisertib alone and in combination with TMZ and radiation in 12 patient-derived glioblastoma cell lines. They found that gartisertib alone reduced the viability of glioblastoma cells, and that the sensitivity was associated with the frequency of DDR mutations and the expression of genes involved in the G2 phase of the cell cycle (the phase where cells prepare for division and check for DNA damage). The researchers also found that gartisertib enhanced the cell death induced by TMZ and radiation, and that the combination was more synergistic than TMZ and radiation alone.

Interestingly, gartisertib was more effective in glioblastoma cells that had unmethylated MGMT promoters and were resistant to TMZ and radiation. (MGMT is a gene that encodes an enzyme that can reverse the damage caused by TMZ, and its promoter is a region that controls its expression. Methylation is a chemical modification that can silence genes, so unmethylated MGMT promoters mean higher MGMT expression and more resistance to TMZ.) The researchers also analyzed the gene expression changes in glioblastoma cells treated with gartisertib, and found that the drug upregulated pathways related to the innate immune system. The researchers speculated that gartisertib may trigger an immune response against glioblastoma cells, which could enhance the anti-tumor effects of the drug.

“We showed that gartisertib alone potently reduced the cell viability of glioblastoma cell lines, where sensitivity was associated with the frequency of DDR mutations and higher expression of the G2 cell cycle pathway. ATR inhibition significantly enhanced cell death in combination with TMZ and RT and was shown to have higher synergy than TMZ+RT treatment. MGMT promoter unmethylated and TMZ+RT resistant glioblastoma cells were also more sensitive to gartisertib. Analysis of gene expression from gartisertib treated glioblastoma cells identified the upregulation of innate immune-related pathways.”

Conclusion

The study is the first to demonstrate the activity of gartisertib in patient-derived glioblastoma cell lines, and it provides evidence that ATR inhibition may be a promising strategy to improve the outcomes of glioblastoma patients. Gartisertib is a potent and selective inhibitor of ATR that has been tested in a phase 1 clinical trial for patients with advanced solid tumors. The researchers suggest that further studies are needed to evaluate the safety and efficacy of gartisertib in combination with TMZ and radiation in glioblastoma patients, and to explore the potential role of the immune system in mediating the anti-tumor effects of the drug.

“In conclusion, this study identifies gartisertib as a potent ATRi within patient-derived glioblastoma cell lines. […] Further investigation of the concept of ATR inhibition for treatment of brain tumours, especially in vivo with brain penetrant compounds, is needed to validate these findings. Lastly, ATR inhibition alters the gene expression of innate immune and inflammatory signalling pathways within glioblastoma cells, which requires additional validation and investigation as a strategy to provoke an immunomodulatory response.”

Click here to read the full research paper in Oncotarget.

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Tagged: glioblastoma

Identifying Biomarkers for Predicting Paclitaxel Response

Combining Causal and Correlative Approaches

Conclusions & Future Directions