Identification, validation and biological characterisation of novel glioblastoma tumour microenvironment subtypes: implications for precision immunotherapy

BACKGROUND

New precision medicine therapies are urgently required for glioblastoma (GBM). However, to date, efforts to subtype patients based on molecular profiles have failed to direct treatment strategies. We hypothesised that interrogation of the GBM tumour microenvironment (TME) and identification of novel TME-specific subtypes could inform new precision immunotherapy treatment strategies.

MATERIALS AND METHODS

A refined and validated microenvironment cell population (MCP) counter method was applied to >800 GBM patient tumours (GBM-MCP-counter). Specifically, partition around medoids (PAM) clustering of GBM-MCP-counter scores in the GLIOTRAIN discovery cohort identified three novel patient clusters, uniquely characterised by TME composition, functional orientation markers and immune checkpoint proteins. Validation was carried out in three independent GBM-RNA-seq datasets. Neoantigen, mutational and gene ontology analysis identified mutations and uniquely altered pathways across subtypes. The longitudinal Glioma Longitudinal AnalySiS (GLASS) cohort and three immunotherapy clinical trial cohorts [treatment with neoadjuvant/adjuvant anti-programmed cell death protein 1 (PD-1) or PSVRIPO] were further interrogated to assess subtype alterations between primary and recurrent tumours and to assess the utility of TME classifiers as immunotherapy biomarkers.

RESULTS

TME^High tumours (30%) displayed elevated lymphocyte, myeloid cell immune checkpoint, programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 transcripts. TME^High/mesenchymal+ patients featured tertiary lymphoid structures. TME^Med (46%) tumours were enriched for endothelial cell gene expression profiles and displayed heterogeneous immune populations. TME^Low (24%) tumours were manifest as an 'immune-desert' group. TME subtype transitions upon recurrence were identified in the longitudinal GLASS cohort. Assessment of GBM immunotherapy trial datasets revealed that TME^High patients receiving neoadjuvant anti-PD-1 had significantly increased overall survival (P = 0.04). Moreover, TME^High patients treated with adjuvant anti-PD-1 or oncolytic virus (PVSRIPO) showed a trend towards improved survival.

CONCLUSIONS

We have established a novel TME-based classification system for application in intracranial malignancies. TME subtypes represent canonical 'termini a quo' (starting points) to support an improved precision immunotherapy treatment approach.

High levels of X-linked Inhibitor-of-Apoptosis Protein (XIAP) are indicative of radio chemotherapy resistance in rectal cancer

BACKGROUND

The mainstay of treatment in rectal cancer is neoadjuvant radio chemotherapy prior to surgery, in an attempt to downstage the tumour, allowing for more complete removal during surgery. In 40 % of cases however, this neoadjuvant radio chemotherapy fails to achieve tumour regression, partly due insufficient apoptosis signaling. X-linked Inhibitor of Apoptosis Protein (XIAP) is an anti-apoptotic protein that has been reported to contribute to disease progression and chemotherapy resistance.

METHODS

We obtained rectal biopsy normal and matched tumour tissue from 29 rectal cancer patients with varying degrees of tumour regression, and using Western blot, examined anti-apoptotic XIAP and pro-apoptotic Smac protein levels in these tissues, with the aim to examine whether disturbed XIAP/Smac levels may be an indicator of neoadjuvant radio chemotherapy resistance. Expression of inhibitor of apoptosis proteins cIAP-1 and cIAP-2 was also examined.

RESULTS

We found that levels of XIAP increased in accordance with the degree of radio chemotherapy resistance of the tissue. Levels of this protein were also significantly higher in tumour tissue, compared to matched normal tissue in highly resistant tissue. In contrast, Smac protein levels did not increase with radio chemotherapy resistance, and the protein was similarly expressed in normal and tumour tissue, indicating a shift in the balance of these proteins. Post treatment surgical resection tissue was available for 8 patients. When we compared matched tissue pre- and post- radio chemotherapy we found that XIAP levels increased significantly during treatment in both normal and tumour tissue, while Smac levels did not change. cIAP-1 and cIAP-2 levels were not differentially expressed in varying degrees of radio chemotherapy resistance, and neoadjuvant therapy did not alter expression of these proteins.

CONCLUSION

These data indicate that disturbance of the XIAP/Smac balance may be a driver of radio chemotherapy resistance, and hence high levels of XIAP may be a useful indicator of neoadjuvant radio chemotherapy resistance in rectal cancer. Moreover, as XIAP levels increase with radio chemotherapy it is possible that a subset of more resistant tumour cells survive this treatment and may be resistant to further adjuvant treatment. Patients with resistant tumours highly expressing XIAP may benefit from alternative treatment strategies, such as Smac mimetics post neoadjuvant radio chemotherapy.

BCL2 protein signalling determines acute responses to neoadjuvant chemoradiotherapy in rectal cancer

In locally advanced rectal cancer, neoadjuvant chemoradiotherapy is performed prior to surgery to downstage the tumour. Thirty to 40 % of patients do not respond. Defects in apoptotic machinery lead to therapy resistance; however, to date, no study quantitatively assessed whether B cell lymphoma 2 (BCL2)-dependent regulation of mitochondrial apoptosis, effector caspase activation downstream of mitochondria or a combination of both predicts patient responses. In a cohort of 20 rectal cancer patients, we performed protein profiling of tumour tissue and employed validated ordinary differential equation-based systems models of apoptosis signalling to calculate the ability of cancer cells to undergo apoptosis. Model outputs were compared to clinical responses. Systems modelling of BCL2-signalling predicted patients in the poor response group (p = 0.0049). Systems modelling also demonstrated that rectal cancers depended on BCL2 rather than B cell lymphoma-extra large (BCL(X)L) or myeloid cell leukemia 1 (MCL1) for survival, suggesting that poor responders may benefit from therapy with selective BCL2 antagonists. Dynamic modelling of effector caspase activation could not stratify patients with poor response and did not further improve predictive power. We deliver a powerful patient stratification tool identifying patients who will likely not benefit from neoadjuvant chemoradiotherapy and should be prioritised for surgical resection or treatment with BCL2 antagonists.

KEY MESSAGES

Modelling BCL2-family proteins identifies patients unresponsive to therapy. Caspase activation downstream of mitochondria cannot identify these patients. Rectal tumours of poor responders are BCL2- but not BCL-XL-dependent. DR_MOMP allows clinicians to identify patients who would not benefit from therapy. DR_MOMP is also a useful patient stratification tool for BCL2 antagonists.