Bcl-xL Is a Key Mediator of Apoptosis Following KRASG12C Inhibition in KRASG12C-mutant Colorectal Cancer

Novel covalent inhibitors of KRASG12C have shown limited response rates in patients with KRASG12C-mutant (MT) colorectal cancer. Thus, novel KRASG12C inhibitor combination strategies that can achieve deep and durable responses are needed. Small-molecule KRASG12C inhibitors AZ'1569 and AZ'8037 were used. To identify novel candidate combination strategies for AZ'1569, we performed RNA sequencing, siRNA, and high-throughput drug screening. Top hits were validated in a panel of KRASG12CMT colorectal cancer cells and in vivo. AZ'1569-resistant colorectal cancer cells were generated and characterized. We found that response to AZ'1569 was heterogeneous across the KRASG12CMT models. AZ'1569 was ineffective at inducing apoptosis when used as a single agent or combined with chemotherapy or agents targeting the EGFR/KRAS/AKT axis. Using a systems biology approach, we identified the antiapoptotic BH3-family member BCL2L1/Bcl-xL as a top hit mediating resistance to AZ'1569. Further analyses identified acute increases in the proapoptotic protein BIM following AZ'1569 treatment. ABT-263 (navitoclax), a pharmacologic Bcl-2 family inhibitor that blocks the ability of Bcl-xL to bind and inhibit BIM, led to dramatic and universal apoptosis when combined with AZ'1569. Furthermore, this combination also resulted in dramatically attenuated tumor growth in KRASG12CMT xenografts. Finally, AZ'1569-resistant cells showed amplification of KRASG12C, EphA2/c-MET activation, increased proinflammatory chemokine profile and cross-resistance to several targeted agents. Importantly, KRAS amplification and AZ'1569 resistance were reversible upon drug withdrawal, arguing strongly for the use of drug holidays in the case of KRAS amplification. Taken together, combinatorial targeting of Bcl-xL and KRASG12C is highly effective, suggesting a novel therapeutic strategy for patients with KRASG12CMT colorectal cancer.

Bcl-xL and association with apoptosis following KRASG12C inhibition in KRASG12C mutant colorectal cancer

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Background: Novel covalent inhibitors of KRASG12C have shown modest response rates in KRASG12C mutant (MT) colorectal cancer (CRC) patients. Thus, novel KRASG12C inhibitor combination strategies that can achieve deep and durable responses are needed. Methods: The small molecule KRASG12C inhibitors AZ’1569 and AZ’8037 were employed. To identify novel candidate combination strategies for AZ’1569, we performed RNA sequencing, siRNA and high-throughput drug screening. Top hits were validated in a panel of KRASG12CMT CRC cells and in vivo xenograft models. AZ’1569 acquired resistant CRC models were generated and characterised. Results: Response to AZ’1569 was heterogeneous across the KRASG12CMT models. AZ’1569 was ineffective at inducing apoptosis when used as a single agent or combined with chemotherapy or agents targeting the EGFR/KRAS/AKT axis. Using a systems biology approach, we identified the anti-apoptotic BH3-family member BCL2L1/Bcl-xL as top hit mediating resistance to AZ’1569. Further analyses identified acute increases in the pro-apoptotic protein BIM following AZ’1569 treatment. ABT-263 (Navitoclax), a pharmacological Bcl-2 family-inhibitor that blocks the ability of Bcl-xL to bind and inhibit BIM, led to dramatic and universal apoptosis when combined with AZ’1569 in a panel of KRASG12C MT CRC cells. Furthermore, this combination also resulted in dramatically attenuated tumour growth in KRASG12C MT CRC xenografts. Finally, AZ’1569 acquired resistant KRASG12C MT CRC cells showed amplification of KRASG12C, EphA2/c-MET activation, increased pro-inflammatory chemokine profile and cross-resistance to standard-of-care chemotherapy and several targeted agents. Importantly, the KRAS amplification and AZ’1569-resistance were reversible upon drug withdrawal, arguing strongly for the use of drug holidays in the case of KRAS amplification. Conclusions: Combinatorial targeting of Bcl-xL and KRASG12C is highly effective, suggesting a novel therapeutic strategy for KRAS G12CMT CRC patients. The cross-resistance to other targeted therapies and importantly conventional chemotherapy in the AZ’1569 acquired resistant cells poses a challenge, with implications for the optimal use of KRASG12C inhibitors as a second or third line option.

classifieR a flexible interactive cloud-application for functional annotation of cancer transcriptomes

BACKGROUND

Transcriptionally informed predictions are increasingly important for sub-typing cancer patients, understanding underlying biology and to inform novel treatment strategies. For instance, colorectal cancers (CRCs) can be classified into four CRC consensus molecular subgroups (CMS) or five intrinsic (CRIS) sub-types that have prognostic and predictive value. Breast cancer (BRCA) has five PAM50 molecular subgroups with similar value, and the OncotypeDX test provides transcriptomic based clinically actionable treatment-risk stratification. However, assigning samples to these subtypes and other transcriptionally inferred predictions is time consuming and requires significant bioinformatics experience. There is no "universal" method of using data from diverse assay/sequencing platforms to provide subgroup classification using the established classifier sets of genes (CMS, CRIS, PAM50, OncotypeDX), nor one which in provides additional useful functional annotations such as cellular composition, single-sample Gene Set Enrichment Analysis, or prediction of transcription factor activity.

RESULTS

To address this bottleneck, we developed classifieR, an easy-to-use R-Shiny based web application that supports flexible rapid single sample annotation of transcriptional profiles derived from cancer patient samples form diverse platforms. We demonstrate the utility of the " classifieR" framework to applications focused on the analysis of transcriptional profiles from colorectal (classifieRc) and breast (classifieRb). Samples are annotated with disease relevant transcriptional subgroups (CMS/CRIS sub-types in classifieRc and PAM50/inferred OncotypeDX in classifieRb), estimation of cellular composition using MCP-counter and xCell, single-sample Gene Set Enrichment Analysis (ssGSEA) and transcription factor activity predictions with Discriminant Regulon Expression Analysis (DoRothEA).

CONCLUSIONS

classifieR provides a framework which enables labs without access to a dedicated bioinformation can get information on the molecular makeup of their samples, providing an insight into patient prognosis, druggability and also as a tool for analysis and discovery. Applications are hosted online at https://generatr.qub.ac.uk/app/classifieRc and https://generatr.qub.ac.uk/app/classifieRb after signing up for an account on https://generatr.qub.ac.uk .

Identification of cancer hallmarks associated with benefit in advanced gastroesophageal adenocarcinoma patients treated with checkpoint blockade

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Background: The benefit of checkpoint blockade in advanced gastric cancer is limited and biomarkers related to response are needed. Novel gene expression analysis software was used to identify Hallmarks of Cancer associated with clinical benefit following nivolumab treatment in >2nd line advanced gastroesophageal adenocarcinoma (GEA). Methods: RNA-sequencing data from baseline GEA patient diagnostic tumor samples (103 from NCT02862535; 5 from NCT02862535) were analyzed using the claraT platform (V2.0.0, Almac Diagnostic Services). 62 gene signatures were quantified representing 6 key Hallmarks of Cancer (Avoiding Immune Destruction, Activating Invasion and Metastases, Sustaining Proliferative Signaling, Inducing Angiogenesis, Resisting Cell Death and Genome Instability and Mutation). Clinical benefit (CB) was defined as tumor response or overall survival (OS) > 1 year. HER2 status was from medical records. Survival analyses used cox proportional hazards models. Results: Gene expression signatures (GES) identified 5 molecular subgroups (C1-C5). Rate of CB in each molecular subtype are outlined in Table. C3 and C4 had significantly improved OS compared to C2, (HR = 0.45; p= 0.02 and HR = 0.42; p= 0.02). Greater proportions of HER2+ subjects were present in C4 and C3 vs. C2, with C3 statistically significant (60% vs. 14%; p= 0.012). Gene expression characterized by chromosomal instability (CIN) and homologous recombination repair deficiency (HRD) were associated with HER2(+) (wilcox p= < 0.05). Patients selected by only using CIN & HRD had significant improvement in OS (HR = 0.63; p= 0.03). Conclusions: Interferon-based GES did not predict benefit from immune checkpoint blockade. GES representing HRD and activation of HER2, EGFR and MAPK (each enriched in CIN) were associated with improved survival upon checkpoint blockade in advanced GEA patients. Clinical trial information: NCT02862535 . [Table: see text]

Consensus gene expression analysis to identify key hallmarks of cancer in malignant melanoma

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Background: Traditionally gene expression signatures (GES) are used individually to classify patients into subgroups. Signatures targeting the same biology are often developed independently and may not classify identically. We developed the claraT software tool that uses consensus between multiple published GES categorised by the Hallmarks of Cancer (Hanahan & Weinberg, 2011) to classify cancers. As metastatic melanoma represents poor prognostic disease (5-yr survival 15-20%), we applied claraT to the TCGA melanoma dataset to identify targetable biologies, validated in a cohort of melanoma patients treated with Ipilimumab. Methods: TCGA RNA-seq data ( n= 472) was analysed using the claraT platform including GES for immune ( n= 14), angiogenesis ( n= 9) and epithelial-mesenchymal transition (EMT) ( n= 12) Hallmarks. Samples were clustered for the combined and individual Hallmarks. Median progression-free (PFS) and overall-survival (OS) differences were analysed across identified subgroups. Analysis was validated in an Ipilimumab treated melanoma dataset ( n= 42) (Van Allen, 2015). Results: Clustering the combined Hallmarks identified 4 subgroups in the TCGA cohort: 1) Immune active, 2) Immune-EMT active, 3) EMT-Angiogenesis active, 4) All inactive. Groups 1&2 had significantly improved OS compared to Groups 3&4 (HR = 0.50, p< 0.0001). Clustering using single Hallmarks revealed that immune-positive tumours had significantly improved OS (HR = 0.53, p< 0.0001) compared to immune-negative tumours. Angiogenesis-negative tumours displayed improved PFS (HR = 0.73, p= 0.03) and OS (HR = 0.53, p <0.0001) compared to angiogenesis-negative tumours. Interestingly the EMT Hallmark was not found to be individually prognostic. When validated in the Ipilimumab treated dataset, patients classified as immune-positive had improved OS (HR = 0.357, p= 0.010) when compared to immune-negative. Similar trends were also observed for angiogenesis and EMT Hallmarks. Conclusions: This study demonstrates how simultaneous analysis of multiple GES ( n= 35 in this study) can identify robust biologies through consensus expression. This platform may have value in the identification of reliable biomarkers for clinical trials and could inform how combination therapies targeting key biologies may be used in cancer treatment.

Ectopic expression of alkaline phosphatase in proximal tubular brush border membrane of human renal cell carcinoma

The present study was conducted to find out any alteration in the expression and activity of alkaline phosphatase in the brush border membrane (BBM) from renal cell carcinoma (RCC) in comparison to normal renal BBM. The specific activity of alkaline phosphatase was drastically reduced in homogenate as well as BBM from RCC kidney when compared to ALP activity in BBM of normal kidney. Kinetic studies revealed that diminished activity of alkaline phosphatase in BBM isolated from RCC was fraternized with decrease in maximal velocity (V(max)) and increase in affinity constant (K(m)) of the enzyme. SDS-PAGE studies showed that the BBM proteins having molecular weights ranging from 95 to 170 kDa were poorly expressed in RCC BBM in relative to normal kidney BBM. Incubation of SDS-PAGE gel with BCIP/NBT dye clearly showed that the expression of ALP in tumor renal BBM was markedly reduced as compared to normal kidney. Further, Western blot analysis using anti-alkaline phosphatase antibody also confirmed the reduced expression of ALP in tumor renal BBM. Lipid composition in reference to phospholipids, glycolipids and cholesterol in tumor renal BBM was altered to that of normal renal BBM, indicating alteration in membrane fluidity of tumor renal BBM.