Abstract Confounding effects of specific KRAS gene alterations on colorectal cancer (CRC) prognosis stratified by microsatellite instability (MSI) and BRAF V600E have not yet been investigated. The aim of our study was to evaluate the combined effects of MSI, BRAF V600E and specific KRAS mutation (Gly → Asp; G12D, Gly → Asp, G13D; Gly → Val; G12V) on prognosis in 404 sporadic and 94 hereditary CRC patients. MSI status was determined according to the Bethesda guidelines. Mutational status of KRAS and BRAF V600E was assessed by direct DNA sequencing. In sporadic CRC, KRAS G12D mutations had a negative prognostic effect compared to G13D and wild‐type cancers ( p = 0.038). With MSI, specific KRAS and BRAF V600E mutations, 3 distinct prognostic subgroups were observed in univariate ( p = 0.006) and multivariable ( p = 0.051) analysis: patients with ( i ) KRAS mutation G12D, G12V or BRAF V600E mutation, ( ii ) KRAS / BRAF V600E wild‐type or KRAS G13D mutations in MSS/MSI‐L and ( iii ) MSI‐H and KRAS G13D mutations. Moreover, none of the sporadic MSI‐H or hereditary patients with KRAS G13 mutations had a fatal outcome. Specific KRAS mutation is an informative prognostic factor in both sporadic and hereditary CRC and applied in an algorithm with BRAF V600E and MSI may identify sporadic CRC patients with poor clinical outcome.
Abstract Treatment of glioblastoma multiforme (GBM), the most aggressive form of primary brain cancer, has essentially not advanced over the past few decades. Numerous challenges hinder the successful development of new therapies, including drug delivery across the blood-brain barrier (BBB), the complexity of the tumor microenvironment (TME), and the lack of clinically predictive cancer models. Here, we present the results of an image-based ex vivo drug-testing platform that addresses these therapeutic roadblocks. To demonstrate the clinical utility of our platform, in a retrospective cohort of 14 GBM patients, we show that ex vivo sensitivity to Temozolomide (TMZ, 1st-line GBM chemotherapy), is associated with longer progression free survival (PFS) and overall survival (OS). Next, by screening 150 clinically approved drugs across 27 GBM surgical patient samples, we identify a set of BBB-permeable neuroactive drugs with anti-glioma activity. These neurological drugs display remarkably consistent on-target killing of cancer cells with minimal toxicity to non-malignant TME cells across both primary and recurrent GBM samples. Single-cell transcriptional profiling of GBM patient samples and functional genetics reveals novel glioma-dependencies on neurological drug-target expression. Furthermore, a drug-target network enrichment analysis uncovers an AP1/BTG/TP53 gene signature associated with the anti-glioma activity of neurological drugs. In silico screening of over 1 million compounds for this common gene signature identified additional drug hits that could be validated in patient samples with 90% accuracy. Multiplexed transcriptomics revealed AP-1 transcription factor family activation to be the common underlying feature of neurological drugs with anti-glioma activity. Among the most promising candidate drugs, we identify the atypical antidepressant Vortioxetine as the strongest inducer of this gene signature, and confirm its efficacy in vivo across multiple mouse models. Vortioxetine in combination with Temozolomide or Lomustine further increased median survival in vivo compared to single agents alone. This study thus provides a clinically predictive and personalized drug-testing platform that identifies new treatment opportunities for GBM, warranting further investigation. Citation Format: Sohyon Lee, Tobias Weiss, Marcel Bühler, Rebekka Wegmann, Julien Mena, Michel Bihl, Sandra Goetze, Audrey van Drogen, Elisabeth J. Rushing, Bernd Wollscheid, Michael Weller, Berend Snijder. Image-based functional precision medicine for repurposing neuroactive drugs in glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5325.
Introduction: Colorectal carcinoma (CRC) is among the most common carcinomas in women and men. In the advanced stage, patients are treated based on the RAS status. Recent studies indicate that in the future, in addition to KRAS and NRAS, alterations in other genes, such as PIK3CA or TP53, will be considered for therapy. Therefore, it is important to know the mutational landscape of routinely diagnosed CRC. Method: We report the molecular profile of 512 Swiss CRC patients analyzed by targeted next-generation sequencing as part of routine diagnostics at our institute. Results: Pathogenic and likely pathogenic variants were found in 462 (90%) CRC patients. Variants were detected in TP53 (54.3%), KRAS (48.2%), PIK3CA (15.6%), BRAF (13.5%), SMAD4 (10.5%), FBXW7 (7.8%), NRAS (3.5%), PTEN (2.7%), ERBB2 (1.6%), AKT1 (1.5%), and CTNNB1 (0.9%). The remaining pathogenic alterations were found in the genes ATM(n= 1), MAP2K1(n= 1), and IDH2(n= 1). Discussion/Conclusions: Our analysis revealed the prevalence of potential predictive markers in a large cohort of CRC patients obtained during routine diagnostic analysis. Furthermore, our study is the first of this size to uncover the molecular landscape of CRC in Switzerland.
Our aim was to investigate the prognostic and predictive value of the oncogenic MAPKK-like protein T-cell-originated protein kinase (TOPK) stratified by KRAS and BRAF mutations in patients with sporadic, hereditary and metastatic colorectal cancer (CRC) treated with anti-EGFR therapy.Immunohistochemistry (IHC) for TOPK was performed on four study groups. Group 1 included two subgroups of 543 and 501 sporadic CRC patients used to test the reliability of TOPK expression by IHC. In Group 2, representing an additional 222 sporadic CRCs, the prognostic effect of TOPK stratified by KRAS and BRAF was assessed. The prognostic effect of TOPK was further analysed in Group 3, representing 71 hereditary Lynch syndrome-associated CRC patients. In Group 4, the predictive and prognostic value of TOPK was analysed on 45 metastatic patients treated with cetuximab or panitumumab stratified by KRAS and BRAF gene status.In both sporadic CRC subgroups (Group 1), associations of diffuse TOPK expression with clinicopathological features were reproducible. Molecular analysis of sporadic CRCs in Group 2 showed that diffuse TOPK expression was associated with KRAS and BRAF mutations (p<0.001) and with poor outcome in patients with either mutation in univariate and multivariate analysis (P=0.017). In hereditary patients (Group 3), diffuse TOPK was linked to advanced pT stage. In metastatic patients treated with anti-EGFR therapy (Group 4), diffuse TOPK expression was linked to dismal outcome despite objective response to treatment (P=0.01).TOPK expression is an unfavourable prognostic indicator in sporadic patients with KRAS or BRAF mutations and also in patients with metastatic disease experiencing a response to anti-EGFR therapies. The inhibition of TOPK, which could benefit 30-40% of CRC patients, may represent a new avenue of investigation for targeted therapy.
Introduction: Colorectal carcinoma (CRC) is among the most common carcinomas in women and men. In the advanced stage, patients are treated based on the RAS status. Recent studies indicate that in the future, in addition to KRAS and NRAS, alterations in other genes, such as PIK3CA or TP53, will be considered for therapy. Therefore, it is important to know the mutational landscape of routinely diagnosed CRC. Method: We report the molecular profile of 512 Swiss CRC patients analyzed by targeted next-generation sequencing as part of routine diagnostics at our institute. Results: Pathogenic and likely pathogenic variants were found in 462 (90%) CRC patients. Variants were detected in TP53 (54.3%), KRAS (48.2%), PIK3CA (15.6%), BRAF (13.5%), SMAD4 (10.5%), FBXW7 (7.8%), NRAS (3.5%), PTEN (2.7%), ERBB2 (1.6%), AKT1 (1.5%), and CTNNB1 (0.9%). The remaining pathogenic alterations were found in the genes ATM(n= 1), MAP2K1(n= 1), and IDH2(n= 1). Discussion/Conclusions: Our analysis revealed the prevalence of potential predictive markers in a large cohort of CRC patients obtained during routine diagnostic analysis. Furthermore, our study is the first of this size to uncover the molecular landscape of CRC in Switzerland.
HOX genes control normal development, primary cellular processes and are characterized by a unique genomic network organization. Locus D HOX genes play an important role in limb generation and mesenchymal condensation. Dysregulated HOXD13 expression has been detected in breast cancer, melanoma, cervical cancer and astrocytomas. We have investigated the epidemiology of HOXD13 expression in human tissues and its potential deregulation in the carcinogenesis of specific tumors. HOXD13 homeoprotein expression has been detected using microarray technology comprising more than 4,000 normal and neoplastic tissue samples including 79 different tumor categories. Validation of HOXD13 expression has been performed, at mRNA level, for selected tumor types. Significant differences are detectable between specific normal tissues and corresponding tumor types with the majority of cancers showing an increase in HOXD13 expression (16.1% normal vs. 57.7% cancers). In contrast, pancreas and stomach tumor subtypes display the opposite trend. Interestingly, detection of the HOXD13 homeoprotein in pancreas-tissue microarrays shows that its negative expression has a significant and adverse effect on the prognosis of patients with pancreatic cancer independent of the T or N stage at the time of diagnosis. Our study provides, for the first time, an overview of a HOX protein expression in a large series of normal and neoplastic tissue types, identifies pancreatic cancer as one of the most affected by the HOXD13 hoemoprotein and underlines the way homeoproteins can be associated to human cancerogenesis.
Abstract Background A recent publication described a supervised classification method for microarray data: Between Group Analysis (BGA). This method which is based on performing multivariate ordination of groups proved to be very efficient for both classification of samples into pre-defined groups and disease class prediction of new unknown samples. Classification and prediction with BGA are classically performed using the whole set of genes and no variable selection is required. We hypothesize that an optimized selection of highly discriminating genes might improve the prediction power of BGA. Results We propose an optimized between-group classification (OBC) which uses a jackknife-based gene selection procedure. OBC emphasizes classification accuracy rather than feature selection. OBC is a backward optimization procedure that maximizes the percentage of between group inertia by removing the least influential genes one by one from the analysis. This selects a subset of highly discriminative genes which optimize disease class prediction. We apply OBC to four datasets and compared it to other classification methods. Conclusion OBC considerably improved the classification and predictive accuracy of BGA, when assessed using independent data sets and leave-one-out cross-validation. Availability The R code is freely available [see Additional file 1] as well as supplementary information [see Additional file 2].
