Consensus molecular subtype transition during progression of colorectal cancer.

The consensus molecular subtype (CMS) classification divides colorectal cancer (CRC) into four distinct subtypes based on RNA expression profiles. The biological differences between CMSs are already present in CRC precursor lesions, but not all CMSs pose the same risk of malignant transformation. To fully understand the path to malignant transformation and to determine whether CMS is a fixed entity during progression, genomic and transcriptomic data from two regions of the same CRC lesion were compared: the precursor region and the carcinoma region. In total, 24 patients who underwent endoscopic removal of T1-2 CRC were included. Regions were subtyped for CMS and DNA mutation analysis was performed. Additionally, a set of 85 benign adenomas was CMS-subtyped. This analysis revealed that almost all benign adenomas were classified as CMS3 (91.8%). In contrast, CMS2 was the most prevalent subtype in precursor regions (66.7%), followed by CMS3 (29.2%). CMS4 was absent in precursor lesions and originated at the carcinoma stage. Importantly, CMS switching occurred in a substantial number of cases and almost all (six out of seven) CMS3 precursor regions showed a shift to a different subtype in the carcinoma part of the lesion, which in four cases was classified as CMS4. In conclusion, our data indicate that CMS3 is related to a more indolent type of precursor lesion that less likely progresses to CRC and when this occurs, it is often associated with a subtype change that includes the more aggressive mesenchymal CMS4. In contrast, an acquired CMS2 signature appeared to be rather fixed during early CRC development. Combined, our data show that subtype changes occur during progression and that CMS3 switching is related to changes in the genomic background through acquisition of a novel driver mutation (TP53) or selective expansion of a clone, but also occurred independently of such genetic changes. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

What's new in WHO fifth edition - urinary tract.

The fifth edition of the WHO Blue Book on urological tumours, specifically in the bladder chapter, represents a refinement and update in the classification of bladder tumours building on the aggregate major changes made in previous editions. Progress in the molecular underpinnings of urothelial tumours, particularly with promising stratifiers for more precision-based treatment approaches, have been made. Special attention has been paid to burning questions in bladder pathology, such as grading, heterogeneous lesions, inverted tumours and substaging. The concept of neuroendocrine tumours will be explained precisely.

Can molecular stratification improve the treatment of inflammatory bowel disease?

Inflammatory bowel disease (IBD) is a debilitating chronic inflammatory disease of the gastrointestinal (GI) tract. It affects more than 3.5 million people in the western world and places a huge financial burden on healthcare systems. IBD is highly heterogeneous; disease severity and outcomes in IBD are highly variable, and patients may experience episodes of relapse and remission. However, treatment often follows a step-up model whereby the patients start with anti-inflammatory agents (corticosteroids or immunosuppressants) and step-up to monoclonal anti-tumour necrosis factor-α (TNFα) antibodies and then other biologics if the initial drugs cannot control disease. Unfortunately, many patients do not respond to the costly biologics, and thus often still require gut-resective surgery, which decreases quality of life. In order to decrease rates of surgery and ineffective treatments, it is important to identify markers that accurately predict disease progression and treatment responses, to inform decisions about the best choice of therapeutics. Here we examine molecular approaches to patient stratification that aim to increase the effectiveness of treatments and potentially reduce healthcare costs. In the future, it may become possible to stratify patients based on their suitability for specific molecular-targeted therapeutic agents, and eventually use molecular stratification for personalised medicine in IBD.

Prospective patient stratification into robust cancer-cell intrinsic subtypes from colorectal cancer biopsies.

Colorectal cancer (CRC) biopsies underpin accurate diagnosis, but are also relevant for patient stratification in molecularly-guided clinical trials. The consensus molecular subtypes (CMSs) and colorectal cancer intrinsic subtypes (CRISs) transcriptional signatures have potential clinical utility for improving prognostic/predictive patient assignment. However, their ability to provide robust classification, particularly in pretreatment biopsies from multiple regions or at different time points, remains untested. In this study, we undertook a comprehensive assessment of the robustness of CRC transcriptional signatures, including CRIS and CMS, using a range of tumour sampling methodologies currently employed in clinical and translational research. These include analyses using (i) laser-capture microdissected CRC tissue, (ii) eight publically available rectal cancer biopsy data sets (n = 543), (iii) serial biopsies (from AXEBeam trial, NCT00828672; n = 10), (iv) multi-regional biopsies from colon tumours (n = 29 biopsies, n = 7 tumours), and (v) pretreatment biopsies from the phase II rectal cancer trial COPERNCIUS (NCT01263171; n = 44). Compared to previous results obtained using CRC resection material, we demonstrate that CMS classification in biopsy tissue is significantly less capable of reliably classifying patient subtype (43% unknown in biopsy versus 13% unknown in resections, p = 0.0001). In contrast, there was no significant difference in classification rate between biopsies and resections when using the CRIS classifier. Additionally, we demonstrated that CRIS provides significantly better spatially- and temporally- robust classification of molecular subtypes in CRC primary tumour tissue compared to CMS (p = 0.003 and p = 0.02, respectively). These findings have potential to inform ongoing biopsy-based patient stratification in CRC, enabling robust and stable assignment of patients into clinically-informative arms of prospective multi-arm, multi-stage clinical trials. © 2018 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Microsatellite instability in gastric cancer: molecular bases, clinical perspectives, and new treatment approaches.

Gastric cancer is one of the most aggressive malignancies, with limited treatment options in both locally advanced and metastatic setting, resulting in poor prognosis. Based on genomic characterization, stomach tumour has recently been described as a heterogeneous disease composed by different subtypes, each of them with peculiar molecular aspects and specific clinical behaviour. With an incidence of 22% among all western gastric tumour cases, stomach cancer with microsatellite instability was identified as one of these subgroups. Retrospective studies and limited prospective trials reported differences between gastric cancers with microsatellite stability and those with instability, mainly concerning clinical and pathological features, but also in regard to immunological microenvironment, correlation with prognostic value, and responses to treatment. In particular, gastric cancer with microsatellite instability constitutes a small but relevant subgroup associated with older age, female sex, distal stomach location, and lower number of lymph-node metastases. Emerging data attribute to microsatellite instability status a favourable prognostic meaning, whereas the poor outcomes reported after perioperative chemotherapy administration suggest a detrimental role of cytotoxic drugs in this gastric cancer subgroup. The strong immunogenicity and the widespread expression of immune-checkpoint ligands make microsatellite instability subtype more vulnerable to immunotherapeutic approach, e.g., with anti-PD-L1 and anti-CTLA4 antibodies. Since gastric cancer with microsatellite instability shows specific features and clinical behaviour not overlapping with microsatellite stable disease, microsatellite instability test might be suitable for inclusion in a diagnostic setting for all tumour stages to guarantee the most targeted and effective treatment to every patient.

Reverse phase protein arrays enable glioblastoma molecular subtyping.

In the present study we investigated the phosphorylation status of the 12 most important signaling cascades in glioblastomas. More than 60 tumor and control biopsies from tumor center and periphery (based on neuronavigation) were subjected to selective protein expression analysis using reverse-phase protein arrays (RPPA) incubated with antibodies against posttranslationally modified cancer pathway proteins. The ratio between phosphorylated (or modified) and non-phosphorylated protein was assessed. All samples were histopathologically validated and proteomic profiles correlated with clinical and survival data. By RPPA, we identified three distinct activation patterns within glioblastoma defined by the ratios of pCREB1/CREB1, NOTCH-ICD/NOTCH1, and pGSK3ß/GSK3ß, respectively. These subclasses demonstrated distinct overall survival patterns in a cohort of patients from a single-institution and in an analysis of publicly available data. In particular, a high pGSK3ß/GSK3ß-ratio was associated with a poor survival. Wnt-activation/GSK3ß-inhibition in U373 and U251 cell lines halted glioma cell proliferation and migration. Gene expression analysis was used as an internal quality control of baseline proteomic data. The protein expression and phosphorylation had a higher resolution, resulting in a better class-subdivision than mRNA based stratification data. Patients with different proteomic profiles from multiple biopsies showed a worse overall survival. The CREB1-, NOTCH1-, GSK3ß-phosphorylation status correlated with glioma grades. RPPA represent a fast and reliable tool to supplement morphological diagnosis with pathway-specific information in individual tumors. These data can be exploited for molecular stratification and possible combinatorial treatment planning. Further, our results may optimize current glioma grading algorithms.

[Personalized oncology]. / Personalisierte Onkologie.

CLINICAL ISSUE: Innovative next generation sequencing (NGS) technologies and comprehensive sequencing investigations in large patient cohorts have paved the way for very promising personalized treatment strategies based on the molecular characteristics of individual tumors. STANDARD TREATMENT: Targeted therapies, such as tyrosine kinase inhibitors, antibodies and modern immunotherapeutic approaches are well established as monotherapy and combination therapy for many hematological and oncological malignancies. TREATMENT INNOVATIONS: A plethora of innovative therapies targeting various components of intracellular signaling cascades and effective mechanisms against oncogenes as well as the availability of NGS technologies enable personalized cancer treatment based on the molecular profiles of individual tumors and genetic stratification, within clinical trials. DIAGNOSTIC WORK-UP: Comprehensive genetic approaches including cancer gene panel sequencing, whole exome, whole genome and transcriptome sequencing are carried out to a varying extent and particularly in the academic setting. PERFORMANCE: Principally, a comprehensive characterization of tumors in addition to DNA and RNA sequencing that also incorporates epigenetic, metabolomic, and proteomic alterations would be desirable. A comprehensive clinical implementation of integrative, multidimensional genetic typing is, however, currently not possible. ACHIEVEMENTS: It remains to be demonstrated whether these approaches will translate into significantly better outcomes for patients and whether they can be increasingly implemented in the routine diagnostic work-up. PRACTICAL RECOMMENDATIONS: The selection of diagnostic tools in individual cases and the extent of genomic analyses in the clinical context, need to take the availability of methods as well as the present clinical situation into account.

Major response of a peritoneal mesothelioma to nivolumab and ipilimumab: a case report, molecular analysis and review of literature.

Malignant peritoneal mesothelioma (MPM) is a rare tumor associated with a poor prognosis and a lack of consensus regarding treatment strategies. While the Checkmate 743 trial demonstrated the superiority of first-line nivolumab and ipilimumab over chemotherapy in malignant pleural mesothelioma (MPlM), few studies have assessed the effectiveness of immunotherapy against MPM, due to its rarity. Here, we report a major and sustained 12-month response in a 74-year-old female patient who received the anti-PD-1 nivolumab and the anti-CTLA4 ipilimumab as first-line therapy for diffuse MPM. PD-L1 was expressed and BAP1 expression was lost, as shown by immunohistochemistry, however the BAP1 gene was not mutated. Our findings suggest a role for ICI in non-resectable diffuse MPM exhibiting PD-L1 overexpression and loss of BAP1 expression, and instill new hope in their treatment. To our knowledge, this is the second reported case of dual immunotherapy used as first-line in MPM with a major clinical response. To investigate the clinical outcome, we conducted additional molecular analyses of the MPM tumor and we reviewed the literature on immunotherapy in MPM to discuss the role of PD-L1 and BAP1.

Prognosis-correlated Systems Involving Characteristic Diagnostic Gene Sets for Survival Analysis on Glioma.

As the most prevalent brain tumor, glioma is malignant with poor prognostic outcomes. As a result, it is of great importance to detect biomarkers for glioma diagnosis and prognosis. In this study, we determined grade-based characteristic gene clusters with gradual expression following grade change, including 1479 down- and 526 up-regulated genes. Combined interaction among proteins originating from these genes was analyzed, and hub genes were exhibited after GSEA enrichment, containing 12 and 11 genes which were correlated with prognostic outcomes, named as unfavorable and favorable gene sets, respectively. The GSVA score of each gene set was calculated and divided into high/low groups; we observed that cases in the low score group had better outcomes than the high score group based on the GSVA of the unfavorable set, while with favorable GSVA score, the low group had poorer outcomes than the high group. Eventually, we compared a variety of infiltrating immune cells between low/high GSVA subgroup, showing various immune cell types (B cell naive, activated mast cells, resting CD4 memory T cell, and so on) with opposite proportion. And interestingly, these cell types also accounted for a contrary percentage between unfavorable and favorable conditions. In conclusion, these two hub gene sets are of good importance as an evaluation system for clinical grade classification and prognosis prediction.

Molecular stratification of high-grade urothelial carcinoma by immunohistochemistry with its histomorphological and clinical correlation.

Introduction: Urothelial carcinoma poses a significant cause of morbidity and mortality. The recent classification of Tumors of Urinary System by World Health Organization fourth edition) has elucidated its molecular subtypes and its associated prognostic significance. Methods: We used immunohistochemistry marker expression (CK5/6, CK20, CD44, EGFR) as a surrogate marker, to stratify 150 cases of high-grade urothelial carcinoma into the intrinsic molecular subtypes. A correlation was also done with immunohistochemical markers p53, p21, E-cadherin and Ki-67. Results: On subtyping, 47.3% cases were basal, 42.7% luminal and 10% remained unclassified. We did not find GATA3 useful for molecular stratification in our study. Muscle invasion was seen in 59% of basal and 31% of luminal subtype (P = 0.016). Squamous differentiation was most commonly associated with basal subtype (P < 0.001). EGFR expression was seen in 62% of basal and 38% of luminal subtype (P = 0.014), and thus can be used as an additional marker for molecular stratification. Overexpression of p53 was seen in 64% cases of muscle invasive and 36% of non-muscle invasive high-grade carcinomas (P < 0.0001). An inverse relationship was observed between p53 and p21 immunoexpression (r = -0.494) (P < .0001). The overall survival at 1- and 2-year interval was more in the luminal subtype, suggesting an early mortality in basal group, (P = 0.827), and at 6 years both the groups had almost similar results. Conclusion: High-grade urothelial carcinoma is challenging in terms of therapeutic strategy. Increased understanding of underlying molecular basis helps identifying targetable treatment options, and newer biomarkers will enhance predictive and prognostic stratification.

Molecular Aberrations Stratify Grade 2 Astrocytomas Into Several Rare Entities: Prognostic and Therapeutic Implications.

The identification of specific molecular aberrations guides the prognostic stratification and management of grade 2 astrocytomas. Mutations in isocitrate dehydrogenase (IDH) 1 and 2, found in the majority of adult diffuse low-grade glioma (DLGG), seem to relate to a favorable prognosis compared to IDH wild-type (IDH-wt) counterparts. Moreover, the IDH-wt group can develop additional molecular alterations worsening the prognosis, such as epidermal growth factor receptor amplification (EGFR-amp) and mutation of the promoter of telomerase reverse transcriptase (pTERT-mut). This review analyzes the prognostic impact and therapeutic implications of genetic alterations in adult LGG.

Ligand-mediated PAI-1 inhibition in a mouse model of peritoneal carcinomatosis.

Peritoneal carcinomatosis (PC) present a ubiquitous clinical conundrum in all intra-abdominal malignancies. Via functional and transcriptomic experiments of ascites-treated PC cells, we identify STAT3 as a key signaling pathway. Integrative analysis of publicly available databases and correlation with clinical cohorts (n = 7,359) reveal putative clinically significant activating ligands of STAT3 signaling. We further validate a 3-biomarker prognostic panel in ascites independent of clinical covariates in a prospective study (n = 149). Via single-cell sequencing experiments, we uncover that PAI-1, a key component of the prognostic biomarker panel, is largely secreted by fibroblasts and mesothelial cells. Molecular stratification of ascites using PAI-1 levels and STAT3 activation in ascites-treated cells highlight a therapeutic opportunity based on a phenomenon of paracrine addiction. These results are recapitulated in patient-derived ascites-dependent xenografts. Here, we demonstrate therapeutic proof of concept of direct ligand inhibition of a prognostic target within an enclosed biological space.

Immunological Networks Defining the Heterogeneity of Inflammatory Bowel Diseases.

Current practice in IBD is to classify patients based on clinical signs and symptoms and provide treatments accordingly. However, the response of IBD patients to available treatments is highly variable, highlighting clinically significant heterogeneity among patients. Thus, more accurate patient stratification is urgently needed to more effectively target therapeutic interventions to specific patients. Here we review the degree of heterogeneity in IBD, discussing how the microbiota, genetics, and immune system may contribute to the variation among patients. We highlight how molecular heterogeneity may relate to clinical phenotype, but in other situations may be independent of clinical phenotype, encouraging future studies to fill the gaps. Finally, we discuss novel stratification methodologies as a foundation for precision medicine, in particular a novel stratification strategy based on conserved genes across species. All of these dimensions of heterogeneity have potential to provide strategies for patient stratification and move IBD practice towards personalised medicine.

Clinical Multigene Panel Sequencing Identifies Distinct Mutational Association Patterns in Metastatic Colorectal Cancer.

Extensive molecular characterization of human colorectal cancer (CRC) via Next Generation Sequencing (NGS) indicated that genetic or epigenetic dysregulation of a relevant, but limited, number of molecular pathways typically occurs in this tumor. The molecular picture of the disease is significantly complicated by the frequent occurrence of individually rare genetic aberrations, which expand tumor heterogeneity. Inter- and intratumor molecular heterogeneity is very likely responsible for the remarkable individual variability in the response to conventional and target-driven first-line therapies, in metastatic CRC (mCRC) patients, whose median overall survival remains unsatisfactory. Implementation of an extensive molecular characterization of mCRC in the clinical routine does not yet appear feasible on a large scale, while multigene panel sequencing of most commonly mutated oncogene/oncosuppressor hotspots is more easily achievable. Here, we report that clinical multigene panel sequencing performed for anti-EGFR therapy predictive purposes in 639 formalin-fixed paraffin-embedded (FFPE) mCRC specimens revealed previously unknown pairwise mutation associations and a high proportion of cases carrying actionable gene mutations. Most importantly, a simple principal component analysis directed the delineation of a new molecular stratification of mCRC patients in eight groups characterized by non-random, specific mutational association patterns (MAPs), aggregating samples with similar biology. These data were validated on a The Cancer Genome Atlas (TCGA) CRC dataset. The proposed stratification may provide great opportunities to direct more informed therapeutic decisions in the majority of mCRC cases.

Pan-cancer identification of clinically relevant genomic subtypes using outcome-weighted integrative clustering.

BACKGROUND: Comprehensive molecular profiling has revealed somatic variations in cancer at genomic, epigenomic, transcriptomic, and proteomic levels. The accumulating data has shown clearly that molecular phenotypes of cancer are complex and influenced by a multitude of factors. Conventional unsupervised clustering applied to a large patient population is inevitably driven by the dominant variation from major factors such as cell-of-origin or histology. Translation of these data into clinical relevance requires more effective extraction of information directly associated with patient outcome. METHODS: Drawing from ideas in supervised text classification, we developed survClust, an outcome-weighted clustering algorithm for integrative molecular stratification focusing on patient survival. survClust was performed on 18 cancer types across multiple data modalities including somatic mutation, DNA copy number, DNA methylation, and mRNA, miRNA, and protein expression from the Cancer Genome Atlas study to identify novel prognostic subtypes. RESULTS: Our analysis identified the prognostic role of high tumor mutation burden with concurrently high CD8 T cell immune marker expression and the aggressive clinical behavior associated with CDKN2A deletion across cancer types. Visualization of somatic alterations, at a genome-wide scale (total mutation burden, mutational signature, fraction genome altered) and at the individual gene level, using circomap further revealed indolent versus aggressive subgroups in a pan-cancer setting. CONCLUSIONS: Our analysis has revealed prognostic molecular subtypes not previously identified by unsupervised clustering. The algorithm and tools we developed have direct utility toward patient stratification based on tumor genomics to inform clinical decision-making. The survClust software tool is available at https://github.com/arorarshi/survClust .

Mechanistic Modeling of Gene Regulation and Metabolism Identifies Potential Targets for Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the predominant form of liver cancer and has long been among the top three cancers that cause the most deaths worldwide. Therapeutic options for HCC are limited due to the pronounced tumor heterogeneity. Thus, there is a critical need to study HCC from a systems point of view to discover effective therapeutic targets, such as through the systematic study of disease perturbation in both regulation and metabolism using a unified model. Such integration makes sense for cancers as it links one of the dominant physiological features of cancers (growth, which is driven by metabolic networks) with the primary available omics data source, transcriptomics (which is systematically integrated with metabolism through the regulatory-metabolic network model). Here, we developed an integrated transcriptional regulatory-metabolic model for HCC molecular stratification and the prediction of potential therapeutic targets. To predict transcription factors (TFs) and target genes affecting tumorigenesis, we used two algorithms to reconstruct the genome-scale transcriptional regulatory networks for HCC and normal liver tissue. which were then integrated with corresponding constraint-based metabolic models. Five key TFs affecting cancer cell growth were identified. They included the regulator CREB3L3, which has been associated with poor prognosis. Comprehensive personalized metabolic analysis based on models generated from data of liver HCC in The Cancer Genome Atlas revealed 18 genes essential for tumorigenesis in all three subtypes of patients stratified based on the non-negative matrix factorization method and two other genes (ACADSB and CMPK1) that have been strongly correlated with lower overall survival subtype. Among these 20 genes, 11 are targeted by approved drugs for cancers or cancer-related diseases, and six other genes have corresponding drugs being evaluated experimentally or investigationally. The remaining three genes represent potential targets. We also validated the stratification and prognosis results by an independent dataset of HCC cohort samples (LIRI-JP) from the International Cancer Genome Consortium database. In addition, microRNAs targeting key TFs and genes were also involved in established cancer-related pathways. Taken together, the multi-scale regulatory-metabolic model provided a new approach to assess key mechanisms of HCC cell proliferation in the context of systems and suggested potential targets.

Combination therapies with HSP90 inhibitors against colorectal cancer.

Oncogene stability and homeostasis mediated by the HSP90 chaperone is a crucial protection trait of cancer cells. Therefore, HSP90 represents an attractive therapeutic target for many cancers, including colorectal cancer. Although monotherapy has limited clinical efficacy, preclinical and early-phase clinical studies indicate improved antitumor activity when HSP90 inhibitors are combined with chemotherapies or targeted agents. This may be further improved with a biomarker-guided approach based on oncogenic HSP90 clients, or stratification based on the consensus molecular subtypes of colorectal cancer, suggesting a synergistic activity with 5-fluorouracil in preclinical models of the chemorefractory mesenchymal subtype. Furthermore, HSP90 inhibition may activate mechanisms to turn non-immunogenic tumors hot and improve their recognition by the immune system, suggesting synergy with immune checkpoint blockade.

Patient Selection for Radium-223 Therapy in Patients With Bone Metastatic Castration-Resistant Prostate Cancer: New Recommendations and Future Perspectives.

Radium-223 therapy was registered in 2013 as a new life-prolonging therapeutic option for patients with symptomatic bone metastatic castration-resistant prostate cancer after the phase 3 ALSYMPCA study. Postregistration reports on the use of radium-223 in real-world populations demonstrate that appropriate selection of patients for radium-223 therapy is challenging. While primarily retrospective and post hoc studies identified prognostic variables associated with overall survival, validated predictive biomarkers are still lacking. Important pretherapeutic prognostic variables include the number of prior therapies, baseline Eastern Cooperative Oncology Group performance status, baseline extent of bone metastatic disease, and baseline alkaline phosphatase, prostate-specific antigen, and lactate dehydrogenase levels. We reviewed the currently available literature to provide recommendations on patient selection for radium-223 therapy in patients with bone metastatic castration-resistant prostate cancer. In addition, the recent evidence from the report of the European Medicines Agency's Pharmacovigilance Risk Assessment Committee regarding the restricted use of radium-223 after interim data analysis of the ERA-223 trial has been incorporated into our recommendations. Future perspectives are also discussed, including radium-223 re-treatment, the use of concomitant therapies, and the implementation of pretherapeutic molecular analysis for treatment stratification.

Clinical Stratification of High-Grade Ovarian Serous Carcinoma Using a Panel of Six Biomarkers.

Molecular stratification of high-grade serous ovarian carcinoma (HGSC) for targeted therapy is a pertinent approach in improving prognosis of this highly heterogeneous disease. Enabling the same necessitates identification of class-specific biomarkers and their robust detection in the clinic. We have earlier resolved three discrete molecular HGSC classes associated with distinct functional behavior based on their gene expression patterns, biological networks, and pathways. An important difference revealed was that Class 1 is likely to exhibit cooperative cell migration (CCM), Class 2 undergoes epithelial to mesenchymal transition (EMT), while Class 3 is possibly capable of both modes of migration. In the present study, we define clinical stratification of HGSC tumors through the establishment of standard operating procedures for immunohistochemistry and histochemistry based detection of a panel of biomarkers including TCF21, E-cadherin, PARP1, Slug, AnnexinA2, and hyaluronan. Further development and application of scoring guidelines based on expression of this panel in cell line-derived xenografts, commercial tissue microarrays, and patient tumors led to definitive stratification of samples. Biomarker expression was observed to vary significantly between primary and metastatic tumors suggesting class switching during disease progression. Another interesting feature in the study was of enhanced CCM-marker expression in tumors following disease progression and chemotherapy. These stratification principles and the new information thus generated is the first step towards class-specific personalized therapies in the disease.