Multi-omic based molecular profiling of advanced cancer identifies treatable targets and improves survival in individual patients.

A proof-of-concept study was conducted to assess whether patients with advanced stage IV cancer for whom predominantly no standard therapy was available could benefit from comprehensive molecular profiling of their tumor tissue to provide targeted therapy. Tumor samples of 83 patients were collected under highly standardized conditions and analyzed using immunohistochemistry, next-generation sequencing and phosphoprotein profiling. Expression and phosphorylation of key oncogenic pathways were measured to identify targets at the (phospho-) proteomic level. At genomic level, 50 oncogenes and tumor suppressor genes were analyzed. Based on molecular profiling, targeted therapies were decided by the attending oncologist. Accordingly, 28 patients who met the defined criteria fell in two equal-sized groups. One group received targeted therapies while the other did not. Following six months of treatment, disease control was achieved by 49% of patients receiving targeted therapy (complete remission, 14%; partial remission, 21%; stable disease, 14%; disease progression, 36%; death, 14%) and 21% of patients receiving non-targeted therapy (stable disease, 21%; disease progression, 64%; death, 14%). Individual patients experienced dramatic responses to a therapy which otherwise would not have been applied. This approach clarifies the value of multi-omic molecular profiling for cancer diagnostics.

Nanoproteomic analysis of ischemia-dependent changes in signaling protein phosphorylation in colorectal normal and cancer tissue.

BACKGROUND: Clinical diagnostic research relies upon the collection of tissue samples, and for those samples to be representative of the in vivo situation. Tissue collection procedures, including post-operative ischemia, can impact the molecular profile of the tissue at the genetic and proteomic level. Understanding the influence of factors such as ischemia on tissue samples is imperative in order to develop both markers of tissue quality and ultimately accurate diagnostic tests. METHODS: Using NanoPro1000 technology, a rapid and highly sensitive immunoassay platform, the phosphorylation status of clinically relevant cancer-related biomarkers in response to ischemia was quantified in tissue samples from 20 patients with primary colorectal cancer. Tumor tissue and adjacent normal tissue samples were collected and subjected to cold ischemia prior to nanoproteomic analysis of AKT, ERK1/2, MEK1/2, and c-MET. Ischemia-induced relative changes in overall phosphorylation and phosphorylation of individual isoforms were calculated and statistical significance determined. Any differences in baseline levels of phosphorylation between tumor tissue and normal tissue were also analyzed. RESULTS: Changes in overall phosphorylation of the selected proteins in response to ischemia revealed minor variations in both normal and tumor tissue; however, significant changes were identified in the phosphorylation of individual isoforms. In normal tissue post-operative ischemia, phosphorylation was increased in two AKT isoforms, two ERK1/2 isoforms, and one MEK1/2 isoform and decreased in one MEK1/2 isoform and one c-MET isoform. Following ischemia in tumor tissue, one AKT isoform showed decreased phosphorylation and there was an overall increase in unphosphorylated ERK1/2, whereas an increase in the phosphorylation of two MEK1/2 isoforms was observed. There were no changes in c-MET phosphorylation in tumor tissue. CONCLUSION: This study provides insight into the influence of post-operative ischemia on tissue sample biology, which may inform the future development of markers of tissue quality and assist in the development of diagnostic tests.

Metabolomics profiling of pre-and post-anesthesia plasma samples of colorectal patients obtained via Ficoll separation.

1H NMR spectroscopy was used to investigate the metabolic consequences of general anesthesia in the plasma of two groups of patients with diagnosis for non-metastatic colorectal cancer and metastatic colorectal cancer with liver-metastasis, respectively. Patients were treated with etomidate or propofol, two frequently used sedation agents. Plasma samples were obtained via Ficoll separation. Here, we demonstrated that this procedure introduces a number of limitations for NMR-based metabolomics studies, due to the appearance of spurious signals. Nevertheless, the comparison of the 1H NMR metabolomic profiles of patients treated with etomidate or propofol at equipotent dose ranges was still feasible and proved that both agents significantly decrease the plasma levels of several NMR-detectable metabolites. Consequently, samples collected during anesthesia are not suitable for metabolic profiling studies aimed at patient stratification, because interpersonal variability are reduced by the overall depression of metabolites levels. On the other hand, this study showed that plasma metabolomics could represent a valuable tool to monitor the effect of different sedation agents and/or the individual metabolic response to anesthesia, providing hints for an appropriate tuning of personalized sedation procedures. In our reference groups, the metabolomic signatures were slightly different in patients anesthetized with etomidate versus propofol. The importance of standardized collection procedures and availability of exhaustive metadata of the experimental design for the accurate evaluation of the significance of the observed changes in metabolites levels are critically discussed.

Identification and Validation of a Potential Marker of Tissue Quality Using Gene Expression Analysis of Human Colorectal Tissue.

Correlative studies have identified numerous biomarkers that are individualizing therapy across many medical specialties, including oncology. Accurate interpretation of these studies requires the collection of tissue samples of sufficient quality. Tissue quality can be measured by changes in levels of gene expression and can be influenced by many factors including pre-analytical conditions, ischemic effects and the surgical collection procedure itself. However, as yet there are no reliable biomarkers of tissue quality at researchers' disposal. The aim of the current study was to identify genes with expression patterns that fluctuated reproducibly in response to typical post-surgical stress (ischemia) in order to identify a specific marker of tissue quality. All tissue samples were obtained from patients with primary colorectal carcinoma (CRC) (N = 40) either via colonoscopy prior to surgery, or by surgical resection. Surgically resected tissue samples were divided into three groups and subjected to cold ischemia for 10, 20 or 45 minutes. Normal colorectal tissue and CRC tissue was analyzed using microarray and quantitative real-time PCR (qPCR). Comparing changes in gene expression between pre- and post-surgical tissue using microarray analysis identified a list of potential tissue quality biomarkers and this list was validated using qPCR. Results revealed that post-operative ischemia significantly alters gene expression in normal and CRC tissue samples. Both microarray analysis and qPCR revealed regulator of G-protein signaling 1 (RGS1) as a potential marker of CRC tissue quality and eukaryotic translation elongation factor 1 alpha 1 (EEF1A1) as a potential reference gene of post-operative tissue quality. Larger studies with additional time points and endpoints will be needed to confirm these results.

Prediction of individual response to anticancer therapy: historical and future perspectives.

Since the introduction of chemotherapy for cancer treatment in the early 20th century considerable efforts have been made to maximize drug efficiency and at the same time minimize side effects. As there is a great interpatient variability in response to chemotherapy, the development of predictive biomarkers is an ambitious aim for the rapidly growing research area of personalized molecular medicine. The individual prediction of response will improve treatment and thus increase survival and life quality of patients. In the past, cell cultures were used as in vitro models to predict in vivo response to chemotherapy. Several in vitro chemosensitivity assays served as tools to measure miscellaneous endpoints such as DNA damage, apoptosis and cytotoxicity or growth inhibition. Twenty years ago, the development of high-throughput technologies, e.g. cDNA microarrays enabled a more detailed analysis of drug responses. Thousands of genes were screened and expression levels were correlated to drug responses. In addition, mutation analysis became more and more important for the prediction of therapeutic success. Today, as research enters the area of -omics technologies, identification of signaling pathways is a tool to understand molecular mechanism underlying drug resistance. Combining new tissue models, e.g. 3D organoid cultures with modern technologies for biomarker discovery will offer new opportunities to identify new drug targets and in parallel predict individual responses to anticancer therapy. In this review, we present different currently used chemosensitivity assays including 2D and 3D cell culture models and several -omics approaches for the discovery of predictive biomarkers. Furthermore, we discuss the potential of these assays and biomarkers to predict the clinical outcome of individual patients and future perspectives.

Surgical procedures and postsurgical tissue processing significantly affect expression of genes and EGFR-pathway proteins in colorectal cancer tissue.

An understanding of tissue data variability in relation to processing techniques during and postsurgery would be desirable when testing surgical specimens for clinical diagnostics, drug development, or identification of predictive biomarkers. Specimens of normal and colorectal cancer (CRC) tissues removed during colon and liver resection surgery were obtained at the beginning of surgery and postsurgically, tissue was fixed at 10, 20, and 45 minutes. Specimens were analyzed from 50 patients with primary CRC and 43 with intrahepatic metastasis of CRC using a whole genome gene expression array. Additionally, we focused on the epidermal growth factor receptor pathway and quantified proteins and their phosphorylation status in relation to tissue processing timepoints. Gene and protein expression data obtained from colorectal and liver specimens were influenced by tissue handling during surgery and by postsurgical processing time. To obtain reliable expression data, tissue processing for research and diagnostic purposes needs to be highly standardized.

Detection of colorectal adenoma and cancer based on transthyretin and C3a-desArg serum levels.

Colorectal cancer is the second leading cause of cancer death, and it develops from benign colorectal adenomas in over 95% of patients. Early detection of these cancer precursors by screening tests and their removal can potentially eradicate more than 95% of colorectal cancers before they develop. To discover sensitive and specific biomarkers for improvement of pre-clinical diagnosis of colorectal adenoma and cancer, we analysed in two independent studies (n = 87 and n = 83 patients) serum samples from colorectal cancer (stage III), colorectal adenoma and control patients using SELDI-TOF-MS. Extensive statistical analysis was performed to establish homogeneous patient groups based on their clinical data. Two biomarkers that were each able to distinguish control patients from either colorectal adenoma or colorectal cancer patients (p<0.001) were identified as transthyretin (pre-albumin) and C3a-desArg by MS/MS and were further validated by antibody-based assays (radial immunodiffusion, ELISA). A combination of both proteins clearly indicated the presence of colorectal adenoma or carcinoma. Using a cut-off of <0.225 g/L for transthyretin and >1974 ng/mL for C3a-desArg, we found a sensitivity and specificity for colorectal adenoma of 96% and 70%, respectively.

Detection and quantification of mutations in the plasma of patients with colorectal tumors.

The early detection of cancers through analysis of circulating DNA could have a substantial impact on morbidity and mortality. To achieve this goal, it is essential to determine the number of mutant molecules present in the circulation of cancer patients and to develop methods that are sufficiently sensitive to detect these mutations. Using a modified version of a recently developed assay for this purpose, we found that patients with advanced colorectal cancers consistently contained mutant adenomatous polyposis coli (APC) DNA molecules in their plasma. The median number of APC DNA fragments in such patients was 47,800 per ml of plasma, of which 8% were mutant. Mutant APC molecules were also detected in >60% of patients with early, presumably curable colorectal cancers, at levels ranging from 0.01% to 1.7% of the total APC molecules. These results have implications for the mechanisms through which tumor DNA is released into the circulation and for diagnostic tests based on this phenomenon.

Extraction and processing of high quality RNA from impalpable and macroscopically invisible prostate cancer for microarray gene expression analysis.

Molecular analyses of early-stage prostate cancers are necessary to assess their potential clinical significance based on established and/or novel biomarkers for tailored clinical management. A prerequisite for the application of RNA-based analyses of such, mostly macroscopically-undetectable, small prostate carcinomas is the recovery and preservation of sufficient RNA quantities and quality. Furthermore, in prostate cancer, heterogeneity is a common phenomenon that includes a juxtaposition of different tissue compositions and variable histological grades within the same tumor focus. To better understand the molecular mechanisms of prostate cancer, it is essential to correlate molecular data with a specific cell type. Here, we present a tissue collecting protocol which is aligned with the preoperative evaluation of tumor localization. In combination with the technique of laser microdissection and pressure catapulting, we are able to preserve RNA of high quality from homogeneous cell populations of macroscopically-undetectable small prostate carcinomas. To obtain the necessary RNA quantities for whole genome cDNA microarrays, the isolated total RNAs were amplified by T7-based RNA-polymerase in vitro transcription. The microarray analyses (Human Unigene Set RZPD3.1) resulted in 216 differentially expressed genes (191 down-regulated, 25 up-regulated). Among these were several known prostate cancer relevant genes, such as AMACR, TARP, LIM, GPR160 (all up-regulated), CAV1, NTN1, MT1X; CLU, TRIM29, SPARCL1 and HSPB8 (all down-regulated).

Tissue ischemia time affects gene and protein expression patterns within minutes following surgical tumor excision.

The aim of this study was to determine the impact of ischemia on gene and protein expression profiles of healthy and malignant colon tissue and, thus, on screening studies for identification of molecular targets and diagnostic molecular patterns. Healthy and malignant colon tissue were snap-frozen at various time points (3-30 min) after colon resection. Gene and protein expression were determined by microarray (HG-U133A chips) and surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) technology (CM10 chips, SAX2 chips, and IMAC3Ni chips), respectively. Real-time reverse transcription PCR (RT-PCR) was used for comparative measurement of expression of particular genes. Initial changes of gene and protein expression profiles were already observed 5-8 min after colon resection. Fifteen minutes after surgery, 10%-15% of molecules, and after 30 min, 20% of all detectable genes and proteins, respectively, differed significantly from the baseline values. Significant changes of expression were found in most functional groups. As confirmed by real-time RT-PCR, this included not only known hypoxia-related molecules (HIF-1 alpha, c-fos, HO-1) but also cytoskeletal genes (e.g., CK20) and tumor-associated antigens (e.g., CEA). In conclusion, preanalytical factors, such as tissue ischemia time, dramatically affect molecular data. Control of these variables is mandatory to obtain reliable data in screening programs for molecular targets and diagnostic molecular patterns.