Applied Molecular-Based Quality Control of Biobanked Samples for Multi-Omics Approach.

Biobanks are vital for high-throughput translational research, but the rapid development of novel molecular techniques, especially in omics assays, poses challenges to traditional practices and recommendations. In our study, we used biospecimens from oncological patients in Polish clinics and collaborated with the Indivumed Group. For serum/plasma samples, we monitored hemolysis, controlled RNA extraction, assessed cDNA library quality and quantity, and verified NGS raw data. Tissue samples underwent pathologic evaluation to confirm histology and determine tumor content. Molecular quality control measures included evaluating the RNA integrity number, assessing cDNA library quality and quantity, and analyzing NGS raw data. Our study yielded the creation of distinct workflows for conducting preanalytical quality control of serum/plasma and fresh-frozen tissue samples. These workflows offer customization options to suit the capabilities of different biobanking entities. In order to ensure the appropriateness of biospecimens for advanced research applications, we introduced molecular-based quality control methods that align with the demands of high-throughput assays. The novelty of proposed workflows, rooted in innovative molecular techniques, lies in the integration of these QC methods into a comprehensive schema specifically designed for high-throughput research applications.

Just Add Data: automated predictive modeling for knowledge discovery and feature selection.

Fully automated machine learning (AutoML) for predictive modeling is becoming a reality, giving rise to a whole new field. We present the basic ideas and principles of Just Add Data Bio (JADBio), an AutoML platform applicable to the low-sample, high-dimensional omics data that arise in translational medicine and bioinformatics applications. In addition to predictive and diagnostic models ready for clinical use, JADBio focuses on knowledge discovery by performing feature selection and identifying the corresponding biosignatures, i.e., minimal-size subsets of biomarkers that are jointly predictive of the outcome or phenotype of interest. It also returns a palette of useful information for interpretation, clinical use of the models, and decision making. JADBio is qualitatively and quantitatively compared against Hyper-Parameter Optimization Machine Learning libraries. Results show that in typical omics dataset analysis, JADBio manages to identify signatures comprising of just a handful of features while maintaining competitive predictive performance and accurate out-of-sample performance estimation.

The Essentials of Multiomics.

Within the last decade, the science of molecular testing has evolved from single gene and single protein analysis to broad molecular profiling as a standard of care, quickly transitioning from research to practice. Terms such as genomics, transcriptomics, proteomics, circulating omics, and artificial intelligence are now commonplace, and this rapid evolution has left us with a significant knowledge gap within the medical community. In this paper, we attempt to bridge that gap and prepare the physician in oncology for multiomics, a group of technologies that have gone from looming on the horizon to become a clinical reality. The era of multiomics is here, and we must prepare ourselves for this exciting new age of cancer medicine.

Global mapping of cancers: The Cancer Genome Atlas and beyond.

Cancer genomes have been explored from the early 2000s through massive exome sequencing efforts, leading to the publication of The Cancer Genome Atlas in 2013. Sequencing techniques have been developed alongside this project and have allowed scientists to bypass the limitation of costs for whole-genome sequencing (WGS) of single specimens by developing more accurate and extensive cancer sequencing projects, such as deep sequencing of whole genomes and transcriptomic analysis. The Pan-Cancer Analysis of Whole Genomes recently published WGS data from more than 2600 human cancers together with almost 1200 related transcriptomes. The application of WGS on a large database allowed, for the first time in history, a global analysis of features such as molecular signatures, large structural variations and noncoding regions of the genome, as well as the evaluation of RNA alterations in the absence of underlying DNA mutations. The vast amount of data generated still needs to be thoroughly deciphered, and the advent of machine-learning approaches will be the next step towards the generation of personalized approaches for cancer medicine. The present manuscript wants to give a broad perspective on some of the biological evidence derived from the largest sequencing attempts on human cancers so far, discussing advantages and limitations of this approach and its power in the era of machine learning.

Druggable genome and precision medicine in cancer: current challenges.

The past decades have seen tremendous developments with respect to "specific" therapeutics that target key signaling molecules to conquer cancer. The key advancements with multiomics technologies, especially genomics, have allowed physicians and molecular oncologists to design "tailor-made" solutions to the specific oncogenes that are deregulated in individual patients, a strategy which has turned out to be successful though the patients quickly develop resistance. The swift integration of multidisciplinary approaches has led to the development of "next generation" therapeutics and, with synergistic therapeutic regimes combined with immune checkpoint inhibitors to reactivate the dampened immune response, has provided the much-needed promise for cancer patients. Despite these advances, a large portion of the druggable genome remains understudied, and the role of druggable genome in the immune system needs further attention. Establishment of patient-derived organoid models has fastened the preclinical validation of novel therapeutics for swift clinical translation. We summarized the current advances and challenges and also stress the importance of biobanking and collection of longitudinal data sets with structured clinical information, as well as the critical role these "high content data sets" will play in designing new therapeutic regimes in a tailor-made fashion.

Liquid biopsies and cancer omics.

The development of the sequencing technologies allowed the generation of huge amounts of molecular data from a single cancer specimen, allowing the clinical oncology to enter the era of the precision medicine. This massive amount of data is highlighting new details on cancer pathogenesis but still relies on tissue biopsies, which are unable to capture the dynamic nature of cancer through its evolution. This assumption led to the exploration of non-tissue sources of tumoral material opening the field of liquid biopsies. Blood, together with body fluids such as urines, or stool, from cancer patients, are analyzed applying the techniques used for the generation of omics data. With blood, this approach would allow to take into account tumor heterogeneity (since the circulating components such as CTCs, ctDNA, or ECVs derive from each cancer clone) in a time dependent manner, resulting in a somehow "real-time" understanding of cancer evolution. Liquid biopsies are beginning nowdays to be applied in many cancer contexts and are at the basis of many clinical trials in oncology.

Cancer predictive studies.

The identification of individual or clusters of predictive genetic alterations might help in defining the outcome of cancer treatment, allowing for the stratification of patients into distinct cohorts for selective therapeutic protocols. Neuroblastoma (NB) is the most common extracranial childhood tumour, clinically defined in five distinct stages (1-4 & 4S), where stages 3-4 define chemotherapy-resistant, highly aggressive disease phases. NB is a model for geneticists and molecular biologists to classify genetic abnormalities and identify causative disease genes. Despite highly intensive basic research, improvements on clinical outcome have been predominantly observed for less aggressive cancers, that is stages 1,2 and 4S. Therefore, stages 3-4 NB are still complicated at the therapeutic level and require more intense fundamental research. Using neuroblastoma as a model system, here we herein outline how cancer prediction studies can help at steering preclinical and clinical research toward the identification and exploitation of specific genetic landscape. This might result in maximising the therapeutic success and minimizing harmful effects in cancer patients.

Differential regulation of extracellular matrix proteins in three recurrent liver metastases of a single patient with colorectal cancer.

Colorectal cancer (CRC) patients suffer from the second highest mortality among all cancer entities. In half of all CRC patients, colorectal cancer liver metastases (CRLM) can be observed. Metastatic colorectal cancer is associated with poor overall survival and limited treatment options. Even after successful surgical resection of the primary tumor, metachronous liver metastases occur in one out of eight cases. The only available curative intended treatment is hepatic resection, but metachronous CRLM frequently recur after approximately 1 year. In this study, we performed a proteome analysis of three recurrent liver metastases of a single CRC patient by mass spectrometry. Despite surgical resection of the primary CRC and adjuvant chemotherapy plus cetuximab treatment, the patient developed three metachronous CRLM which occurred consecutively after 9, 21 and 31 months. We identified a set of 1132 proteins expressed in the three metachronous CRLM, of which 481 were differentially regulated, including 81 proteins that were associated with the extracellular matrix (ECM). 56 ECM associated proteins were identified as upregulated in the third metastasis, 26 (46%) of which were previously described as negative prognostic markers in CRC, including tenascin C, nidogen 1, fibulin 1 and vitronectin. These data may reflect an ascending trend of malignancy from the first to the third metachronous colorectal cancer liver metastasis. Additionally, the results indicate different ECM phenotypes for recurrent metachronous metastasis, associated with different grades of malignancy and highlights the importance of individual analysis of molecular features in different, consecutive metastatic events in a single patient.

NGS Evaluation of Colorectal Cancer Reveals Interferon Gamma Dependent Expression of Immune Checkpoint Genes and Identification of Novel IFNγ Induced Genes.

To evaluate the expression of immune checkpoint genes, their concordance with expression of IFNγ, and to identify potential novel ICP related genes (ICPRG) in colorectal cancer (CRC), the biological connectivity of six well documented ("classical") ICPs (CTLA4, PD1, PDL1, Tim3, IDO1, and LAG3) with IFNγ and its co-expressed genes was examined by NGS in 79 CRC/healthy colon tissue pairs. Identification of novel IFNγ- induced molecules with potential ICP activity was also sought. In our study, the six classical ICPs were statistically upregulated and correlated with IFNγ, CD8A, CD8B, CD4, and 180 additional immunologically related genes in IFNγ positive (FPKM > 1) tumors. By ICP co-expression analysis, we also identified three IFNγ-induced genes [(IFNγ-inducible lysosomal thiol reductase (IFI30), guanylate binding protein1 (GBP1), and guanylate binding protein 4 (GBP4)] as potential novel ICPRGs. These three genes were upregulated in tumor compared to normal tissues in IFNγ positive tumors, co-expressed with CD8A and had relatively high abundance (average FPKM = 362, 51, and 25, respectively), compared to the abundance of the 5 well-defined ICPs (Tim3, LAG3, PDL1, CTLA4, PD1; average FPKM = 10, 9, 6, 6, and 2, respectively), although IDO1 is expressed at comparably high levels (FPKM = 39). We extended our evaluation by querying the TCGA database which revealed the commonality of IFNγ dependent expression of the three potential ICPRGs in 638 CRCs, 103 skin cutaneous melanomas (SKCM), 1105 breast cancers (BC), 184 esophageal cancers (ESC), 416 stomach cancers (STC), and 501 lung squamous carcinomas (LUSC). In terms of prognosis, based on Pathology Atlas data, correlation of GBP1 and GBP4, but not IFI30, with 5-year survival rate was favorable in CRC, BC, SKCM, and STC. Thus, further studies defining the role of IFI30, GBP1, and GBP4 in CRC are warranted.

Novel reference genes in colorectal cancer identify a distinct subset of high stage tumors and their associated histologically normal colonic tissues.

BACKGROUND: Reference genes are often interchangeably called housekeeping genes due to 1) the essential cellular functions their proteins provide and 2) their constitutive expression across a range of normal and pathophysiological conditions. However, given the proliferative drive of malignant cells, many reference genes such as beta-actin (ACTB) and glyceraldehyde-3-phosphate-dehydrogenase (GAPDH) which play critical roles in cell membrane organization and glycolysis, may be dysregulated in tumors versus their corresponding normal controls METHODS: Because Next Generation Sequencing (NGS) technology has several advantages over hybridization-based technologies, such as independent detection and quantitation of transcription levels, greater sensitivity, and increased dynamic range, we evaluated colorectal cancers (CRC) and their histologically normal tissue counterparts by NGS to evaluate the expression of 21 "classical" reference genes used as normalization standards for PCR based methods. Seventy-nine paired tissue samples of CRC and their patient matched healthy colonic tissues were subjected to NGS analysis of their mRNAs. RESULTS: We affirmed that 17 out of 21 classical reference genes had upregulated expression in tumors compared to normal colonic epithelial tissue and dramatically so in some cases. Indeed, tumors were distinguished from normal controls in both unsupervised hierarchical clustering analyses (HCA) and principal component analyses (PCA). We then identified 42 novel potential reference genes with minimal coefficients of variation (CV) across 79 CRC tumor pairs. Though largely consistently expressed across tumors and normal control tissues, a subset of high stage tumors (HSTs) as well as some normal tissue samples (HSNs) located adjacent to these HSTs demonstrated dysregulated expression, thus identifying a subset of tumors with a potentially distinct and aggressive biological profile. CONCLUSION: While classical CRC reference genes were found to be differentially expressed between tumors and normal controls, novel reference genes, identified via NGS, were more consistently expressed across malignant and normal colonic tissues. Nonetheless, a subset of HST had profound dysregulation of such genes as did many of the histologically normal tissues adjacent to such HSTs, indicating that the HSTs so distinguished may have unique biological properties and that their histologically normal tissues likely harbor a small population of microscopically undetected but metabolically active tumors.

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.

Comparison of central laboratory assessments of ER, PR, HER2, and Ki67 by IHC/FISH and the corresponding mRNAs (ESR1, PGR, ERBB2, and MKi67) by RT-qPCR on an automated, broadly deployed diagnostic platform.

PURPOSE: The methods (IHC/FISH) typically used to assess ER, PR, HER2, and Ki67 in FFPE specimens from breast cancer patients are difficult to set up, perform, and standardize for use in low and middle-income countries. Use of an automated diagnostic platform (GeneXpert®) and assay (Xpert® Breast Cancer STRAT4) that employs RT-qPCR to quantitate ESR1, PGR, ERBB2, and MKi67 mRNAs from formalin-fixed, paraffin-embedded (FFPE) tissues facilitates analyses in less than 3 h. This study compares breast cancer biomarker analyses using an RT-qPCR-based platform with analyses using standard IHC and FISH for assessment of the same biomarkers. METHODS: FFPE tissue sections from 523 patients were sent to a College of American Pathologists-certified central reference laboratory to evaluate concordance between IHC/FISH and STRAT4 using the laboratory's standard of care methods. A subset of 155 FFPE specimens was tested for concordance with STRAT4 using different IHC antibodies and scoring methods. RESULTS: Concordance between STRAT4 and IHC was 97.8% for ESR1, 90.4% for PGR, 93.3% for ERBB2 (IHC/FISH for HER2), and 78.6% for MKi67. Receiver operating characteristic curve (ROC) area under the curve (AUC) values of 0.99, 0.95, 0.99, and 0.85 were generated for ESR1, PGR, ERBB2, and MKi67, respectively. Minor variabilities were observed depending on the IHC antibody comparator used. CONCLUSION: Evaluation of breast cancer biomarker status by STRAT4 was highly concordant with central IHC/FISH in this blinded, retrospectively analyzed collection of samples. STRAT4 may provide a means to cost-effectively generate standardized diagnostic results for breast cancer patients in low- and middle-income countries.

Tumor Pre-Analytics in Molecular Pathology: Impact on Protein Expression and Analysis.

PURPOSE OF REVIEW: Precision medicine promises patient tailored, individualized diagnosis and treatment of diseases and relies on clinical specimen integrity and accuracy of companion diagnostic testing. Therefore, pre-analytics, which are defined as the collection, processing, and storage of clinical specimens, are critically important to enable optimal diagnostics, molecular profiling, and clinical decision-making around harvested specimens. This review article discusses the impact of tumor pre-analytics on molecular pathology focusing on biospecimen protein expression and analysis. RECENT FINDINGS: Due to busy clinical schedules and workflows that have been established for many years and to lack of standardization and limited assessment tools to quantify variability in pre-analytical processing, the effects of pre-analytics on biospecimen integrity are often overlooked. Several studies have recently emphasized an emerging crisis in science and reproducibility of results. SUMMARY: Biomarker instability due to pre-analytical variables affects comprehensive analysis and molecular phenotyping of patients' tissue. This problematic emphasizes the critical need for standardized protocols and technologies to be applied in the clinical and research setting.

Transcriptome analysis of human colorectal cancer biopsies reveals extensive expression correlations among genes related to cell proliferation, lipid metabolism, immune response and collagen catabolism.

Precise characterization of biological processes critical to proliferation and metastasis of colorectal cancer should facilitate the development of diagnostic and prognostic biomarkers as well as novel treatments. Using mRNA-Seq, we examined the protein coding messenger RNA (mRNA) expression profiles across different histologically defined stages of primary colon cancers and compared them to their patient matched normal tissue controls. In comparing 79 colorectal cancers to their matched normal mucosa, tumors were distinguished from normal non-malignant tissues not only in the upregulation of biological processes pertaining to cell proliferation, inflammation, and tissue remodeling, but even more strikingly, in downregulated biological processes including fatty acid beta oxidization for ATP production and epithelial cell differentiation and function. A network analysis of deregulated genes revealed newly described cancer networks and putative hub genes. Taken together, our findings suggest that, within an inflammatory microenvironment, invasive, dedifferentiated and rapidly dividing tumor cells divert the oxidation of fatty acids and lipids from energy production into lipid components of cell membranes and organelles to support tumor proliferation. A gene co-expression network analysis provides a clear and broad picture of biological pathways in tumors that may significantly enhance or supplant current histopathologic studies.

Systematic biobanking, novel imaging techniques, and advanced molecular analysis for precise tumor diagnosis and therapy: The Polish MOBIT project.

Personalized and precision medicine is gaining recognition due to the limitations by standard diagnosis and treatment; many areas of medicine, from cancer to psychiatry, are moving towards tailored and individualized treatment for patients based on their clinical characteristics and genetic signatures as well as novel imaging techniques. Advances in whole genome sequencing have led to identification of genes involved in a variety of diseases. Moreover, biomarkers indicating severity of disease or susceptibility to treatment are increasingly being characterized. The continued identification of new genes and biomarkers specific to disease subtypes and individual patients is essential and inevitable for translation into personalized medicine, in estimating both, disease risk and response to therapy. Taking into consideration the mostly unsolved necessity of tailored therapy in oncology the innovative project MOBIT (molecular biomarkers for individualized therapy) was designed. The aims of the project are: (i) establishing integrative management of precise tumor diagnosis and therapy including systematic biobanking, novel imaging techniques, and advanced molecular analysis by collecting comprehensive tumor tissues, liquid biopsies (whole blood, serum, plasma), and urine specimens (supernatant; sediment) as well as (ii) developing personalized lung cancer diagnostics based on tumor heterogeneity and integrated genomics, transcriptomics, metabolomics, and radiomics PET/MRI analysis. It will consist of 5 work packages. In this paper the rationale of the Polish MOBIT project as well as its design is presented. (iii) The project is to draw interest in and to invite national and international, private and public, preclinical and clinical initiatives to establish individualized and precise procedures for integrating novel targeted therapies and advanced imaging techniques.

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.

Distinct Profiles for Mitochondrial t-RNAs and Small Nucleolar RNAs in Locally Invasive and Metastatic Colorectal Cancer.

PURPOSE: To gain insight into factors involved in tumor progression and metastasis, we examined the role of noncoding RNAs in the biologic characteristics of colorectal carcinoma, in paired samples of tumor together with normal mucosa from the same colorectal carcinoma patient. The tumor and healthy tissue samples were collected and stored under stringent conditions, thereby minimizing warm ischemic time. EXPERIMENTAL DESIGN: We focused particularly on distinctions among high-stage tumors and tumors with known metastases, performing RNA-Seq analysis that quantifies transcript abundance and identifies novel transcripts. RESULTS: In comparing 35 colorectal carcinomas, including 9 metastatic tumors (metastases to lymph nodes and lymphatic vessels), with their matched healthy control mucosa, we found a distinct signature of mitochondrial transfer RNAs (MT-tRNA) and small nucleolar RNAs (snoRNA) for metastatic and high-stage colorectal carcinoma. We also found the following: (i) MT-TF (phenylalanine) and snord12B expression correlated with a substantial number of miRNAs and mRNAs in 14 colorectal carcinomas examined; (ii) an miRNA signature of oxidative stress, hypoxia, and a shift to glycolytic metabolism in 14 colorectal carcinomas, regardless of grade and stage; and (iii) heterogeneous MT-tRNA/snoRNA fingerprints for 35 pairs. CONCLUSIONS: These findings could potentially assist in more accurate and predictive staging of colorectal carcinoma, including identification of those colorectal carcinomas likely to metastasize.

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.

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.