Impact of collection and storage of lung tumor tissue on whole genome expression profiling

Tumor specimen cold ischemia time impacts molecular cancer drug target discovery

Tumor tissue collections are used to uncover pathways associated with disease outcomes that can also serve as targets for cancer treatment, ideally by comparing the molecular properties of cancer tissues to matching normal tissues. The quality of such collections determines the value of the data and information generated from their analyses including expression and modifications of nucleic acids and proteins. These biomolecules are dysregulated upon ischemia and decompose once the living cells start to decay into inanimate matter. Therefore, ischemia time before final tissue preservation is the most important determinant of the quality of a tissue collection. Here we show the impact of ischemia time on tumor and matching adjacent normal tissue samples for mRNAs in 1664, proteins in 1818, and phosphosites in 1800 cases (tumor and matching normal samples) of four solid tumor types (CRC, HCC, LUAD, and LUSC NSCLC subtypes). In CRC, ischemia times exceeding 15 min impacted 12.5% (mRNA), 25% (protein), and 50% (phosphosites) of differentially expressed molecules in tumor versus normal tissues. This hypoxia- and decay-induced dysregulation increased with longer ischemia times and was observed across tumor types. Interestingly, the proteomics analysis revealed that specimen ischemia time above 15 min is mostly associated with a dysregulation of proteins in the immune-response pathway and less so with metabolic processes. We conclude that ischemia time is a crucial quality parameter for tissue collections used for target discovery and validation in cancer research.

Machine learning-based investigation of regulated cell death for predicting prognosis and immunotherapy response in glioma patients

Glioblastoma is a highly aggressive and malignant type of brain cancer that originates from glial cells in the brain, with a median survival time of 15 months and a 5-year survival rate of less than 5%. Regulated cell death (RCD) is the autonomous and orderly cell death under genetic control, controlled by precise signaling pathways and molecularly defined effector mechanisms, modulated by pharmacological or genetic interventions, and plays a key role in maintaining homeostasis of the internal environment. The comprehensive and systemic landscape of the RCD in glioma is not fully investigated and explored. After collecting 18 RCD-related signatures from the opening literature, we comprehensively explored the RCD landscape, integrating the multi-omics data, including large-scale bulk data, single-cell level data, glioma cell lines, and proteome level data. We also provided a machine learning framework for screening the potentially therapeutic candidates. Here, based on bulk and single-cell sequencing samples, we explored RCD-related phenotypes, investigated the profile of the RCD, and developed an RCD gene pair scoring system, named RCD.GP signature, showing a reliable and robust performance in predicting the prognosis of glioblastoma. Using the machine learning framework consisting of Lasso, RSF, XgBoost, Enet, CoxBoost and Boruta, we identified seven RCD genes as potential therapeutic targets in glioma and verified that the SLC43A3 highly expressed in glioma grades and glioma cell lines through qRT-PCR. Our study provided comprehensive insights into the RCD roles in glioma, developed a robust RCD gene pair signature for predicting the prognosis of glioma patients, constructed a machine learning framework for screening the core candidates and identified the SLC43A3 as an oncogenic role and a prediction biomarker in glioblastoma.

Identification of a single cell-based signature for predicting prognosis risk and immunotherapy response in patients with glioblastoma

This study constructed a novel gene pair signature based on bulk and single-cell sequencing samples in relative expression order within the samples. The subsequent analysis included glioma samples from Xiangya Hospital. Gene pair signatures possessed a solid ability to predict the prognosis of glioblastoma and pan-cancer. Samples having different malignant biological hallmarks were distinguished by the algorithm, with the high gene pair score group featuring classic copy number variations, oncogenic mutations, and extensive hypomethylation, mediating poor prognosis. The increased gene pair score group with a poorer prognosis demonstrated significant enrichment in tumor and immune-related signaling pathways while presenting immunological diversity. The remarkable infiltration of M2 macrophages in the high gene pair score group was validated by multiplex immunofluorescence, suggesting that combination therapies targeting adaptive and innate immunity may serve as a therapeutic option. Overall, a gene pair signature applicable to predict prognosis hopefully provides a reference to guide clinical practice.

Advancing wide implementation of precision oncology: A liquid nitrogen-free snap freezer preserves molecular profiles of biological samples

PURPOSE

In precision oncology, tumor molecular profiles guide selection of therapy. Standardized snap freezing of tissue biospecimens is necessary to ensure reproducible, high-quality samples that preserve tumor biology for adequate molecular profiling. Quenching in liquid nitrogen (LN₂ ) is the golden standard method, but LN₂ has several limitations. We developed a LN₂ -independent snap freezer with adjustable cold sink temperature. To benchmark this device against the golden standard, we compared molecular profiles of biospecimens.

METHODS

Cancer cell lines and core needle normal tissue biopsies from five patients' liver resection specimens were used to compare mass spectrometry (MS)-based global phosphoproteomic and RNA sequencing profiles and RNA integrity obtained by both freezing methods.

RESULTS

Unsupervised cluster analysis of phosphoproteomic and transcriptomic profiles of snap freezer versus LN₂ -frozen K562 samples and liver biopsies showed no separation based on freezing method (with Pearson's r 0.96 (range 0.92-0.98) and >0.99 for K562 profiles, respectively), while samples with +2 h bench-time formed a separate cluster. RNA integrity was also similar for both snap freezing methods. Molecular profiles of liver biopsies were clearly identified per individual patient regardless of the applied freezing method. Two to 25 s freezing time variations did not induce profiling differences in HCT116 samples.

CONCLUSION

The novel snap freezer preserves high-quality biospecimen and allows identification of individual patients' molecular profiles, while overcoming important limitations of the use of LN₂ . This snap freezer may provide a useful tool in clinical cancer research and practice, enabling a wider implementation of (multi-)omics analyses for precision oncology.

FFPE-Based NGS Approaches into Clinical Practice: The Limits of Glory from a Pathologist Viewpoint

The introduction of next-generation sequencing (NGS) in the molecular diagnostic armamentarium is deeply changing pathology practice and laboratory frameworks. NGS allows for the comprehensive molecular characterization of neoplasms, in order to provide the best treatment to oncologic patients. On the other hand, NGS raises technical issues and poses several challenges in terms of education, infrastructures and costs. The aim of this review is to give an overview of the main NGS sequencing platforms that can be used in current molecular diagnostics and gain insights into the clinical applications of NGS in precision oncology. Hence, we also focus on the preanalytical, analytical and interpretative issues raised by the incorporation of NGS in routine pathology diagnostics.

Development and Performance of a CD8 Gene Signature for Characterizing Inflammation in the Tumor Microenvironment across Multiple Tumor Types

Across multiple tumor types, immune checkpoint inhibitors (ICIs) have demonstrated clinical benefit to patients with cancer, yet there is a need to identify predictive biomarkers of response to these therapies. A multiparameter gene expression profiling-based tumor inflammation assay may offer robust characterization of the tumor microenvironment, thereby extending the utility of single-gene analysis or immunohistochemistry (IHC) in predicting response to ICIs. The authors interrogated 1778 commercially procured, formalin-fixed, paraffin-embedded samples using gene expression profiling and pathology-assisted digital CD8 IHC. A machine-learning approach was used to develop gene expression signatures that predicted CD8⁺ immune cell abundance as surrogates for tumor inflammation in melanoma and squamous cell carcinoma of the head and neck samples. An assay for a 16-gene CD8 signature was developed and analytically validated across 12 tumor types. CD8 signature scores correlated with CD8 IHC in a platform-independent manner, and inflammation prevalence was similar between assay methods for all tumor types except prostate cancer and small cell lung cancer. In retrospective analyses, CD8 signature scores were associated with progression-free survival and overall survival with nivolumab in patients with urothelial carcinoma from CheckMate 275. This study demonstrated that the CD8 signature assay can be used to accurately quantify CD8⁺ immune cell abundance in the tumor microenvironment and has potential clinical utility for determining patients with cancer likely to respond to ICIs.

Pathologists at the Leading Edge of Optimizing the Tumor Tissue Journey for Diagnostic Accuracy and Molecular Testing

OBJECTIVES

Tumor biomarker analyses accompanying immuno-oncology therapies are coupled with a tumor tissue journey aiming to guide tissue procurement and allow for accurate diagnosis and delivery of test results. The engagement of pathologists in the tumor tissue journey is essential because they are able to link the preanalytic requirements of this process with pathologic evaluation and clinical information, ultimately influencing treatment decisions for patients with cancer. The aim of this review is to provide suggestions on how cancer diagnosis and the delivery of molecular test results may be optimized, based on the needs and available resources of institutions, by placing the tumor tissue journey under the leadership of pathologists.

METHODS

Literature searches on PubMed and personal experience provided the necessary material to satisfy the objectives of this review.

RESULTS

Pathologists are usually involved across many steps of the tumor tissue journey and have the requisite knowledge to ensure its efficiency.

CONCLUSIONS

The expansion of oncology diagnostic testing emphasizes the need for pathologists to acquire a leadership role in the multidisciplinary effort to optimize the accuracy, completeness, and delivery of diagnoses guiding personalized treatments.

Identification of EMT-related high-risk stage II colorectal cancer and characterisation of metastasis-related genes

Background

Our laboratory previously reported an individual-level prognostic signature for patients with stage II colorectal cancer (CRC). However, this signature was not applicable for RNA-sequencing datasets. In this study, we constructed a robust epithelial-to-mesenchymal transition (EMT)- related gene pair prognostic signature.

Methods

Based on EMT-related genes, metastasis-associated gene pairs were identified between metastatic and non-metastatic samples. Then, we selected prognosis-associated gene pairs, which were significantly correlated with disease-free survival of stage II CRC using multivariate Cox regression model, as the EMT-related prognosis signature.

Results

An EMT-related signature composed of fifty-one gene pairs (51-GPS) for prediction-relapse risk of patients with stage II CRC was developed, whose prognostic efficiency was validated in independent datasets. Moreover, 51-GPS achieved better predictive performance than other reported signatures, including a commercial signature Oncotype Dx colon cancer and an immune-related gene pair signature. Besides, EMT-related functional gene sets achieved high enrichment scores in high-risk samples. Especially, loss-of-function antisense approach showed that DEGs between the predicted two clusters were metastasis-related.

Conclusions

The EMT-related gene pair signature can identify the high relapse-risk patients with stage II CRC, which can facilitate individualised management of patients.

Association of tumour and stroma PD-1, PD-L1, CD3, CD4 and CD8 expression with DCB and OS to nivolumab treatment in NSCLC patients pre-treated with chemotherapy

BACKGROUND

Immune checkpoint inhibitors are most beneficial in patients with high tumour PD-L1 expression. However, the use of PD-L1 expression is not straightforward. We investigated PD-L1 expression and immune cell (IC) infiltrates in non-small-cell lung cancer (NSCLC) patients treated with nivolumab.

METHODS

Tumour tissue specimens of 139 NSCLC patients were scored for tumour/stromal PD-L1 and various IC expression markers, and associated with durable clinical benefit (DCB) and overall survival (OS).

RESULTS

Median OS was higher for patients with high stromal infiltration of CD8⁺ ICs (9.0 months) compared with patients with low and intermediate infiltration (both 5.0 months, p = 0.035) and for patients with high infiltration of stromal CD4⁺ ICs (9.0 months) compared with patients with low and intermediate infiltration (both 5.0 months, p = 0.010) and this was confirmed in the validation cohort. Post hoc analyses showed that biopsies taken after the last line of chemotherapy (ACT) were predictive for DCB and OS, whereas samples obtained before the last line of chemotherapy (BCT) were not.

CONCLUSIONS

Stromal infiltration of ICs can predict response to PD-1-directed immunotherapy in NSCLC patients. Interestingly, we found differences in the predictive value of IC markers between the ACT and BCT biopsies, suggesting that chemotherapy might influence the immune microenvironment.

Reference genome and annotation updates lead to contradictory prognostic predictions in gene expression signatures: a case study of resected stage I lung adenocarcinoma

RNA-sequencing enables accurate and low-cost transcriptome-wide detection. However, expression estimates vary as reference genomes and gene annotations are updated, confounding existing expression-based prognostic signatures. Herein, prognostic 9-gene pair signature (GPS) was applied to 197 patients with stage I lung adenocarcinoma derived from previous and latest data from The Cancer Genome Atlas (TCGA) processed with different reference genomes and annotations. For 9-GPS, 6.6% of patients exhibited discordant risk classifications between the two TCGA versions. Similar results were observed for other prognostic signatures, including IRGPI, 15-gene and ORACLE. We found that conflicting annotations for gene length and overlap were the major cause of their discordant risk classification. Therefore, we constructed a prognostic 40-GPS based on stable genes across GENCODE v20-v30 and validated it using public data of 471 stage I samples (log-rank P < 0.0010). Risk classification was still stable in RNA-sequencing data processed with the newest GENCODE v32 versus GENCODE v20-v30. Specifically, 40-GPS could predict survival for 30 stage I samples with formalin-fixed paraffin-embedded tissues (log-rank P = 0.0177). In conclusion, this method overcomes the vulnerability of existing prognostic signatures due to reference genome and annotation updates. 40-GPS may offer individualized clinical applications due to its prognostic accuracy and classification stability.

A Qualitative Transcriptional Signature for Predicting Extreme Resistance of ER-Negative Breast Cancer to Paclitaxel, Doxorubicin, and Cyclophosphamide Neoadjuvant Chemotherapy

For estrogen receptor (ER)-negative breast cancer patients, paclitaxel (P), doxorubicin (A) and cyclophosphamide (C) neoadjuvant chemotherapy (NAC) is the standard therapeutic regimen. Pathologic complete response (pCR) and residual disease (RD) are common surrogate measures of chemosensitivity. After NAC, most patients still have RD; of these, some partially respond to NAC, whereas others show extreme resistance and cannot benefit from NAC but only suffer complications resulting from drug toxicity. Here we developed a qualitative transcriptional signature, based on the within-sample relative expression ordering (REO) of gene pairs, to identify extremely resistant samples to PAC NAC. Using gene expression data for ER-negative breast cancer patients including 113 pCR samples and 137 RD samples from four datasets, we selected 61 gene pairs with reversal REO patterns between the two groups as the resistance signature, denoted as NR61. Samples with more than 37 signature gene pairs that had the same REO patterns within the extremely resistant group were defined as having extreme resistance; otherwise, they were considered responders. In the GSE25055 and GSE25065 dataset, the NR61 signature could correctly identify 44 (97.8%) of the 45 pCR samples and 22 (95.7%) of the 23 pCR samples as responder samples, respectively; it also identified 13 (16.9%) of 77 RD samples and 8 (21.1%) of 38 RD samples as extremely resistant samples, respectively. Survival analysis showed that the distant relapse-free survival (DRFS) time of the 14 extremely resistant cases was significantly shorter than that of the 108 responders (P < 0.01; HR = 3.84; 95% CI = 1.91–7.70) in GSE25055. Similar results were obtained in GSE25065. Moreover, in the integrated data of the two datasets with 94 responders and 21 extremely resistant samples identified from RD patients, the former had significantly longer DRFS than the latter (P < 0.01; HR = 2.22; 95% CI = 1.26–3.90). In summary, our signature could effectively identify patients who completely respond to PAC NAC, as well as cases of extreme resistance, which can assist decision-making on the clinical therapy for these patients.

Impact of different stabilization methods on RT-qPCR results using human lung tissue samples

Aiming to increase the reproducibility of biomedical research results, biobanks obtain human tissues of the highest quality and carry out different storage methods adapted to the needs of analytical technique to be performed by the biomedical researchers. However, there is much controversy and little data concerning the real impact of different stabilization methods on tissue quality, integrity and functionality of derived biomolecules. The influence of four stabilization methods [RNAlater (RNL), snap freezing (SF), snap freezing using Optimal Cutting Tissue compound (SF-OCT) and formalin-fixed paraffin-embedded (FFPE)] on RNA quality and integrity was evaluated in paired samples of lung tissue. RNA integrity was evaluated through PCR-endpoint assays amplifying six fragments of different length of the HPRT1 gene and RNA Integrity Number (RIN). To evaluate the difference of tissue functionality among the stabilization methods tested, RT-qPCRs were performed focusing on the differential expression of the HPRT1, SNRPD3 and Jun genes. RNA from the samples preserved with the RNL or SF-OCT method showed better integrity compared to SF and FFPE, measured by PCR-endpoint and RT-qPCR assays. However, only statistically significant differences were observed between the RNA from FFPE and other stabilization methods when gene expression of HPRT1, SNRPD3 and Jun housekeeping genes were determined by RT-qPCR. For the three mentioned genes, Cq and RIN values were highly correlated. The present work describes the fragility of SF samples, being critical the moment just before RNA extraction, although further experiments of tissue RNA are needed. Standardization pre-analytic workflow can lead to improved reproducibility between biomedical research studies. The present study demonstrated clear evidences about the impact of the stabilization method on RNA derived from lung human tissue samples.

Pathology and Biobanking

Biobanks are units where high quality and long-term protection of biomaterials is maintained. This system, in which biological materials and data are systematically recorded and stored, is a unique resource for the study of the pathophysiology of disease, the development of diagnostic biomarkers, and working with human tissues for the potential discovery of targeted therapeutic agents. At this point, the pathology unit plays a unifying and complementary role between the clinical and core disciplines and offers optimal management of the patients' biomaterials for diagnostic and research projects. The aim of this article is to present general information with regard to a biobank constructed for the storage of tumor tissue and blood biospecimens. Ethical issues (informed consent, protection of confidentiality and privacy, and secondary use of biospecimens) and the information technology system (collection, systematic recording, backup and protection of clinical information) are important issues in biobanking. The selection of freezers to be used in storage (mechanical freezers, liquid-vapor nitrogen tanks), and if mechanical freezers are preferred the establishment of the relevant infrastructure and support team (such as additional power units for protection from power outages), the preservation of materials by aliquoting in different freezers, ensuring financing so as to afford the cost of the infrastructure, and implementation of all these dynamics while adhering to international guidelines are of the utmost importance.

In search of an evidence-based strategy for quality assessment of human tissue samples: report of the tissue Biospecimen Research Working Group of the Spanish Biobank Network

The purpose of the present work is to underline the importance of obtaining a standardized procedure to ensure and evaluate both clinical and research usability of human tissue samples. The study, which was carried out by the Biospecimen Science Working Group of the Spanish Biobank Network, is based on a general overview of the current situation about quality assurance in human tissue biospecimens. It was conducted an exhaustive review of the analytical techniques used to evaluate the quality of human tissue samples over the past 30 years, as well as their reference values if they were published, and classified them according to the biomolecules evaluated: (i) DNA, (ii) RNA, and (iii) soluble or/and fixed proteins for immunochemistry. More than 130 publications released between 1989 and 2019 were analysed, most of them reporting results focused on the analysis of tumour and biopsy samples. A quality assessment proposal with an algorithm has been developed for both frozen tissue samples and formalin-fixed paraffin-embedded (FFPE) samples, according to the expected quality of sample based on the available pre-analytical information and the experience of the participants in the Working Group. The high heterogeneity of human tissue samples and the wide number of pre-analytic factors associated to quality of samples makes it very difficult to harmonize the quality criteria. However, the proposed method to assess human tissue sample integrity and antigenicity will not only help to evaluate whether stored human tissue samples fit for the purpose of biomarker development, but will also allow to perform further studies, such as assessing the impact of different pre-analytical factors on very well characterized samples or evaluating the readjustment of tissue sample collection, processing and storing procedures. By ensuring the quality of the samples used on research, the reproducibility of scientific results will be guaranteed.

A qualitative transcriptional signature for determining the grade of colorectal adenocarcinoma

Histological grading (HG) is an important prognostic factor of colorectal adenocarcinoma (CRAC): the high-grade CRAC patients have poorer prognosis after tumor resection. Especially, the high-grade stage II CRAC patients are recommended to receive adjuvant chemotherapy. Due to the subjective nature of HG assessment, it is difficult to achieve consistency among pathologists, which brings patients uncertain grading outcomes and inappropriate treatments. We developed a qualitative transcriptional signature based on the within-sample relative expression orderings (REOs) of gene pairs to discriminate high-grade and low-grade CRAC. Using the stage II-III CRAC samples, we detected gene pairs with stable REOs in the high-grade samples and reversal stable REOs in the low-grade samples, and retained the gene pairs whose specific REO patterns were significantly associated with the disease-free survival of patients by univariate Cox regression model. Then, we used a forward-backward searching procedure to extract gene pairs with the highest concordance index as the final grading signature. Finally, 9 gene pairs (9-GPS) were developed to divide CRAC patients into high-grade and low-grade groups. With the signature, there were more differential expression characteristics between reclassified high-grade and low-grade groups. Significant difference of prognosis between the classified two group patients could be seen in four independent datasets. Additionally, genomic analyses showed that the classified high-grade groups were characterized by hypermutation while classified low-grade groups were characterized by frequent copy number alternations. In conclusion, the 9-GPS can provide an objective and robust grading assessment for CRAC patients, which could assist clinical treatment decision.

Deleterious effects of formalin-fixation and delays to fixation on RNA and miRNA-Seq profiles

The National Cancer Institute conducted the Biospecimen Pre-analytical Variables (BPV) study to determine the effects of formalin fixation and delay to fixation (DTF) on the analysis of nucleic acids. By performing whole transcriptome sequencing and small RNA profiling on matched snap-frozen and FFPE specimens exposed to different delays to fixation, this study aimed to determine acceptable delays to fixation and proper workflow for accurate and reliable Next-Generation Sequencing (NGS) analysis of FFPE specimens. In comparison to snap-freezing, formalin fixation changed the relative proportions of intronic/exonic/untranslated RNA captured by RNA-seq for most genes. The effects of DTF on NGS analysis were negligible. In 80% of specimens, a subset of RNAs was found to differ between snap-frozen and FFPE specimens in a consistent manner across tissue groups; this subset was unaffected in the remaining 20% of specimens. In contrast, miRNA expression was generally stable across various formalin fixation protocols, but displayed increased variability following a 12 h delay to fixation.

Cold Ischemia Score: An mRNA Assay for the Detection of Extended Cold Ischemia in Formalin-Fixed, Paraffin-Embedded Tissue

Although there are thousands of formalin-fixed paraffin-embedded (FFPE) tissue blocks potentially available for scientific research, many are of questionable quality, partly due to unknown preanalytical variables. We analyzed FFPE tissue biospecimens as part of the National Cancer Institute (NCI) Biospecimen Preanalytical Variables program to identify mRNA markers denoting cold ischemic time. The mRNA was extracted from colon, kidney, and ovary cancer FFPE blocks (40 patients, 10-12 hr fixation time) with 1, 2, 3, and 12 hr cold ischemic times, then analyzed using qRT-PCR for 23 genes selected following a literature search. No genes tested could determine short ischemic times (1-3 hr). However, a combination of three unstable genes normalized to a more stable gene could generate a "Cold Ischemia Score" that could distinguish 1 to 3 hr cold ischemia from 12 hr cold ischemia with 62% sensitivity and 84% specificity.

Mechanisms and Measurement of Changes in Gene Expression

Research on gene expression (GE) provides insights into the physiology of a cell or group of cells at a given point in time. Studies of changes in GE can be used to identify patients at higher risk for various medical conditions, a higher symptom burden, and/or the adverse consequences associated with various treatments. The aims of this article are as follows: (1) to describe the different types of RNA transcripts, (2) to describe the processes involved in GE (i.e., RNA transcription, epigenetics, and posttranscriptional modifications), (3) to describe common sources of variation in GE, (4) to describe the most common methods used to measure GE, and (5) to discuss factors to consider when choosing tissue for a GE study. This article begins with an overview of the mechanisms involved in GE. Then, the factors that can influence the findings from GE experiments (e.g., tissue specificity, host age, host gender, and time of sample collection) are described and potential solutions are presented. This article concludes with a discussion of how the types of tissue used in GE studies can affect study findings. Given that the costs associated with the measurement of changes in GE are decreasing and the methods to analyze GE data are becoming easier to use, nurse scientists need to understand the basic principles that underlie any GE study.

Transcriptional signatures for coupled predictions of stage II and III colorectal cancer metastasis and fluorouracil-based adjuvant chemotherapy benefit

The current study suggests that the identification of predictive signatures of fluorouracil (5-FU) response for stage II and III colorectal cancer (CRC) could be confounded by chemotherapy-irrelevant low relapse risk. Using the samples of patients with stage II and III CRC who were treated with curative surgery only, we identified a signature with which to predict chemotherapy-irrelevant relapse risk for patients after curative surgery. By applying this signature to the samples of patients with stage II and III CRC who were treated with 5-FU-based adjuvant chemotherapy (ACT) after surgery, we predicted the relapse risk if treated with surgery only. From high-risk samples, we further identified another signature with which to predict therapeutic benefit from 5-FU-based ACT. On the basis of the relative expression orderings of gene pairs, a postsurgery relapse risk signature that consisted of 44 gene pairs was developed and verified in 3 independent data sets. A 5-FU therapeutic benefit signature that consisted of 4 gene pairs was then developed to predict the response of 5-FU-based ACT for those patients with high relapse risk after curative surgery. The signature was verified in 4 independent datasets. For patients with stage II and III CRC, the coupled signatures can first identify patients with high relapse risk after curative surgery, then predict therapeutic benefit from 5-FU-based ACT.-Song, K., Guo, Y., Wang, X., Cai, H., Zheng, W., Li, N., Song, X., Ao, L., Guo, Z., Zhao, W. Transcriptional signatures for coupled predictions of stage II and III colorectal cancer metastasis and fluorouracil-based adjuvant chemotherapy benefit.

Multi-Omics Analysis Reveals a HIF Network and Hub Gene EPAS1 Associated with Lung Adenocarcinoma

Recent technological advancements have permitted high-throughput measurement of the human genome, epigenome, metabolome, transcriptome, and proteome at the population level. We hypothesized that subsets of genes identified from omic studies might have closely related biological functions and thus might interact directly at the network level. Therefore, we conducted an integrative analysis of multi-omic datasets of non-small cell lung cancer (NSCLC) to search for association patterns beyond the genome and transcriptome. A large, complex, and robust gene network containing well-known lung cancer-related genes, including EGFR and TERT, was identified from combined gene lists for lung adenocarcinoma. Members of the hypoxia-inducible factor (HIF) gene family were at the center of this network. Subsequent sequencing of network hub genes within a subset of samples from the Transdisciplinary Research in Cancer of the Lung-International Lung Cancer Consortium (TRICL-ILCCO) consortium revealed a SNP (rs12614710) in EPAS1 associated with NSCLC that reached genome-wide significance (OR = 1.50; 95% CI: 1.31-1.72; p = 7.75 × 10^-9). Using imputed data, we found that this SNP remained significant in the entire TRICL-ILCCO consortium (p = .03). Additional functional studies are warranted to better understand interrelationships among genetic polymorphisms, DNA methylation status, and EPAS1 expression.

Individualized predictive signatures for 5-fluorouracil-based chemotherapy in right- and left-sided colon cancer

5‐Fluorouracil (5‐FU)‐based adjuvant chemotherapy (ACT) is widely used for the treatment of colon cancer. Colon cancers with different primary tumor locations are clinically and molecularly distinct, implied through their response to 5‐FU‐based ACT. In this work, using 69 and 133 samples of patients with stage II‐III right‐sided and left‐sided colon cancer (RCC and LCC) treated with post‐surgery 5‐FU‐based ACT, we preselected gene pairs whose relative expression orderings were significantly correlated with the disease‐free survival of patients by univariate Cox proportional hazards model. Then, from the identified prognostic‐related gene pairs, a forward‐stepwise selection algorithm was formulated to search for an optimal subset of gene pairs that resulted in the highest concordance index, referred to as the gene pair signature (GPS). We identified prognostic signatures, 3‐GPS and 5‐GPS, for predicting response to 5‐FU‐based ACT of patients with RCC and LCC, respectively, which were validated in independent datasets of GSE14333 and GSE72970. With the aid of the signatures, the transcriptional and genomic characteristics between the predicted responders and non‐responders were explored. Notably, both in RCC and LCC, the predicted responders to 5‐FU‐based ACT were characterized by hypermutation, whereas the predicted non‐responders were characterized by frequent copy number alternations. Finally, in comparison with the established relative expression ordering‐based signature, which was developed without considering the differences between RCC and LCC, the newly proposed signatures had a better predictive performance. In conclusion, 3‐GPS or 5‐GPS can robustly predict response to 5‐FU‐based ACT for patients with RCC or LCC, respectively, in an individual level.

The role of the pathology department in the preanalytical phase of molecular analyses

After introducing the new molecules for the treatment of patients with tumoral pathology, the therapeutical decision will be taken depending on the molecular profile performed upon the harvested tissues. This major modification makes the molecular and morphological analysis an essential part in the clinical management of patients and the pathologist plays an important role in this process. The quality and reproducibility of the results are imperative today and they depend on both the reliability of the molecular techniques and the quality of the tissue we use in the process. Also, the genomics and proteomics techniques, used increasingly often, require high-quality tissues, and pathology laboratories play a very significant role in the management of all phases of this process. In this paper the parameters which must be followed in order to obtain optimal results within the techniques which analyze nucleic acids and proteins were reviewed.

Robust transcriptional tumor signatures applicable to both formalin-fixed paraffin-embedded and fresh-frozen samples

Formalin-fixed paraffin-embedded (FFPE) samples represent a valuable resource for clinical researches. However, FFPE samples are usually considered an unreliable source for gene expression analysis due to the partial RNA degradation. In this study, through comparing gene expression profiles between FFPE samples and paired fresh-frozen (FF) samples for three cancer types, we firstly showed that expression measurements of thousands of genes had at least two-fold change in FFPE samples compared with paired FF samples. Therefore, for a transcriptional signature based on risk scores summarized from the expression levels of the signature genes, the risk score thresholds trained from FFPE (or FF) samples could not be applied to FF (or FFPE) samples. On the other hand, we found that more than 90% of the relative expression orderings (REOs) of gene pairs in the FF samples were maintained in their paired FFPE samples and largely unaffected by the storage time. The result suggested that the REOs of gene pairs were highly robust against partial RNA degradation in FFPE samples. Finally, as a case study, we developed a REOs-based signature to distinguish liver cirrhosis from hepatocellular carcinoma (HCC) using FFPE samples. The signature was validated in four datasets of FFPE samples and eight datasets of FF samples. In conclusion, the valuable FFPE samples can be fully exploited to identify REOs-based diagnostic and prognostic signatures which could be robustly applicable to both FF samples and FFPE samples with degraded RNA.

Robust transcriptional signatures for low-input RNA samples based on relative expression orderings

Background

It is often difficult to obtain sufficient quantity of RNA molecules for gene expression profiling under many practical situations. Amplification from low-input samples may induce artificial signals.

Results

We compared the expression measurements of low-input mRNA samples, from 25 pg to 1000 pg mRNA, which were amplified and profiled by Smart-seq, DP-seq and CEL-seq techniques using the Illumina HiSeq 2000 platform, with those of the paired high-input (50 ng) mRNA samples. Even with 1000 pg mRNA input, we found that thousands of genes had at least 2 folds-change of expression levels in the low-input samples compared with the corresponding paired high-input samples. Consequently, a transcriptional signature based on quantitative expression values and determined from high-input RNA samples cannot be applied to low-input samples, and vice versa. In contrast, the within-sample relative expression orderings (REOs) of approximately 90% of all the gene pairs in the high-input samples were maintained in the paired low-input samples with 1000 pg input mRNA molecules. Similar results were observed in the low-input total RNA samples amplified and profiled by the Whole-Genome DASL technique using the Illumina HumanRef-8 v3.0 platform. As a proof of principle, we developed REOs-based signatures from high-input RNA samples for discriminating cancer tissues and showed that they can be robustly applied to low-input RNA samples.

Conclusions

REOs-based signatures determined from the high-input RNA samples can be robustly applied to samples profiled with the low-input RNA samples, as low as the 1000 pg and 250 pg input samples but no longer stable in samples with less than 250 pg RNA input to a certain degree.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4280-7) contains supplementary material, which is available to authorized users.

An individualized gene expression signature for prediction of lung adenocarcinoma metastases

Our laboratory previously reported an individual‐level signature consisting of nine gene pairs, named 9‐GPS. This signature was developed by training on microarray expression data and validated using three independent integrated microarray data sets, with samples of stage I non‐small‐cell lung cancer after complete surgical resection. In this study, we first validated the cross‐platform robustness of 9‐GPS by demonstrating that 9‐GPS could significantly stratify the overall survival of 213 stage I lung adenocarcinoma (LUAD) patients detected with RNA‐sequencing platform in The Cancer Genome Atlas (TCGA; log‐rank P = 0.0318, C‐index = 0.55). Applying 9‐GPS to all the 423 stage I‐IV LUAD samples in TCGA, the predicted high‐risk samples were significantly enriched with clinically diagnosed metastatic samples (Fisher's exact test, P = 0.0015). We further modified the voting rule of 9‐GPS and found that the modified 9‐GPS had a better performance in predicting metastasis states (Fisher's exact test, P < 0.0001). With the aid of the modified 9‐GPS for reclassifying the metastasis states of patients with LUAD, the reclassified metastatic samples presented clearer transcriptional and genomic characteristics compared to the reclassified nonmetastatic samples. Finally, regulator network analysis identified TP53 and IRF1 with frequent genomic aberrations in the reclassified metastatic samples, indicating their key roles in driving tumor metastasis. In conclusion, 9‐GPS is a robust signature for identifying early‐stage LUAD patients with potential occult metastasis. This occult metastasis prediction was associated with clear transcriptional and genomic characteristics as well as the clinical diagnoses.

Epigenetic sampling effects: nephrectomy modifies the clear cell renal cell cancer methylome

PURPOSE

Currently, it is unclear to what extent sampling procedures affect the epigenome. Here, this phenomenon was evaluated by studying the impact of artery ligation on DNA methylation in clear cell renal cancer.

METHODS

DNA methylation profiles between vascularised tumour biopsy samples and devascularised nephrectomy samples from two individuals were compared. The relevance of significantly altered methylation profiles was validated in an independent clinical trial cohort.

RESULTS

We found that six genes were differentially methylated in the test samples, of which four were linked to ischaemia or hypoxia (REXO1L1, TLR4, hsa-mir-1299, ANKRD2). Three of these genes were also found to be significantly differentially methylated in the validation cohort, indicating that the observed effects are genuine.

CONCLUSION

Tissue ischaemia during normal surgical removal of tumour can cause epigenetic changes. Based on these results, we conclude that the impact of sampling procedures in clinical epigenetic studies should be considered and discussed, particularly after inducing hypoxia/ischaemia, which occurs in most oncological surgery procedures through which tissues are collected for translational research.

Biobanking in genomic medicine

CONTEXT

Genomic medicine requires the identification of biomarkers and therapeutic targets, which in turn, requires high-quality biospecimens. Achieving high-quality biospecimens requires implementing standard operating procedures to control the variations of preanalytic variables in biobanking. Currently, most biobanks do not control the variations of preanalytic variables when collecting, processing, and storing their biospecimens. However, those variations have been shown to affect the quality of biospecimens and gene expression profiling.

OBJECTIVE

To identify evidence-based preanalytic parameters that can be applied and those parameters that need further study.

DATA SOURCES

We searched the Biospecimen Research and PubMed databases using defined key words. We retrieved and reviewed 212 articles obtained through those searches. We included 58 articles (27%) according to our inclusion and exclusion criteria for this review.

CONCLUSION

-Preanalytic variables in biobanking can degrade the quality of biospecimens and alter gene expression profiling. Variables that require further study include the effect of surgical manipulation; the effect of warm ischemia; the allowable duration of delayed specimen processing; the optimal type, duration, and temperature of preservation and fixation; and the optimal storage duration of formalin-fixed, paraffin embedded specimens in a fit-for-purpose approach.

Immunologic checkpoint blockade in lung cancer

Despite the availability of radiotherapy, cytotoxic agents, and targeted agents, a high unmet medical need remains for novel therapies that improve treatment outcomes in patients with lung cancer who are ineligible for surgical resection. Building upon the early promise shown with general immunostimulatory agents, immuno-oncology is at the forefront of research in this field, with several novel agents currently under investigation. In particular, agents targeting immune checkpoints, such as the cytotoxic T-lymphocyte antigen-4 (CTLA-4) receptor and programmed death-1 (PD-1) receptor, have shown in early clinical trials potential for improving tumor responses and survival in patients with non-small cell lung cancer (NSCLC). Here, we examine the rationale for targeting immune checkpoints in lung cancer and review the clinical data from studies with immune checkpoint inhibitors currently in development. The challenges associated with optimizing treatment with these agents in lung cancer also are discussed.

A tissue retrieval and postharvest processing regimen for rodent reproductive tissues compatible with long-term storage on the international space station and postflight biospecimen sharing program

Collection and processing of tissues to preserve space flight effects from animals after return to Earth is challenging. Specimens must be harvested with minimal time after landing to minimize postflight readaptation alterations in protein expression/translation, posttranslational modifications, and expression, as well as changes in gene expression and tissue histological degradation after euthanasia. We report the development of a widely applicable strategy for determining the window of optimal species-specific and tissue-specific posteuthanasia harvest that can be utilized to integrate into multi-investigator Biospecimen Sharing Programs. We also determined methods for ISS-compatible long-term tissue storage (10 months at −80°C) that yield recovery of high quality mRNA and protein for western analysis after sample return. Our focus was reproductive tissues. The time following euthanasia where tissues could be collected and histological integrity was maintained varied with tissue and species ranging between 1 and 3 hours. RNA quality was preserved in key reproductive tissues fixed in RNAlater up to 40 min after euthanasia. Postfixation processing was also standardized for safe shipment back to our laboratory. Our strategy can be adapted for other tissues under NASA's Biospecimen Sharing Program or similar multi-investigator tissue sharing opportunities.

Efficient utilization of EBUS-TBNA samples for both diagnosis and molecular analyses

BACKGROUND

The assessment of an increasing number of molecular markers is becoming a standard requirement from endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) specimens. However, it is unclear how many needle passes should be performed and the amount of lung cancer cells that should be sent for molecular analyses. The objective of this study was to determine if it is feasible to divide the material obtained by EBUS-TBNA to allow for molecular analysis without compromising the accuracy of mediastinal staging.

OBJECTIVE

We aimed to determine if dividing EBUS-TBNA specimens has a negative impact on either histopathological diagnosis or molecular analysis.

METHODS

EBUS-TBNA was performed in 249 enlarged lymph nodes. Negative or ambiguous histopathological results were confirmed by surgical means and clinical follow-up over 6 months. The tissue obtained by EBUS-TBNA was placed onto a glass slide and divided for histopathological workup and molecular analysis. The number of passes was recorded. Both the accuracy of the mediastinal lymph node staging and the applicability of the sample division for molecular analysis were assessed.

RESULTS

Each lymph node was punctured an average of 3.18 times and division of the obtained material for diagnosis and molecular analysis was feasible in all cases. The sensitivity and accuracy of the mediastinal lymph node staging were 96.6% and 97.6%, respectively. A cytokeratin (CK)-19-mRNA concentration-based molecular test was feasible in 74.1% of cases.

CONCLUSION

Dividing EBUS-TBNA samples for both histopathological diagnosis and molecular testing is feasible and does not compromise the accuracy of mediastinal staging. This method may be an alternative to taking additional needle passes for molecular analyses.

Impact of delay to cryopreservation on RNA integrity and genome-wide expression profiles in resected tumor samples

The quality of tissue samples and extracted mRNA is a major source of variability in tumor transcriptome analysis using genome-wide expression microarrays. During and immediately after surgical tumor resection, tissues are exposed to metabolic, biochemical and physical stresses characterized as “warm ischemia”. Current practice advocates cryopreservation of biosamples within 30 minutes of resection, but this recommendation has not been systematically validated by measurements of mRNA decay over time. Using Illumina HumanHT-12 v3 Expression BeadChips, providing a genome-wide coverage of over 24,000 genes, we have analyzed gene expression variation in samples of 3 hepatocellular carcinomas (HCC) and 3 lung carcinomas (LC) cryopreserved at times up to 2 hours after resection. RNA Integrity Numbers (RIN) revealed no significant deterioration of mRNA up to 2 hours after resection. Genome-wide transcriptome analysis detected non-significant gene expression variations of −3.5%/hr (95% CI: −7.0%/hr to 0.1%/hr; p = 0.054). In LC, no consistent gene expression pattern was detected in relation with warm ischemia. In HCC, a signature of 6 up-regulated genes (CYP2E1, IGLL1, CABYR, CLDN2, NQO1, SCL13A5) and 6 down-regulated genes (MT1G, MT1H, MT1E, MT1F, HABP2, SPINK1) was identified (FDR <0.05). Overall, our observations support current recommendation of time to cryopreservation of up to 30 minutes and emphasize the need for identifying tissue-specific genes deregulated following resection to avoid misinterpreting expression changes induced by warm ischemia as pathologically significant changes.

Testing an aflatoxin B1 gene signature in rat archival tissues

Archival tissues from laboratory studies represent a unique opportunity to explore the relationship between genomic changes and agent-induced disease. In this study, we evaluated the applicability of qPCR for detecting genomic changes in formalin-fixed, paraffin-embedded (FFPE) tissues by determining if a subset of 14 genes from a 90-gene signature derived from microarray data and associated with eventual tumor development could be detected in archival liver, kidney, and lung of rats exposed to aflatoxin B1 (AFB1) for 90 days in feed at 1 ppm. These tissues originated from the same rats used in the microarray study. The 14 genes evaluated were Adam8, Cdh13, Ddit4l, Mybl2, Akr7a3, Akr7a2, Fhit, Wwox, Abcb1b, Abcc3, Cxcl1, Gsta5, Grin2c, and the C8orf46 homologue. The qPCR FFPE liver results were compared to the original liver microarray data and to qPCR results using RNA from fresh frozen liver. Archival liver paraffin blocks yielded 30 to 50 μg of degraded RNA that ranged in size from 0.1 to 4 kB. qPCR results from FFPE and fresh frozen liver samples were positively correlated (p ≤ 0.05) by regression analysis and showed good agreement in direction and proportion of change with microarray data for 11 of 14 genes. All 14 transcripts could be amplified from FFPE kidney RNA except the glutamate receptor gene Grin2c; however, only Abcb1b was significantly upregulated from control. Abundant constitutive transcripts, S18 and β-actin, could be amplified from lung FFPE samples, but the narrow RNA size range (25-500 bp length) prevented consistent detection of target transcripts. Overall, a discrete gene signature derived from prior transcript profiling and representing cell cycle progression, DNA damage response, and xenosensor and detoxication pathways was successfully applied to archival liver and kidney by qPCR and indicated that gene expression changes in response to subchronic AFB1 exposure occurred predominantly in the liver, the primary target for AFB1-induced tumors. We conclude that an evaluation of gene signatures in archival tissues can be an important toxicological tool for evaluating critical molecular events associated with chemical exposures.