Tumor Adjacent Normal Tissue Samples Research Articles

Abstract 1603: Genomic transcriptomic evolution in TRACERx lung cancer and metastasis

Abstract Background: Genomic intra-tumor heterogeneity (ITH) drives tumor evolution, leading to immune evasion and resistance to therapy. Emerging evidence implicates the transcriptome as a source of important variation that impacts tumor phenotype. Here, we perform a genomic-transcriptomic analysis of intra-tumor transcriptomic diversity upon 941 tumor regions taken from 357 TRACERx non-small cell lung cancers (NSCLC) across primary and metastatic disease subjected to high-depth bulk DNA and RNA sequencing, as well as 91 tumor-adjacent normal tissue samples. Results: Genomic and transcriptomic diversity are linked across primary and metastatic disease, with expression signatures of proliferation being enriched in the metastasis seeding subclone of the primary tumor relative to non-metastasis seeding subclones. Copy-number independent allele-specific expression (CN-independent ASE), a source of transcriptome-specific diversity, affects 1% (± 0.5%) of genes and is underpinned by aberrant allele-specific methylation (OR=7.58, p≤2.2x10-16), thus providing a window to the NSCLC epigenomic landscape. Driver mutations in chromatin remodellers and histone modifiers, in particular SETD2 and KDM5C, are associated with increased global levels of CN-independent ASE (p=0.0001). In genomically stable tumors, high levels of CN-independent ASE are linked to expression signatures consistent with genomic instability and proliferation (R=0.58, p=0.001), highlighting convergence between the genome and transcriptome in tumor evolution. For the first time, we uncover mutational signatures of RNA editing. Analysis of their activity links the expression of ADAR and APOBEC enzymes to editing processes revealing otherwise hidden APOBEC activity within tumors at sampling (RNA APOBEC activity identified in 188 tumor regions (32%) without evidence of DNA APOBEC activity). RNA editing activity is shared between primary tumors and paired metastasis, but not paired tumor-adjacent normal tissue, suggestive of heritability of this somatic transcriptional process. Finally, we combine multiple measures of genomic and transcriptomic variation in a multi-region approach to define important variation within cancer genes. We illustrate examples that would be missed with a purely genomic focus and demonstrate genomic-transcriptomic parallel evolution, converging on disruption to single cancer genes, such as FAT1 and APC, in different regions of a tumor. Conclusions: This work highlights the importance of the transcriptome during tumor evolution, as well as the power of integrative multi-omic assessments of ITH, and provides novel insight into the role of transcriptomic variation in lung cancer. Citation Format: James R. M. Black, Carlos Martinez-Ruiz, Clare Puttick, Jonas Demeulemeester, Elizabeth Larose Cadieux, Kerstin Thol, Thomas P. Jones, Selvaraju Veeriah, Cristina Naceur-Lombardelli, Andrew Rowan, Sophia Ward, Michelle Dietzen, Ariana Huebner, Maise Al Bakir, Miljana Tanic, Thomas B. Watkins, Emilia L. Lim, Ali M. Al Rashed, Daniel E. Cook, Rachel Rosenthal, Gareth Wilson, Alexander M. Frankell, Nnennaya Kanu, Kevin Litchfield, Nicolai J. Birkbak, Allan Hackshaw, Stephan Beck, Peter Van Loo, Mariam Jamal-Hanjani, the lung TRACERx Consortium, Charles Swanton, Nicholas McGranahan. Genomic transcriptomic evolution in TRACERx lung cancer and metastasis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1603.

Inconsistency in the expression pattern of a five-lncRNA signature as a potential diagnostic biomarker for gastric cancer patients in bioinformatics and in vitro.

Objective(s):Due to diagnosis of gastric cancer in advanced stages as well as its poor prognosis, finding biomarkers is essential. In this study, using the TCGA RNAseq data of gastric cancer patients, we evaluated the diagnostic value of lncRNAs that had differential expression.Materials and Methods:We evaluated P-value, FDR, and log fold change for whole transcripts. Next, by comparison of the RNAseq gene names with the total known lncRNA names, we identified differential expressed lncRNAs. Following this, specificity and sensitivity for lncRNAs coming from the previous step were calculated. For more confirmation, we predicted target genes and performed GO and KEGG signaling pathway analysis. In the end, we examined reliability and consistency of expression of this signature in three gastric cancer cell lines and one of them in twenty tumors and tumor-adjacent normal tissue samples using qRT-PCR.Results:Five lncRNAs had proper sensitivity and specificity and had target genes involved in cancer-related signaling pathways; however, they showed different expression patterns in TCGA data and in vitro.Conclusion:The results of our study demonstrated that the five-lncRNAs PART1, UCA1, DIRC3, HOTAIR, and HOXA11AS require more investigation to be confirmed as diagnostic biomarkers in gastric cancer.

Autophagy-Related Signatures as Prognostic Indicators for Hepatocellular Carcinoma.

BackgroundHepatocellular carcinoma (HCC) is the most common and deadly type of liver cancer. Autophagy is the process of transporting damaged or aging cellular components into lysosomes for digestion and degradation. Accumulating evidence implies that autophagy is a key factor in tumor progression. The aim of this study was to determine a panel of novel autophagy-related prognostic markers for liver cancer.MethodsWe conducted a comprehensive analysis of autophagy-related gene (ARG) expression profiles and corresponding clinical information based on The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. The univariate Cox proportional regression model was used to screen candidate autophagy-related prognostic genes. In addition, a multivariate Cox proportional regression model was used to identify five key prognostic autophagy-related genes (ATIC, BAX, BIRC5, CAPNS1, and FKBP1A), which were used to construct a prognostic signature. Real-time qPCR analysis was used to evaluate the expression levels of ARGs in 20 surgically resected HCC samples and matched tumor-adjacent normal tissue samples. In addition, the effect of FKBP1A on autophagy and tumor progression was determined by performing in vitro and in vivo experiments.ResultsBased on the prognostic signature, patients with liver cancer were significantly divided into high-risk and low-risk groups in terms of overall survival (OS). A subsequent multivariate Cox regression analysis indicated that the prognostic signature remained an independent prognostic factor for OS. The prognostic signature possessing a better area under the curve (AUC) displayed better performance in predicting the survival of patients with HCC than other clinical parameters. Furthermore, FKBP1A was overexpressed in HCC tissues, and knockdown of FKBP1A impaired cell proliferation, migration, and invasion through the PI3K/AKT/mTOR signaling pathway.ConclusionThis study provides a prospective biomarker for monitoring outcomes of patients with HCC.

Integrin Beta 1 Promotes Glioma Cell Proliferation by Negatively Regulating the Notch Pathway.

In this study, genes associated with the Notch signaling pathway in gliomas were analyzed using bioinformatics and in vitro experiments. The dataset GSE22772 was downloaded from the Gene-Cloud of Biotechnology Information database. Differentially expressed genes (DEGs) between short hairpin RNA (shRNA) intervening glioma cells and control cells were screened using the unpaired t test. Functional enrichment analysis was performed, and coexpression network was analyzed to identify the most important genes associated with the Notch signaling pathway. Integrin beta 1 (ITGB1) mRNA and protein levels in clinical glioma tumor samples and tumor adjacent normal tissue samples were analyzed using quantitative real-time PCR and immunohistochemistry, respectively. The relationship between ITGB1 expression and the prognosis of patients with gliomas was analyzed using the Kaplan-Meier curve. ITGB1 interference expression cell line U87 and ITGB1 overexpressing cell line were established using sh-ITGB1 and oe-ITGB1 plasmids, respectively. MTT and colony formation assays were used to detect changes in the proliferation of glioma cells. Moreover, western blotting was used to detect the expression of Notch and Hey1. A total of 7,962 DEGs were screened between shRNA intervening glioma cells and control cells, which were mainly associated with spliceosome, proteoglycans in cancer, focal adhesion, and the Notch signaling pathway. ITGB1 showed the highest expression in the coexpression network. The mRNA and protein expression of ITGB1 in glioma tumor samples was significantly higher than that in tumor adjacent normal tissue samples (p < 0.05). Overall survival time of patients in the ITGB1 low-expression group was significantly longer than that in the ITGB1 high-expression group, indicating that ITGB1 expression negatively correlated with the prognosis. Fluorescence microscopy, qRT-PCR, and western blotting confirmed the transfection efficiency of ITGB1 overexpression and interference expression in U251 and U87 cells. The MTT and colony formation assays indicated that U87 cell proliferation was significantly inhibited after intervention with ITGB1 (p < 0.05), and overexpression of ITGB1 significantly promoted U251 cell proliferation (p < 0.05). In addition, the expression of Notch and Hey1 proteins was significantly decreased after ITGB1 intervention (p < 0.05), and their expression was significantly upregulated after ITGB1 overexpression (p < 0.05). ITGB1 expression in glioma tissues was significantly higher than that in adjacent normal tissues and was negatively correlated with the survival time of patients. Therefore, ITGB1 can significantly promote proliferation of glioma cells via feedback regulation of the Notch signaling pathway.

Abstract 1597: The landscape of PD1-PD-L1 axis in the context of immune cells: Tumors versus stromal compartments

Abstract Introduction: Immune response, tolerance, suppression, and resistance are the result of a complex dynamic interaction comprising PD1-PD-L1 axis in the context of immune cells (ICs) involving tumor cells, and anti/pro-tumor immune-cells of the stromal compartment. Aim: Here we present the landscape of PD1-PD-L1 axis in the context of CD3, CD4, CD8, PD1, FOXP3, and IL12RB2 positive ICs in the tumor (T) and the tumor-adjacent normal (TAN) tissues from patients with ovarian cancers (OC), and lung cancers (LC). Methods: The study was approved by Avera IRB. Surgically resected paired T and TAN tissue samples (from patients with OC and LC) were used to identify CD3 (ab16669), CD4 (ab133616), CD8 (ab85792), FOXP3 ([236A/E7], PD1 (ab137132), IL12RB2 (NBP1-85983), CD68 (Dako. #M0876), CD163 (Cell Signaling #93498) in ICs and PD-L1 (Clone 22C3; Dako) in T cells &amp; tumor-associated macrophages (TAMs). Tonsil tissue was used for the IHC validation. Paired specimens were morphologically evaluated by H&amp;E stain &amp; Ki-67, cl-caspase 3. Anatomic pathological evaluation for the diagnosis of the disease was carried out by a Pathologist. Results: Expression of CD3, CD4, CD8, PD1, and FOXP3 was heterogeneous, with each tumor presenting an individual pattern of distribution of ICs. However in most tumor samples, the distribution of ICs was of tumor-cooperating phenotypes. PD-L1 expression in tumors did not correlate with any other ICs of the tumor-microenvironment. In TAN tissues from OC, PD1-PD-L1 staining was absent. While macrophages in TAN tissue from LC were moderately positive for PD-L1. In T tissue from OC and LC, PD1-PD-L1 staining was only present in the stroma, lymphocytes, and absent in the tumor compartments while PD-L1 staining was identified only in the macrophages. Tumoricidal cells were rarely observed within the tumor compartment of T tissues from OC. The tumors cells from LC was only positive for PD-L1. Conclusion: Using dual stain of PD1 and PD-L1, we present for the first time, the co-distribution pattern of PD1-PD-L1 axis in the context of the expression of CD3, CD4, CD8, FOXP3 T cells as well as CD68, and CD163 positive TAMs in the paired sample of a T tissue and its TAN tissue in LC and OC. The relationship between the PD1-PD-L1 axis and the expression of IL12 Receptor in the context of immune-landscape is being worked out and will be presented in the meeting. Citation Format: Xiaoqian Lin, Raed Sulaiman, Jennifer C. Aske, Paul Meyer, Luis RojasEspaillat, David Starks, Pradip De, Nandini Dey. The landscape of PD1-PD-L1 axis in the context of immune cells: Tumors versus stromal compartments [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1597.

Abstract 4579: A comparative immune-landscape within tumor-microenvironment: Pattern of distribution of immune cells in tumor versus tumor-adjacent normal tissues

Abstract Introduction: Tumor and immune cells can determine each other’s fate. Immunotherapy targets either the PD1-PD-L1 axis which modulates immune-checkpoints or the cytotoxic CTLA4-mediated immune invasion of tumor cells. Thus the success of cellular-dynamics based immunotherapy depends on the makeup of the immune landscape within a given tumor as compared to its adjacent normal tissue. Aim: We hypothesize that as the immune-environment directly or indirectly shapes and determines the fate, drug response, and progression of an established tumor, the immune-landscape of the tumor-microenvironment will be characteristically different from that of the tumor-adjacent normal tissue. We studied the distribution pattern of selected immune cells in the tumor and tumor-adjacent normal tissues from patients with cancers of lung and ovary. Methods: The study was approved by Avera IRB. FFPE tumor and tumor-adjacent normal tissue samples in pairs from surgically resected tissues were used for IHC to identify CD3 (Anti-CD3 [SP7] ab16669), CD4 ([EPR6855] ab133616), CD8 (ab85792), CD68 (Dako. #M0876), CD163 (Cell Signaling #93498), FOXP3 ([236A/E7] ab20034) in immune cells and PD-L1 (Clone 22C3; Dako. #M3653) in tumor cells &amp; tumor-associated macrophages. Tonsil tissue was used for the IHC validation. Tumor and normal cells from paired specimens were compared using H&amp;E stain &amp; Ki-67, pS6RP, cl-caspase 3, CIP2A, and CD31 IHC-stains based on criteria of evaluation for individual protein(s). Anatomic pathological evaluation for the diagnosis of the disease was carried out by Pathologist. Results: IHC expression of CD3, CD4, CD8, CD68, CD163, and FOXP3 in immune cells and PD-L1 in tumor cells was found heterogeneous. Although each tumor presented an individual pattern of distribution of immune cells, in most tumor samples, the identified immune cells were of tumor-cooperating phenotypes. Tumoricidal cells were rarely observed within the tumor compartment, and barely present in spaces, while tumor-friendly immune cells were frequent. In lung tumors, alveolar macrophages were predominantly of tumor-cooperating M2 types (CD68+/CD163+), whereas tumoricidal M1 macrophages (CD68+) were either absent or rare. The expression of PD-L1 in tumors did not correlate participation of any other immune cells in the tumor-microenviroment. Lung macrophages were highly positive for PD-L1 in which the intensity ranged from punctate to high. Conclusion: We present for the first time, a tissue-based analysis of distribution pattern of different immune cells in histological subtypes of the lung and ovarian cancers, in the tumor and tumor-adjacent normal tissues. The relationship between the immune-landscape of the tumor and tumor-adjacent normal tissue is being worked out and will be presented in the meeting. Citation Format: Xiaoqian Lin, Read Sulaiman, Jennifer Aske, Paul Mayer, Luis Rojas-Espaillat, David Starks, Pradip De, Brian Leyland-Jones, Nandini Dey. A comparative immune-landscape within tumor-microenvironment: Pattern of distribution of immune cells in tumor versus tumor-adjacent normal tissues [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4579.

Genome-wide methylation analysis identifies novel prognostic methylation markers in colon adenocarcinoma.

Previous studies have indicated that abnormal methylation is a critical and early event in the pathogenesis of most types of human cancer, which contributes to tumorigenesis. However, there has been little focus on the potential of DNA methylation patterns as predictive markers for the prognosis of colon adenocarcinoma (COAD). In the present study, a genome-wide comparative analysis of DNA methylation profiles was performed between 315 COAD samples and 38 matched tumor-adjacent normal tissue samples. A total of 675 differentially methylated regions (DMRs) associated with 630 genes were identified, including 654 hypermethylated regions (UMRs) and 21 hypomethylated regions, which were capable of distinguishing COAD samples from non-malignant tissue samples. Although most of the DMRs appeared to be located within the gene body or promoter regions, UMRs were mostly located within CpG islands. Functional analysis suggested that genes associated with DMRs were enriched in many of the core cancer-signaling pathways known to be important in COAD biology. A survival analysis was also performed, which identified 7 DMRs as potential candidate markers with the ability to classify patients into high and low-risk groups with significantly different overall survival. The present study provides a better understanding of the molecular mechanisms underlying COAD, and demonstrates the utility of aberrant DNA methylation in the prognosis of COAD.

The relationship between MMP-2 and MMP-9 expression levels with breast cancer incidence and prognosis.

The relationship between the expression levels of matrix metalloproteinase-2 (MMP-2) and MMP-9 and breast cancer prognosis was studied. Two breast cancer cell lines (MDA-MB-231 and MCF-7) and one human normal breast cell line (HS578Bst) were investigated. Fluorescence real-time reverse transcription-polymerase chain reaction (RT-PCR) and western blotting were used to detect cellular mRNA and protein MMP-2 and MMP-9 expression levels. Breast cancer tissue samples from 80 patients and tumor-adjacent normal tissue samples from 40 patients were collected, and MMP-2 and MMP-9 expression in these samples were examined using immunohistochemistry (IHC). The relationship of MMP-2 and MMP-9 expression levels with breast cancer patient clinicopathological parameters and prognosis was analyzed. RT-PCR and western blot results showed that MMP-2 and MMP-9 mRNA and protein expression levels were significantly higher in MDA-MB-231 and MCF-7 cells than in HS578Bst cells. A high expression of MMP-2 and MMP-9 was found in 83.75% (67/80) and 78.75% (63/80) of breast cancer tissue samples, respectively. MMP-2 and MMP-9 expression in breast cancer tissues were significantly different from that in tumor-adjacent normal tissues (p<0.01). MMP-2 and MMP-9 expression levels in breast cancer tissues were correlated with lymph node metastasis and tumor staging. Single factor survival analysis showed that MMP-2 and MMP-9 were factors influencing breast cancer prognosis. MMP-2 and MMP-9 are highly expressed in breast cancer tissues and are closely related to lymph node metastasis and tumor staging. MMP-2 and MMP-9 can be used as reference indices for guiding breast cancer prognosis and treatment.

Long non-coding RNA LINC01296 is a potential prognostic biomarker in patients with colorectal cancer.

Colorectal cancer (CRC), one of the most malignant cancers, is currently the fourth leading cause of cancer deaths worldwide. Recent studies indicated that long non-coding RNAs (lncRNAs) could be robust molecular prognostic biomarkers that can refine the conventional tumor-node-metastasis staging system to predict the outcomes of CRC patients. In this study, the lncRNA expression profiles were analyzed in five datasets (GSE24549, GSE24550, GSE35834, GSE50421, and GSE31737) by probe set reannotation and an lncRNA classification pipeline. Twenty-five lncRNAs were differentially expressed between CRC tissue and tumor-adjacent normal tissue samples. In these 25 lncRNAs, patients with higher expression of LINC01296, LINC00152, and FIRRE showed significantly better overall survival than those with lower expression (P < 0.05), suggesting that these lncRNAs might be associated with prognosis. Multivariate analysis indicated that LINC01296 overexpression was an independent predictor for patients' prognosis in the test datasets (GSE24549, GSE24550) (P = 0.001) and an independent validation series (GSE39582) (P = 0.027). Our results suggest that LINC01296 could be a novel prognosis biomarker for the diagnosis of CRC.