Pan Cancer Research Articles

Immune Infiltration of MMP14 in Pan Cancer and Its Prognostic Effect on Tumors.

BackgroundMatrix metalloproteinase 14 (MMP14) is a member of the MMP family, which interacts with tissue inhibitors of metalloproteinase (TIMPs), and is involved in normal physiological functions such as cell migration, invasion, metastasis, angiogenesis, and proliferation, as well as tumor genesis and progression. However, there has been a lack of relevant reports on the effect of MMP14 across cancers. This study aims to explore the correlation between MMP14 and pan-cancer prognosis, immune infiltration, and the effects of pan-cancer gene mismatch repair (MMR), microsatellite instability (MSI), tumor mutational burden (TMB), DNA methylation, and immune checkpoint genes.MethodsIn this study, we used bioinformatics to analyze data from multiple databases, including The Cancer Genome Atlas (TCGA), ONCOMINE, and Kaplan–Meier plotter. We investigated the relationship between the expression of MMP14 in tumors and tumor prognosis, the relationship between MMP14 expression and tumor cell immune infiltration, and the relationship between MMR gene MMR, MSI, TMB, DNA methylation, and immune checkpoint genes.ResultsMMP14 expression is highly associated with the prognosis of a variety of cancers and tumor immune invasion and has important effects on pan oncologic MMR, MSI, TMB, DNA methylation, and immune checkpoint genes.ConclusionMMP14 is highly correlated with tumor prognosis and immune invasion and affects the occurrence and progression of many tumors. All of these results fully indicate that MMP14 may be a biomarker for the prognosis, diagnosis, and treatment of many tumors and provide new ideas and direction for subsequent tumor immune research and treatment strategies.

HCG18 Participates in Vascular Invasion of Hepatocellular Carcinoma by Regulating Macrophages and Tumor Stem Cells.

ObjectivesTo identify key genes involved in vascular invasion in hepatocellular carcinoma (HCC), to describe their regulatory mechanisms, and to explore the immune microenvironment of HCC.MethodologyIn this study, the genome, transcriptome, and immune microenvironment of HCC were assessed by using multi-platform data from The Cancer Genome Atlas (n = 373) and GEO data (GSE149614). The key regulatory networks, transcription factors and core genes related to vascular invasion and prognosis were explored based on the CE mechanism. Survival analysis and gene set enrichment were used to explore pathways related to vascular invasion. Combined with single-cell transcriptome data, the distribution of core gene expression in various cells was observed. Cellular communication analysis was used to identify key cells associated with vascular invasion. Pseudo-temporal locus analysis was used to explore the regulation of core genes in key cell phenotypes. The influence of core genes on current immune checkpoint therapy was evaluated and correlations with tumor stem cell scores were explored.ResultsWe obtained a network containing 1,249 pairs of CE regulatory relationships, including 579 differential proteins, 28 non-coding RNAs, and 37 miRNAs. Three key transcription factors, ILF2, YBX1, and HMGA1, were identified, all regulated by HCG18 lncRNA. ScRNAseq showed that HCG18 co-localized with macrophages and stem cells. CIBERSORTx assessed 22 types of immune cells in HCC and found that HCG18 was positively correlated with M0 macrophages, while being negatively correlated with M1 and M2 macrophages, monocytes, and dendritic cells. Cluster analysis based on patient prognosis suggested that regulating phenotypic transformation of macrophages could be an effective intervention for treating HCC. At the same time, higher expression of HCG18, HMGA1, ILF2, and YBX1 was associated with a higher stem cell score and less tumor differentiation. Pan cancer analysis indicated that high expression of HCG18 implies high sensitivity to immune checkpoint therapy.ConclusionHCG18 participates in vascular invasion of HCC by regulating macrophages and tumor stem cells through three key transcription factors, YBX1, ILF2, and HMGA1.

PARP-Targeted Auger Therapy in p53 Mutant Colon Cancer Xenograft Mouse Models.

Despite Auger electrons being highly appealing due to their short-range and high linear energy transfer to surrounding tissues, the progress in the field has been limited due to the challenge in delivering a therapeutic dose within the close proximity of cancer cell's DNA. Here, we demonstrate that the PARP inhibitor 123I-MAPi is a viable agent for the systemic administration and treatment of p53 mutant cancers. Significantly, minimal off-site toxicity was observed in mice administered with up to 74 MBq of 127I-PARPi. Taken together, these results lay the foundation for future clinical evaluation and broader preclinical investigations. By harnessing the scaffold of the PARP inhibitor Olaparib, we were able to deliver therapeutic levels of Auger radiation to the site of human colorectal cancer xenograft tumors after systemic administration. In-depth toxicity studies analyzed blood chemistry levels and markers associated with specific organ toxicity. Finally, p53+/+ and p53-/- human colorectal cancer cell lines were evaluated for the ability of 123I-MAPi to induce tumor growth delay. Toxicity studies demonstrate that both 123I-MAPi and its stable isotopologue, 127I-PARPi, have no significant off-site toxicity when administered systemically. Analysis following 123I-MAPi treatment confirmed its ability to induce DNA damage at the site of xenograft tumors when administered systemically. Finally, we demonstrate that 123I-MAPi generates a therapeutic response in p53-/-, but not p53+/+, subcutaneous xenograft tumors in mouse models. Taken together, these results represent the first example of a PARP Auger theranostic agent capable of delivering a therapeutic dose to xenograft human colorectal cancer tumors upon systemic administration without causing significant toxicity to surrounding mouse organs. Moreover, it suggests that a PARP Auger theranostic can act as a targeted therapeutic for cancers with mutated p53 pathways. This landmark goal paves the way for clinical evaluation of 123I-MAPi for pan cancer therapeutics.

Integrative analysis the characterization of peroxiredoxins in pan-cancer

BackgroundPeroxiredoxins (PRDXs) are an antioxidant enzymes protein family involved in several biological functions such as differentiation, cell growth. In addition, previous studies report that PRDXs play critical roles in the occurrence and development of carcinomas. However, few studies have conducted systematic analysis of PRDXs in cancers. Therefore, the present study sought to explore the molecular characteristics and potential clinical significance of PRDX family members in pan cancer and further validate the function of PRDX6 in bladder urothelial carcinoma (BLCA).MethodsA comprehensive analysis of PRDXs in 33 types of cancer was performed based on the TCGA database. This involved an analysis of mRNA expression profiles, genetic alterations, methylation, prognostic values, potential biological pathways and target drugs. Moreover, both the gain and loss of function strategies were used to assess the importance and mechanism of PRDX6 in the cell cycle of BLCA.ResultAnalysis showed abnormal expression of PRDX1-6 in several types of cancer compared to normal tissues. Univariate Cox proportional hazard regression analysis showed that expression levels of PRDX1, PRDX4 and PRDX6 were mostly associated with poor survival of OS, DSS and PFI, and PRDX2 and PRDX3 with favorable survival. In addition, the expression of PRDX genes were positively correlated with CNV and negatively with methylation. Moreover, analysis based on PharmacoDB dataset showed that the augmented levels of PRDX1, PRDX3 and PRDX6 were significantly correlated with EGFR/VEGFR inhibitor drugs. Furthermore, knocking down of PRDX6 inhibited growth of cancer cells through the JAK2-STAT3 in bladder cell lines.ConclusionsPRDXs are potential biomarkers and therapeutic targets for several carcinomas, especially for BLCA. In addition, PRDX6 could regulate proliferation of cancer cell via JAK2-STAT3 pathway and involve into the process of cell cycle in BLCA.

Abstract 2151: Neuroendocrine cancer cells have changed HOX code during trans-differentiation

Abstract Background: HOX genes encode Homeobox-containing proteins. There are 39 HOX genes organized into 4 clusters in human. The nested and partially overlapping expression of HOX genes in an anatomic region can determine its tissue specificity, which is termed as “HOX code”. In this study, we examined the expression of HOX genes in neuroendocrine prostate cancer (NEPCa), an aggressive subtype prostate cancer that arises from prostate adenocarcinoma (AdPCa) trough trans-differentiation. Methods: The HOX genes expression data were extracted from Cancer Cell Line Encyclopedia (CCLE) dataset. All in silico analysis were performed by using R language. Immunohistochemistry (IHC), dual immunofluorescence staining, Western blot and RT-qPCR were conducted to access the expression of HOXs. Results: Using the HOXs' mRNA expression data from CCLE, we generated HOX codes for 25 different types of tissues. These HOX codes were validated in TCGA pan cancer. By calculating the Pearson correlation, we were able to use 9 HOX codes including prostatic HOX code to identify the tissue origins of the cancer samples. Further, we found that in prostate cancer, the NEPCa samples have lost prostatic HOX code while majority of the AdPCa samples maintain the prostatic HOX code. The expression of HOXB13, the most prominent HOX expressed in prostatic tissues, was increased in AdPCa along with PCa progression but was decreased in NEPCa. Similarly, we found that in breast cancer, a sub-group of samples correlated well with the HOX code of mammary gland, but the rest did not. By comparing the differentially expressed genes in these two subgroups of samples, we found that the neuroendocrine markers including CHGA, CHGB and SYP were higher in HOX code-negative samples compared with HOX code-positive ones. Additionally, we observed a similar phenomenon in colorectal cancer samples: The expression of neurogenesis genes were enriched in HOX code-negative subgroup. Conclusions: 1) The expression of HOXB13 is decreased in NEPCa. 2) NEPCa has changed HOX code, suggesting the loss of prostatic identity in these samples. 3) The association of neuroendocrine phenotype with the changes in HOX code is not limited to prostate cancer but also is observed in other types of cancer. Significance: The HOX codes we established can be used in pan cancer research to identify the tissue origins of cancer samples and to study the trans-differentiation of cancer cells. Funding: This study is supported by: The LSUHS Office of Research SEED awards, NIH R01 CA226285 and Feist-Weiller Cancer Center. Citation Format: Siyuan Cheng, Shu Yang, Yingli Shi, Runhua Shi, Yunshin Yeh, Xiuping Yu. Neuroendocrine cancer cells have changed HOX code during trans-differentiation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2151.

Abstract 327: High conversion library preparation with optimal hybridization capture panel design strategy in RNA-seq

Abstract RNA-seq is a powerful tool to detect tissue-specific gene expression, splicing, and genetic variations associated with disease states. However, current RNA-seq approaches have limitations due to poor signal from low-abundant transcripts. Furthermore, tissue-derived RNA samples are often highly degraded, thereby limiting gene detection and suffering from potential sequencing artifacts. Here we show that target capture of sequencing libraries tagged with unique molecular identifiers (UMIs) using the xGen™ Prism DNA library prep kit, optimized for low-input and degraded samples, can overcome these obstacles. Directional and UMI-tagged RNA-seq libraries were constructed with RNA extracted from a FFPE RNA Fusion Reference Standard and captured with different designs of the xGen Pan-Cancer Panel spiked with probes for fusion genes. The first design strategy used IDT's stocked Pan Cancer V1.5 panel targeted to gDNA coordinates. The second design involved extracting all associated RefSeq NM transcripts associated with the gene list. Probes were designed to each transcript and duplicate probes were removed based on exact sequence match. The third strategy leveraged a multi-strain design, which created probes from fasta inputs, but removed probes with 90% or greater homology. Normalized expression was highly correlated (> 85%) between captured and uncaptured samples regardless of rRNA depletion prior to library prep. Captured samples had a greater depth of coverage with over 90% on target bases. In addition, our panel design strategies identified low frequency fusions with deep sequencing regardless of rRNA depletion prior to library prep. The multi-strain design was more effective in reducing redundant capture probes compared the other design strategies. Enhanced coverage and PCR de-duplication with UMIs allowed us to reproducibly measure expression over a wide range of RNA inputs (5-500 ng). We show that target capture of RNA-seq libraries reliably maintains expression information present in uncaptured libraries while increasing coverage for poorly expressed genes and low frequency fusions. In addition, the target captured libraries without rRNA depletion prior to library prep have comparable on-target rate and target coverage with rRNA-depleted, target captured libraries. The addition of UMIs to differentiate between PCR duplicates and unique starting molecules also makes it possible to reliably analyze even highly amplified libraries. (For research use only). Citation Format: Tzu-Chun Chen, Katelyn Larkin, Shale Dames, Hsiao-Yun Huang, Kevin Lai, Jessica Sheu, Timothy Barnes, Katia Star, Manqing Hong, Bosun Min, Ryan Demeter, Ashley Dvorak, Ushati Das Chakravarty, Patrick Lau, Steven Henck. High conversion library preparation with optimal hybridization capture panel design strategy in RNA-seq [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 327.

The Cancer Genomic Atlas – “TO CONQUER CANCER”

The Cancer Genomic Atlas (TCGA) is a publicly accessible cancer data repository and tool that allows us to understand the molecular basis of cancer through the application of genomics and proteomics. So far, researchers have been able to diagnose 33 cancer types including 10 rare cancer types. The key features of TCGA are to make the data collection process publicly accessible for the better understanding of the molecular and genetic basis of cancer and its mechanism of action along with its prevention. Studies on different cancer types along with comprehensive pan cancer analysis have expanded the understanding and purpose of TCGA. Ever since its’ conceptualization, its’ high-throughput approach has provided a platform for the identification of genes and pathways involved in cancers and accurate classification of cancers.

Pan cancer analysis of the intra-tumoral microbiome’s correlation with racial disparities.

2519 Background: Microbiome composition can influence cancer development and is moderated by diet, hygiene, sanitation, and other environmental variables. For example, a Mediterranean diet could increase breast Lactobacillus abundance, while the gut microbiome changes dramatically with fructose intake. Recent studies have revealed correlations between microbial abundance and racial disparities in cancer. Given these reports, it is critical to examine whether environmental influences on the microbiome contribute to racial disparities in cancer incidence and prognosis. Methods: We examined the intra-tumoral microbiome in the lungs, breasts, bladder, colon, rectum, cervix, head and neck, prostate, and pancreas (n = 4,169). Raw tumor RNA sequencing data were downloaded from The Cancer Genome Atlas (TCGA) and aligned to bacterial genomes. Microbial abundance was correlated to race, ethnicity, and prognostic variables (Kruskal-Wallis test or Cox regression, p< 0.05). Results: We identified several microbes correlated with racial disparities for breast and bladder cancer, two microbes for lung squamous cell carcinoma, and one microbe for colon cancer. For breast cancer, African Americans have the highest mortality rate, followed by white Americans and Asian Americans. We found that four microbes, all under the order Burkholderiales, were positively correlated with poor prognosis and were most abundant in African Americans and least abundant in Asian Americans. Therefore, increased abundance of these microbes may contribute to the observed mortality differences between races. For bladder cancer, Asian Americans have the lowest incidence and mortality rates. Seven microbes, including two Geobacillus, two Pseudomonas, and two Burkholderiales, positively correlate with good prognosis and are upregulated in Asian Americans. High Pseudomonas fluorescens abundance is positively correlated with decreased risk of death (HR: 0.57, 95% CI: 0.38-0.85). High abundance of the Burkholderiales R. pickettii (HR: 0.62, 95% CI: 0.42-0.92) and V. paradoxus (HR: 0.59, 95% CI: 0.36-0.98) also exhibit the same trend. Geobacillus and Pseudomonas are both present in food, while Burkholderiales can cause nosocomial infections and are altered by diet. Conclusions: Our study is the most comprehensive to date investigating racial differences in the intra-tumoral microbiome. Our data serve as a starting point for exploring whether environmental influence of microbial abundance contributes to racial disparities in cancer.

Gene expression profiling in normal cytogenetic acute myeloid leukaemia of Malay patient

Background: Insight into recent molecular analyses of patients with acute myeloid leukaemia (AML) and a normal cytogenetic have revealed a striking heterogeneity with regard to the presence of acquired changes in gene expression. Nano String technology which is aimed to identify descriptive profiling of normal cytogenetic AML in differentially expressed genes involved in the different pathways in normal cytogenetic AML patients.
 Materials and method: Blood samples were obtained from eight at diagnosis patients with normal cytogenetics AML, two follow-up patients and two normal healthy controls prior to RNA extractions. RNA gene expression assay was performed using Nano Stringn Counter® Pan Cancer Pathway Panel (Nanostring Technologies, Seattle, Washington). Briefly, 100 ng of each total RNA sample was used as input into then Counter Pan Cancer Pathway Panel sample preparation. Data was extracted using then Counter RCC Collector and raw data output was imported into nSolver v2.6 analysis software for data analysis.
 Results: The age range was from 13-69 years, with a median age-range of 41 years. We found the most enriched up regulated genes in newly diagnosed normal cytogenetic AML enlisted MPO (7.25 log FC), FLT3 (5.02 log FC), MYCN (4.99 log FC), MYB (4.74 log FC), ITGA9 (4.48 log FC), KIT (4.41 log FC), MCM2 (3.47 log FC), RAD51 (3.40 log FC), CCNA2 (3.37 log FC) and PROM1 (3.24 log FC) which those commonly be found in AML cases. For highly expressed down regulated genes were GZMB (-5.80 log FC), IL8 (-5.79 log FC), TNFRSFSF10C (-5.03 log FC), LEF1 (-4.82 log FC), IL2RB (-4.70 log FC), IL7R (-4.44 log FC), BCL2A1 (-4.15 log FC), RASGRP1 (-4.13 log FC), IL1R2 (-4.00 log FC) and HSPA6 (-3.99 log FC).
 Discussion and conclusion: Nano String required smaller amounts of starting material, and can perform mRNA expression profiling with digital precision, therefore the results do not require further validation by another method. MPO expression was significantly associated with disease-free survival (DFS). Previous report demonstrated that the groups by the MPO expression in the intermediate cytogenetic risk group showed a significant difference in DFS (p<0.001). A study by Valk et al., (2004) showed FLT3, a hematopoietic growth factor receptor, is the most common molecular abnormality in AML. The presence of such mutations in FLT3 and elevated expression of the transcription factor EVI1 confer a poor prognosis. N-MYC expression levels in AML samples from patients with favorable, intermediate, or unfavorable prognosis were compared with that in CD34+ cells from four healthy bone marrow donors. The most highly down regulated gene in newly diagnosed AML goes to Granzyme B (GZMB) which involved in cytolytic activity that showed high correlation with other transcripts expressed in activated cytotoxic T lymphocytes (CTLs) and natural killer (NK) cells as well as lymphocyte activation-related gene validating it as a robust and specific metric of active cellular immunity. Increased expression of IL-8 and/or its receptors has been characterized in cancer cells, endothelial cells, infiltrating neutrophils, and tumor-associated macrophages, suggesting that IL-8 may function as a significant regulatory factor within the tumor microenvironment.
 Bangladesh Journal of Medical Science Vol.20(3) 2021 p.556-562

Gene Co-Expression Analysis of Human RNASEH2A Reveals Functional Networks Associated with DNA Replication, DNA Damage Response, and Cell Cycle Regulation.

Simple SummaryRNASEH2A is the catalytic subunit of the ribonuclease (RNase) H2 ternary complex that plays an important role in maintaining DNA stability in cells. Recent studies have shown that the RNASEH2A subunit alone is highly expressed in certain cancer cell types. Via a series of bioinformatics approaches, we found that RNASEH2A is highly expressed in human proliferative tissues and many cancers. Our analyses reveal a possible involvement of RNASEH2A in cell cycle regulation in addition to its well established role in DNA replication and DNA repair. Our findings underscore that RNASEH2A could serve as a biomarker for cancer diagnosis and a therapeutic target.Ribonuclease (RNase) H2 is a key enzyme for the removal of RNA found in DNA-RNA hybrids, playing a fundamental role in biological processes such as DNA replication, telomere maintenance, and DNA damage repair. RNase H2 is a trimer composed of three subunits, RNASEH2A being the catalytic subunit. RNASEH2A expression levels have been shown to be upregulated in transformed and cancer cells. In this study, we used a bioinformatics approach to identify RNASEH2A co-expressed genes in different human tissues to underscore biological processes associated with RNASEH2A expression. Our analysis shows functional networks for RNASEH2A involvement such as DNA replication and DNA damage response and a novel putative functional network of cell cycle regulation. Further bioinformatics investigation showed increased gene expression in different types of actively cycling cells and tissues, particularly in several cancers, supporting a biological role for RNASEH2A but not for the other two subunits of RNase H2 in cell proliferation. Mass spectrometry analysis of RNASEH2A-bound proteins identified players functioning in cell cycle regulation. Additional bioinformatic analysis showed that RNASEH2A correlates with cancer progression and cell cycle related genes in Cancer Cell Line Encyclopedia (CCLE) and The Cancer Genome Atlas (TCGA) Pan Cancer datasets and supported our mass spectrometry findings.

Integrative pan cancer analysis reveals epigenomic variation in cancer type and cell specific chromatin domains

Epigenetic mechanisms contribute to the initiation and development of cancer, and epigenetic variation promotes dynamic gene expression patterns that facilitate tumor evolution and adaptation. While the NCI-60 panel represents a diverse set of human cancer cell lines that has been used to screen chemical compounds, a comprehensive epigenomic atlas of these cells has been lacking. Here, we report an integrative analysis of 60 human cancer epigenomes, representing a catalog of activating and repressive histone modifications. We identify genome-wide maps of canonical sharp and broad H3K4me3 domains at promoter regions of tumor suppressors, H3K27ac-marked conventional enhancers and super enhancers, and widespread inter-cancer and intra-cancer specific variability in H3K9me3 and H4K20me3-marked heterochromatin domains. Furthermore, we identify features of chromatin states, including chromatin state switching along chromosomes, correlation of histone modification density with genetic mutations, DNA methylation, enrichment of DNA binding motifs in regulatory regions, and gene activity and inactivity. These findings underscore the importance of integrating epigenomic maps with gene expression and genetic variation data to understand the molecular basis of human cancer. Our findings provide a resource for mining epigenomic maps of human cancer cells and for identifying epigenetic therapeutic targets.

The Tumour Immune Infiltrations in Immune Checkpoint Inhibitor Therapeutic Efficacy: A Computational Retrospective Study

Background: Tumour immune microenvironment (TIME) are likely to be important determinants in sensitive to immune checkpoint inhibitors (ICI) treatment. However, a comprehensive analysis covers the complexity and diversity of the TIME and its influence on ICI therapeutic efficacy is still lacking. Methods: Data of 782 samples from 10 ICI clinical trials were collected. To infer 22 subsets of immune cells, CIBERSORTx was applied to bulk tumour transcriptomes. The associations between each cell fraction and response to ICI treatment, progression-free survival (PFS) and overall survival (OS) were evaluated, modelling cellular proportions as quartiles. Findings: Activity of interferon-γ pathway, cytolytic activity score and MHC score were associated with well prognosis in melanoma. Of the immune cells investigated, M1 macrophages, activated memory CD4+ T cells, T follicular helper (Tfh) cells and CD8+ T cells correlated with response, prolonged PFS and OS, while resting memory CD4+ T cells and resting masts cells associated with unfavourable prognosis within pan cancer and melanoma. Consensus clustering revealed four immune subgroups with distinct response to ICI therapy and survival patterns. A cluster with high proportions of infiltrated CD8+ T cells, activated memory CD4+ T cells, Tfh cells and low level of resting memory CD4+ T cells, exhibited higher tumour mutation burden and neoantigen load within melanoma, was conferred higher ratio of response and improved survival. Interpretation: The local systemic immune cellular difference associated with outcomes after ICI therapy. Further investigations of the tumour-infiltrating cellular immune response lay the foundation for achieving durable efficacy. Funding: This study was supported by the National Scientific Foundation of China (No. 31801121) and National Natural Science Foundation of Hunan (No. 2020JJ5879). Declaration of Interest: None to declare. Ethical Approval: This study has been approved by the Institute of Clinical Pharmacology, Central South University.

Pan cancer patterns of allelic imbalance from chromosomal alterations in 33 tumor types.

Somatic copy number alterations (SCNAs) serve as hallmarks of tumorigenesis and often result in deviations from one-to-one allelic ratios at heterozygous loci, leading to allelic imbalance (AI). The Cancer Genome Atlas (TCGA) reports SCNAs identified using a circular binary segmentation algorithm, providing segment mean copy number estimates from single-nucleotide polymorphism DNA microarray total intensities (log R ratio), but not allele-specific intensities ("B allele" frequencies) that inform of AI. Our approach provides more sensitive identification of SCNAs by modeling the "B allele" frequencies jointly, thereby bolstering the catalog of chromosomal alterations in this widely utilized resource. Here we present AI summaries for all 33 tumor sites in TCGA, including those induced by SCNAs and copy-neutral loss-of-heterozygosity (cnLOH). We identified AI in 94% of the tumors, higher than in previous reports. Recurrent events included deletions of 17p, 9q, 3p, amplifications of 8q, 1q, 7p, as well as mixed event types on 8p and 13q. We also observed both site-specific and pan-cancer (spanning 17p) cnLOH, patterns which have not been comprehensively characterized. The identification of such cnLOH events elucidates tumor suppressors and multi-hit pathways to carcinogenesis. We also contrast the landscapes inferred from AI- and total intensity-derived SCNAs and propose an automated procedure to improve and adjust SCNAs in TCGA for cases where high levels of aneuploidy obscured baseline intensity identification. Our findings support the exploration of additional methods for robust automated inference procedures and to aid empirical discoveries across TCGA.

Buffy Coat Immunotranscriptomics for Diagnosis of Malignant Pleural Mesothelioma

Malignant pleural mesothelioma is a highly aggressive tumor primarily caused by asbestos exposure and associated with poor clinical outcomes. The availability of a robust non-invasive test for the screening of asbestos-exposed subjects is therefore an important unmet clinical need. It is widely recognized that the immune system can play a fundamental role in the control of tumor growth within an organism. Simultaneously, the presence of cancer cells can activate different immune cells to undergo various phenotypic and functional changes. Buffy coat—a novel circulating microenvironment of leukocytes and platelets—may thus reflect critical immuno-oncologic activity, pathways, and molecular programs. We hypothesized the immunotranscriptome of circulating buffy coat could accurately distinguish malignant pleural mesothelioma from high-risk asbestos exposure. Buffy coat RNA was extracted from 84 patients having resection: 40 patients with malignant pleural mesothelioma and 44 patients with asbestos exposure. Gene expression profiling was performed using a Pan Cancer Immune Panel for 770 immune genes and cytokines, and significantly different genes between cohorts were selected to develop diagnostic models. Using 1000 loops of cross validation, a 37 gene signature separated malignant pleural mesothelioma from asbestos exposure with a mean validation AUCS of 0.925. Our buffy coat immunotranscriptomic signature is at least comparable to the most commonly used blood-based diagnostic biomarker for MPM, serum mesothelin-related peptide. In addition, immunophenotyping and pathway analysis of differentially expressed genes characterized MPM buffy coat as a relatively tumorigenic and immunosuppressive state. Several of the most differentially expressed genes encode proteins implicated in cancer development (e.g., CD63, CD44, ISG15, CD59, IL1R2, and TAPBP) and may hold clinical value as therapeutic targets. Larger studies on externally validated cohorts are needed to refine the signature for clinical relevance and develop a more robust diagnostic panel.

Clinical significance and immunogenomic landscape analyses of the immune cell signature based prognostic model for patients with breast cancer.

Breast cancer is one of the most common types of cancers and the leading cause of death from malignancy among women worldwide. Tumor-infiltrating lymphocytes are a source of important prognostic biomarkers for breast cancer patients. In this study, based on the tumor-infiltrating lymphocytes in the tumor immune microenvironment, a risk score prognostic model was developed in the training cohort for risk stratification and prognosis prediction in breast cancer patients. The prognostic value of this risk score prognostic model was also verified in the two testing cohorts and the TCGA pan cancer cohort. Nomograms were also established in the training and testing cohorts to validate the clinical use of this model. Relationships between the risk score, intrinsic molecular subtypes, immune checkpoints, tumor-infiltrating immune cell abundances and the response to chemotherapy and immunotherapy were also evaluated. Based on these results, we can conclude that this risk score model could serve as a robust prognostic biomarker, provide therapeutic benefits for the development of novel chemotherapy and immunotherapy, and may be helpful for clinical decision making in breast cancer patients.

36P Progression-free survival as a surrogate for overall survival in trials of immune checkpoint inhibitors in pan cancer evaluated by RECIST 1.1

36P Progression-free survival as a surrogate for overall survival in trials of immune checkpoint inhibitors in pan cancer evaluated by RECIST 1.1

Frequency and prognostic value of mutations associated with the homologous recombination DNA repair pathway in a large pan cancer cohort

PARP inhibitors have shown remarkable efficacy in the clinical management of several BRCA-mutated tumors. This approach is based on the long-standing hypothesis that PARP inhibition will impair the repair of single stranded breaks, causing synthetic lethality in tumors with loss of high-fidelity double-strand break homologous recombination. While this is now well accepted and has been the basis of several successful clinical trials, emerging evidence strongly suggests that mutation to several additional genes involved in homologous recombination may also have predictive value for PARP inhibitors. While this notion is supported by early clinical evidence, the mutation frequencies of these and other functionally related genes are largely unknown, particularly in cancers not classically associated with homologous recombination deficiency. We therefore evaluated the mutation status of 22 genes associated with the homologous recombination DNA repair pathway or PARP inhibitor sensitivity, first in a pan-cancer cohort of 55,586 patients, followed by a more focused analysis in The Cancer Genome Atlas cohort of 12,153 patients. In both groups we observed high rates of mutations in a variety of HR-associated genes largely unexplored in the setting of PARP inhibition, many of which were associated also with poor clinical outcomes. We then extended our study to determine which mutations have a known oncogenic role, as well as similar to known oncogenic mutations that may have a similar phenotype. Finally, we explored the individual cancer histologies in which these genomic alterations are most frequent. We concluded that the rates of deleterious mutations affecting genes associated with the homologous recombination pathway may be underrepresented in a wide range of human cancers, and several of these genes warrant further and more focused investigation, particularly in the setting of PARP inhibition and HR deficiency.

DeepHPV: a deep learning model to predict human papillomavirus integration sites.

Human papillomavirus (HPV) integrating into human genome is the main cause of cervical carcinogenesis. HPV integration selection preference shows strong dependence on local genomic environment. Due to this theory, it is possible to predict HPV integration sites. However, a published bioinformatic tool is not available to date. Thus, we developed an attention-based deep learning model DeepHPV to predict HPV integration sites by learning environment features automatically. In total, 3608 known HPV integration sites were applied to train the model, and 584 reviewed HPV integration sites were used as the testing dataset. DeepHPV showed an area under the receiver-operating characteristic (AUROC) of 0.6336 and an area under the precision recall (AUPR) of 0.5670. Adding RepeatMasker and TCGA Pan Cancer peaks improved the model performance to 0.8464 and 0.8501 in AUROC and 0.7985 and 0.8106 in AUPR, respectively. Next, we tested these trained models on independent database VISDB and found the model adding TCGA Pan Cancer performed better (AUROC: 0.7175, AUPR: 0.6284) than the model adding RepeatMasker peaks (AUROC: 0.6102, AUPR: 0.5577). Moreover, we introduced attention mechanism in DeepHPV and enriched the transcription factor binding sites including BHLHA15, CHR, COUP-TFII, DMRTA2, E2A, HIC1, INR, NPAS, Nr5a2, RARa, SCL, Snail1, Sox10, Sox3, Sox4, Sox6, STAT6, Tbet, Tbx5, TEAD, Tgif2, ZNF189, ZNF416 near attention intensive sites. Together, DeepHPV is a robust and explainable deep learning model, providing new insights into HPV integration preference and mechanism. Availability: DeepHPV is available as an open-source software and can be downloaded from https://github.com/JiuxingLiang/DeepHPV.git, Contact: huzheng1998@163.com, liangjiuxing@m.scnu.edu.cn, lizheyzy@163.com.

KAT6A amplifications are associated with shorter progression-free survival and overall survival in patients with endometrial serous carcinoma.

Somatic copy number alterations (CNA) are common in endometrial serous carcinoma (ESC). We used the Tumor Cancer Genome Atlas Pan Cancer dataset (TCGA Pan Can) to explore the impact of somatic CNA and gene expression levels (mRNA) of cancer-related genes in ESC. Results were correlated with clinico-pathologic parameters such as age of onset, disease stage, progression-free survival (PFS) and overall survival (OS) (n = 108). 1,449 genes with recurrent somatic CNA were identified, observed in 10% or more tumor samples. Somatic CNA and mRNA expression levels were highly correlated (r> = 0.6) for 383 genes. Among these, 45 genes were classified in the Tier 1 category of Cancer Genome Census-Catalogue of Somatic Mutations in Cancer. Eighteen of 45 Tier 1 genes had highly correlated somatic CNA and mRNA expression levels including ARNT, PIK3CA, TBLXR1, ASXL1, EIF4A2, HOOK3, IKBKB, KAT6A, TCEA1, KAT6B, ERBB2, BRD4, KEAP1, PRKACA, DNM2, SMARCA4, AKT2, SS18L1. Our results are in agreement with previously reported somatic CNA for ERBB2, BRD4 and PIK3C in ESC. In addition, AKT2 (p = 0.002) and KAT6A (p = 0.015) amplifications were more frequent in tumor samples from younger patients (<60), and CEBPA (p = 0.028) and MYC (p = 0.023) amplifications were more common with advanced (stage III and IV) disease stage. Patients with tumors carrying KAT6A and MYC amplifications had shorter PFS and OS. The hazard ratio (HR) of KAT6A was 2.82 [95 CI 1.12–7.07] for PFS and 3.87 [95 CI 1.28–11.68] for OS. The HR of MYC was 2.25 [95 CI 1.05–4.81] and 2.62[95 CI 1.07–6.41] for PFS and OS, respectively.

Abstract LB-315: Oncology research applications on an electrical impedance based, high accuracy sequencing platform

Abstract Next Generation Sequencing (NGS) technologies have revolutionized basic biological and clinical research, especially in oncology. NGS cancer assays are used to determine cancer predisposition, identify tumor mutations, monitor treatment response and develop personalized therapies. Here, GenapSys presents a scalable, low cost, and high accuracy sequencing platform based on electrical impedance detection. We demonstrate that a single run with a 16M sensor chip generates up to 2 Gb of data, with greater than 99% raw accuracy and an average read length of about 150 bp. We highlight its applications for oncology research, using diverse cancer panels on reference and clinical samples. We tested hybrid-capture and multiplex PCR-based cancer panels on a range of DNA sources, including oncology reference standards derived from cell line DNA, cfDNA standards, as well as clinical samples: FFPE, fresh frozen tumor tissue, and blood. For hybrid-capture libraries, we used the IDT xGen Pan Cancer 1.5 and Exome Research panels. We detected low frequency mutations in the range of 1%-24.5% across multiple reference standards with the cancer panel, and observed high correlation in allele frequency with expected values (R2 &amp;gt; 0.99). Similar results were obtained with an amplicon panel, the Ion AmpliSeq Cancer Hotspot Panel v2. Whole exome sequencing and pan cancer sequencing of clinical FFPE, fresh frozen and blood samples showed high concordance (F1-score &amp;gt; 95%) of SNV mutation calling with commonly used NGS technology. Thus, we demonstrate that the GenapSys Sequencing Platform is an accurate, scalable, and low cost solution for oncology research on a wide range of sample types and NGS assays. Citation Format: Saurabh Paliwal, Mohammad Fallahi, Ali Nabi, Tyson A. Clark, Bin Dong, Srijeeta Bagchi, Maryam Jouzi, Hannah Ritchie, Lydia Bonar, Anthony Thomas, Narin Tangprasertchai, Meysam R. Barmi, Xavier Gomes, Subra Sankar, Hesaam Esfandyarpour. Oncology research applications on an electrical impedance based, high accuracy sequencing platform [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 LB-315.