Citations

Abstract Background: Traditionally, mutational burden and mutational signatures have been assessed by tumor-normal pair DNA sequencing. The requirement of having both normal and tumor samples is not always feasible from a clinical perspective, and led us to investigate the efficacy of using RNA sequencing of only the tumor sample to determine the mutational burden and signatures, and subsequently molecular cause of the cancer. The potential advantages include reducing the cost of testing, and simultaneously providing information on the gene expression profile and gene fusions present in the tumor. Results: In this study, we devised supervised and unsupervised learning methods to determine mutational signatures from tumor RNA-seq data. As applications, we applied the methods to a training set of 587 TCGA uterine cancer RNA-seq samples, and examined in an independent testing set of 521 TCGA colorectal cancer RNA-seq samples. Both diseases are known associated with microsatellite instable high (MSI-H) and driver defects in DNA polymerase ɛ (POLɛ). From RNA-seq called variants, we found majority (>95%) are likely germline variants, leading to C>T enriched germline variants (dbSNP) widely applicable in tumor and normal RNA-seq samples. We found significant associations between RNA-derived mutational burdens and MSI/POLɛ status, and insignificant relationship between RNA-seq total coverage and derived mutational burdens. Additionally we found that over 80% of variants could be explained by using the COSMIC mutational signature-5, -6 and -10, which are implicated in natural aging, MSI-H, and POLɛ, respectively. For classifying tumor type, within UCEC we achieved a recall of 0.56 and 0.78, and specificity of 0.66 and 0.99 for MSI and POLɛ respectively. By applying learnt RNA signatures from UCEC to COAD, we were able to improve our classification of both MSI and POLɛ. Conclusions: Taken together, our work provides a novel method to detect RNA-seq derived mutational signatures with effective procedures to remove likely germline variants. It can leads to accurate classification of underlying driving mechanisms of DNA damage deficiency.

Abstract Background: Traditionally, mutational burden and mutational signatures have been assessed by tumor-normal pair DNA sequencing. The requirement of having both normal and tumor samples is not always feasible from a clinical perspective, and led us to investigate the efficacy of using RNA sequencing of only the tumor sample to determine the mutational burden and signatures, and subsequently molecular cause of the cancer. The potential advantages include reducing the cost of testing, and simultaneously providing information on the gene expression profile and gene fusions present in the tumor. Results: In this study, we devised supervised and unsupervised learning methods to determine mutational signatures from tumor RNA-seq data. As applications, we applied the methods to a training set of 587 TCGA uterine cancer RNA-seq samples, and examined in an independent testing set of 521 TCGA colorectal cancer RNA-seq samples. Both diseases are known associated with microsatellite instable high (MSI-H) and driver defects in DNA polymerase ɛ (POLɛ).From RNA-seq called variants, we found majority (>95%) are likely germline variants, leading to C>T enriched germline variants (dbSNP) widely applicable in tumor and normal RNA-seq samples. We found significant associations between RNA-derived mutational burdens and MSI/POLɛ status, and insignificant relationship between RNA-seq total coverage and derived mutational burdens. Additionally we found that over 80% of variants could be explained by using the COSMIC mutational signature-5, -6 and -10, which are implicated in natural aging, MSI-H, and POLɛ, respectively. For classifying tumor type, within UCEC we achieved a recall of 0.56 and 0.78, and specificity of 0.66 and 0.99 for MSI and POLɛ respectively. By applying learnt RNA signatures from UCEC to COAD, we were able to improve our classification of both MSI and POLɛ. Conclusions: Taken together, our work provides a novel method to detect RNA-seq derived mutational signatures with effective procedures to remove likely germline variants. It can leads to accurate classification of underlying driving mechanisms of DNA damage deficiency.

Abstract Cisplatin chemotherapy, although efficacious in positive resolution of cancer, adversely potentiates off-target cognitive dysfunction and affects approximately 14 million cancer survivors in the United States alone. Despite the high prevalence of chemotherapy induced cognitive impairments (known as chemobrain), there is little information on how memory and learning are impaired and no known cure. To elucidate the mechanisms by which chemobrain impairs cognition, we implement a novel experimental mouse model resembling clinical cisplatin-chemotherapy. Our results reveal that repeated cisplatin administration impairs hippocampal neuronal functional morphology, while inducing significant emotional and memory deficits. Although the molecular targets and pathways vulnerable to cisplatin in the central nervous system (CNS) are currently unknown, RNA-sequencing derived from mice administered cisplatin or vehicle revealed the G-protein coupled adenosine A2A receptor (Adora2a) known to be critical for synaptic plasticity and memory, as a promising therapeutic target for chemobrain. Bioinformatic analysis and qRT-PCR validation revealed significant induction of Adora2a mRNA expression by cisplatin in the adult hippocampus, a brain structure critical for learning and memory. Interestingly, while Adora2a is known to be expressed by neurons, astrocytes and other brain glia, confocal microscopy demonstrates that cisplatin specifically increases Adora2a expression in hippocampal neurons without affecting astrocytes, indicating that Adora2a expressing neurons are particularly vulnerable. To mechanistically determine whether elevated neuronal Adora2a functionality are implicated in cisplatin-induced chemobrain, we assessed the efficacy of Istradefylline (KW-6002), a selective Adora2a inhibitor, in preventing cisplatin-induced chemobrain. Our results indicate that selective pharmacological inhibition of Adora2a prevented cisplatin induced anxiety and cognitive impairments in the elevated plus maze, the Morris water maze and novel object recognition test. In addition, our translational approach employing the non-specific Adora2a antagonist caffeine, protected against cisplatin-induced impairments in body weight, motor learning and motor function. Therefore, our results suggest a critical regulatory role for Adora2a in cisplatin-induced cognitive and motor dysfunction. Given that Adora2a antagonists are proven to be safe and neuroprotective in neurodegeneration as well as in enhancing anti-tumor activity, inhibiting Adora2a may have far-reaching synergistic effects on cancer treatment and chemobrain. This work was supported by Mayo Clinic Breast SPORE (R50CA116201) and Regenerative Medicine Minnesota (RMM 091718 DS 005) to M.H.J. and the Bosarge Family Foundation-Waun Ki Hong Scholar Award to A.O. Citation Format: Alfredo Oliveros, Ki-Hyun Yoo, jun Tang, Ana M. Corujo, Danielle Brogren, Yuanhang Liu, Mi-Hyeon Jang. Adora2a inhibition as a novel therapeutic target for cisplatin chemobrain-induced cognitive dysfunction [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 4141.

Abstract Introduction: Acquired resistance to platinum remains a major clinical problem in ovarian cancer since systemic therapies have limited efficacy in this setting. There is growing evidence that the tumor microenvironment (TME) contributes to such resistance, as well as the pathogenesis of the disease. The study of the TME is limited by technical challenges of separating the epithelial from the stromal component. To overcome this limitation, we performed RNA sequencing (RNA-Seq) for three pairs of sensitive and induced resistant patient-derived xenograft models since the epithelial transcripts originate from human tissue and the stroma component is murine. Methods: To determine which TME genes might be contributing to chemotherapy resistance, three platinum-sensitive ovarian cancer PDX lines were treated repeatedly with carboplatin/paclitaxel until resistance occurred. Primary platinum-sensitive and induced platinum resistant tumors were characterized histologically by H&E and Masson Trichrome staining. The three pairs of sensitive and resistant PDX models were then subjected to RNA-Seq. Raw sequencing data were processed through Xenome to classify the reads into epithelial carcinoma (human) or TME (mouse) through Mayo Clinic’s internal RNA-Seq pipeline for transcriptome quantification. Differential expression analysis between induced resistant and sensitive models was carried out for both carcinoma and TME components using edgeR paired analysis. Gene set enrichment analysis was used to identify overrepresented biologic functions for differentially expressed genes between the pairs. Top significantly varied, differentially expressed genes between the pairs were validated using species-specific qPCR. Results: Histologic analysis of the matched sensitive/resistant pairs revealed a marked increase of the stromal component in the resistant tumors evident by H&E and Masson trichrome staining. A total number of 95 and 312 genes were differentially expressed in the epithelial and TME component, respectively (FDR<0.05; absolute log2 fold-change >1.5). The stemness marker SOX2 was significantly upregulated in the human component of the resistant tumors as confirmed by qPCR. Genes involved in stroma remodeling were upregulated in the “murine” component of the resistant tumors, and upregulation was confirmed by qPCR (normalized to a murine housekeeper gene). Gene set enrichment analysis showed that the upregulated genes in TME of resistant models were enriched for cytoskeleton related functions, while the downregulated genes were enriched for extracellular matrix-related functions. Conclusion: A bioinformatics strategy able to map human and murine reads separately may identify resistance mechanisms attributed to the two tumor subcompartments and could lead to strategies to potentially target each separately or concurrently. Citation Format: Valentina Zanfagnin, Yuanhang Liu, Pritha Chanana, Xiaonan Pritha, Beverly Long, Joe Pathoulas, Brad Evans, Jaime Davila, Chen Wang, Saravut John Weroha. Transcriptional profiling of tumor stroma using ovarian cancer PDX models with induced platinum-resistance [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr B18.

Abstract Objectives Mucinous cystic neoplasm of the liver is characterized by neoplastic mucinous and/or biliary epithelium surrounded by ovarian-type stroma. Immunohistochemical studies have shown that the ovarian-type stroma expresses estrogen receptor, suggesting potential hormonal responsiveness. The molecular biology of mucinous cystic neoplasm of the liver remains poorly studied. Methods Transcriptome sequencing and immunohistochemistry were performed on a series of mucinous cystic neoplasms. Results Mucinous cystic neoplasm of the liver exhibited significantly increased RNA expression of ovarian stromal markers WT1, PR, and ER2 and sex cord stromal markers SF-1, inhibin-α, and calretinin compared with nonneoplastic liver. Immunohistochemistry confirmed the RNA-level data. Evidence for sex hormone biosynthesis was identified by significant overexpression of multiple estrogen biosynthetic enzymes. Expression of 17β-hydroxysteroid dehydrogenase 1 was confirmed immunohistochemically. Pathway analysis also identified significant upregulation of the hedgehog and Wnt pathways and significant downregulation of T-helper 1 and T-helper 2 pathways. Conclusions Mucinous cystic neoplasm of the liver recapitulates ovarian stroma at the morphologic, DNA, RNA, and protein levels. These data support the concept that this tumor likely arises from ectopic primitive gonadal tissue and/or stromal cells with capacity to transdifferentiate to ovarian cortical cells.

Abstract Background: Traditionally, mutational burden and mutational signatures have been assessed by tumor-normal pair DNA sequencing. The requirement of having both normal and tumor samples is not always feasible from a clinical perspective, and led us to investigate the efficacy of using RNA sequencing of only the tumor sample to determine the mutational burden and signatures, and subsequently molecular cause of the cancer. The potential advantages include reducing the cost of testing, and simultaneously providing information on the gene expression profile and gene fusions present in the tumor.Results: In this study, we devised supervised and unsupervised learning methods to determine mutational signatures from tumor RNA-seq data. As applications, we applied the methods to a training set of 587 TCGA uterine cancer RNAseq samples, and examined in an independent testing set of xxx TCGA colorectal cancer RNAseq samples. Both diseases are known associated with microsatellite instable high (MSI-H) and driver defects in DNA polymerase ɛ (POLɛ). From RNAseq called variants, we found majority (>95%) are likely germline variants, leading to C>T enriched germline variants (dbSNP) widely applicable in tumor and normal RNAseq samples. We found significant associations between RNA-derived mutational burdens and MSI/POLɛ status, and insignificant relationship between RNAseq total coverage and derived mutational burdens. Additionally we found that over 80% of variants could be explained by using the COSMIC mutational signature-5, -6 and -10, which are implicated in natural aging, MSI-H, and POLɛ, respectively. For classifying tumor type, within UCEC we achieved a recall of 0.56 and 0.78, and specificity of 0.66 and 0.99 for MSI and POLɛ respectively. By applying learnt RNA signatures from UCEC to COAD, we were able to improve our classification of both MSI and POLɛ. Conclusions: Taken together, our work provides a novel method to detect RNAseq derived mutational signatures with effective procedures to remove likely germline variants. It can leads to accurate classification of underlying driving mechanisms of DNA damage deficiency.

Background: Scattered tubular-like cells (STCs) proliferate and differentiate to support neighboring injured renal tubular cells during recovery from insults. Renal artery stenosis (RAS) induces renal ischemia and hypertension and leads to loss of kidney function, but whether RAS alters renal endogenous repair mechanisms, such as STCs, remains unknown. We hypothesize that RAS in swine modifies the messenger RNA (mRNA) profile of STCs, blunting their in vitro reparative capacity. Methods: CD24+/CD133+ STCs were isolated from pig kidneys after 10-weeks of RAS or sham (n = 3 each) and their gene cargo analyzed using high-throughput mRNAseq. Expression profiles for upregulated and downregulated mRNAs in RAS-STCs were functionally interpreted by gene ontology analysis. STC activation was assessed by counting the total number of STCs in pig kidney sections using flow cytometry, whereas cell proliferation was assessed in vitro. Results: Of all expressed genes, 1430 genes were upregulated and 315 downregulated in RAS- versus Normal-STCs. Expression of selected candidate genes followed the same fold change directions as the mRNAseq findings. Genes upregulated in RAS-STCs were involved in cell adhesion, extracellular matrix remodeling, and kidney development, whereas those downregulated in RAS-STCs are related to cell cycle and cytoskeleton. The percentage of STCs from dissociated kidney cells was higher in RAS versus Normal pigs, but their proliferation rate was blunted. Conclusions: Renal ischemia and hypertension in swine induce changes in the mRNA profile of STCs, associated with increased STC activation and impaired proliferation. These observations suggest that RAS may alter the reparative capacity of STCs.

Abstract Background: Archived formalin fixed paraffin embedded (FFPE) samples are valuable clinical resources to examine clinically relevant morphology features and also to study genetic changes. However, DNA quality and quantity of FFPE samples are sub-optimal, and resulting NGS-based genetics variant detections are prone to false positives. Evaluations of wet-lab and bioinformatics approaches are needed to optimize variant detection from FFPE samples. Results: As a pilot study, we designed within-subject triplicate samples of DNA derived from paired FFPE and fresh frozen breast tissues to highlight FFPE-specific artifacts. For FFPE samples, we tested two FFPE DNA extraction methods to determine impact of wet-lab procedures on variant calling: QIAGEN QIAamp DNA Mini Kit ("QA"), and QIAGEN GeneRead DNA FFPE Kit ("QGR"). We also used negative-control (NA12891) and positive control samples (Horizon Discovery Reference Standard FFPE). All DNA sample libraries were prepared for NGS according to the QIAseq Human Breast Cancer Targeted DNA Panel protocol and sequenced on the HiSeq 4000. Variant calling and filtering were performed using QIAGEN Gene Globe Data Portal. Detailed variant concordance comparisons and mutational signature analysis were performed to investigate effects of FFPE samples compared to paired fresh frozen samples, along with different DNA extraction methods. In this study, we found that five times or more variants were called with FFPE samples, compared to their paired fresh-frozen tissue samples even after applying molecular barcoding error-correction and default bioinformatics filtering recommended by the vendor. We also found that QGR as an optimized FFPE-DNA extraction approach leads to much fewer discordant variants between paired fresh frozen and FFPE samples. Approximately 92 % of the uniquely called FFPE variants were of low allelic frequency range (<5%), and collectively shared a “C>T|G>A” mutational signature known to be representative of FFPE artifacts resulting from cytosine deamination. Based on control samples and FFPE-frozen replicates, we derived an effective filtering strategy with associated empirical false-discovery estimates. Conclusions: Through this study, we demonstrated feasibility of calling and filtering genetic variants from FFPE tissue samples using a combined strategy with molecular barcodes, optimized DNA extraction, and bioinformatics methods incorporating genomics context such as mutational signature and variant allelic frequency.

Abstract Background Archived formalin fixed paraffin embedded (FFPE) samples are valuable clinical resources to examine clinically relevant morphology features and also to study genetic changes. However, DNA quality and quantity of FFPE samples are often sub-optimal, and resulting NGS-based genetics variant detections are prone to false positives. Evaluations of wet-lab and bioinformatics approaches are needed to optimize variant detection from FFPE samples. Results As a pilot study, we designed within-subject triplicate samples of DNA derived from paired FFPE and fresh frozen breast tissues to highlight FFPE-specific artifacts. For FFPE samples, we tested two FFPE DNA extraction methods to determine impact of wet-lab procedures on variant calling: QIAGEN QIAamp DNA Mini Kit ("QA"), and QIAGEN GeneRead DNA FFPE Kit ("QGR"). We also used negative-control (NA12891) and positive control samples (Horizon Discovery Reference Standard FFPE). All DNA sample libraries were prepared for NGS according to the QIAseq Human Breast Cancer Targeted DNA Panel protocol and sequenced on the HiSeq 4000. Variant calling and filtering were performed using QIAGEN Gene Globe Data Portal. Detailed variant concordance comparisons and mutational signature analysis were performed to investigate effects of FFPE samples compared to paired fresh frozen samples, along with different library preparations. In this study, we found that five times or more variants were called with FFPE samples, compared to their paired fresh-frozen tissue samples even after applying molecular barcoding error-correction and default bioinformatics filtering recommended by the vendor. We also found that QGR as an optimized FFPE-DNA extraction approach leads to much fewer discordant variants between paired fresh frozen and FFPE samples. Approximately 92% of the uniquely called FFPE variants were of low allelic frequency range (<5%), and collectively shared a “C>T|G>A” mutational signature known to be representative of FFPE artifacts resulting fromcytosine deamination. Based on control samples and FFPE-frozen replicates, we derived an effective filtering strategy with associated empirical false-discovery estimates. Conclusions Through this study, we demonstrated feasibility of calling and filtering genetic variants from FFPE tissue samples using a combined strategy with molecular barcodes, optimized DNA extraction, and bioinformatics methods incorporating genomics context such as mutational signature and variant allelic frequency.