Davila, Jaime

Abstract Introduction/Objective Mutations in KIT and PDGFRA drive the majority of gastrointestinal stromal tumors (GIST) and inform targeted therapy selection. While single-driver mutations are typical, a subset of cases harbors multiple KIT mutations, complicating clinical interpretation. This study investigated the frequency, distribution, and inferred hierarchy of primary and secondary KIT mutations using DNA-based sequencing in a large GIST cohort. Methods/Case Report We retrospectively reviewed 579 GIST cases that underwent DNA-based next-generation sequencing using a custom panel targeting all coding exons of KIT and PDGFRA. Tumor-rich formalin-fixed paraffin-embedded (FFPE) tissue was required. In double-mutant cases, the mutation with higher variant allele frequency (VAF) was presumed to be primary. Results Mutations in KIT or PDGFRA were detected in 482/579 cases (83.2%). Among KIT-mutant cases, 28 had two mutations and one had three. Secondary mutations frequently occurred in exons 13, 14, and 17 and were significantly more common in non-gastric tumors (p < 0.0001). Primary mutations most often involved exon 11. Conclusion VAF analysis enabled classification of mutation hierarchy in cases with multiple KIT mutations. The distinct anatomical and exon-specific distribution of primary vs. secondary mutations highlights their potential therapeutic implications and warrants further study.

IntroductionAdamantinoma‐like Ewing sarcoma (ALES) is a rare aggressive malignancy occasionally diagnosed in the thyroid gland. ALES shows basaloid cytomorphology, expresses keratins, p63, p40, frequently CD99, and harbours the t(11;22) EWSR1::FLI1 translocation. There is debate on whether ALES resembles more sarcoma or carcinoma.MethodsWe performed RNA sequencing from two ALES cases and compared findings with skeletal Ewing's sarcomas and nonneoplastic thyroid tissue. ALES was investigated by in situ hybridization (ISH) for high‐risk human papillomavirus (HPV) DNA and immunohistochemistry for the following antigens: keratin 7, keratin 20, keratin 5, keratins (AE1/AE3 and CAM5.2), CD45, CD20, CD5, CD99, chromogranin, synaptophysin, calcitonin, thyroglobulin, PAX8, TTF1, S100, p40, p63, p16, NUT, desmin, ER, FLI1, INI1, and myogenin.ResultsAn uncommon EWSR1::FLI transcript with retained EWSR1 exon 8 was detected in both ALES cases. Regulators of EWSR1::FLI1 splicing (HNRNPH1, SUPT6H, SF3B1) necessary for production of a functional fusion oncoprotein, as well as 53 genes (including TNNT1, NKX2.2) activated downstream to the EWSR1::FLI1 cascade, were overexpressed. Eighty‐six genes were uniquely overexpressed in ALES, most of which were related to squamous differentiation. Immunohistochemically, ALES strongly expressed keratins 5, AE1/AE3 and CAM5.2, p63, p40, p16, and focally CD99. INI1 was retained. The remaining immunostains and HPV DNA ISH were negative.ConclusionComparative transcriptomic profiling reveals overlapping features of ALES with skeletal Ewing's sarcoma and an epithelial carcinoma, as evidenced by immunohistochemical expression of keratin 5, p63, p40, CD99, the transcriptome profile, and detection of EWSR1::FLI1 fusion transcript by RNA sequencing.

The accurate detection of point mutations from pathology slides using sequencing data is of great importance in cancer genomics and precision oncology. Formalin-fixation paraffin-embedding (FFPE) is a widely used technique to preserve pathology tissues. The FFPE process introduces artificial C > T mutations in next-generation sequencing, so we set out to develop excerno , a method to score and filter such spurious variants. FFPE mutational artifacts follow a mutational signature. By using the FFPE signature and Bayes' formula, we can calculate the probability of a mutation resulting from the FFPE process and use this probability to filter FFPE variants. We implement this method as the excerno R package. We tested excerno by simulating mutations across all 60-baseline mutational signatures from the Catalog of Somatic Mutations in Cancer (COSMIC) and combining them with mutations following the FFPE mutational signature. The sensitivity and specificity of excerno are adversely affected by the cosine similarity between the baseline and FFPE signatures ( c o s F F P E ). Higher percentages of FFPE mutations ( p c t F F P E ) result in increased sensitivity and reduced specificity. The specificity and sensitivity of excerno can be predicted as linear model with an interaction term using c o s F F P E and p c t F F P E , with an R 2 o f 0 . 8 4 and 0.79, respectively. Finally, we tested excerno using six RNA sequencing cancer samples and observed concordant trends of specificity and sensitivity with respect to our simulated data. The excerno R package can be used to annotate and filter FFPE-induced mutations in cancer genomics. Our method is adversely affected by c o s F F P E and p c t F F P E .

Abstract Objectives Cirrhosis-like hepatocellular carcinoma (CL-HCC) is a rare hepatocellular malignancy characterized by multiple tumor nodules that clinically, radiologically, macroscopically, and microscopically mimic cirrhosis. We aimed to elucidate the molecular biology of CL-HCC and determine tumor nodule clonality. Methods We performed RNA sequencing on formalin-fixed, paraffin-embedded tissue from confirmed CL-HCC cases (n = 6), along with corresponding nonneoplastic hepatic tissue (n = 4) when available. Transcriptomes from our previous work on steatohepatitic hepatocellular carcinoma and The Cancer Genome Atlas (TCGA) were used for comparison purposes. Results Histologically, CL-HCC displayed innumerable nodules and extensive vascular invasion. Intratumoral nodule comparison indicated that the multiple nodules were all clonally related, not independent primaries. The unique histomorphologic appearance corresponded with a distinct transcriptome compared with other HCCs, including fibrolamellar HCC (n = 6), steatohepatitic HCC (n = 8), and conventional HCC in TCGA (n = 424). Tumor-normal gene expression analysis revealed consistent overexpression of several genes involved in degradation of tissue matrix. No recurrent translocations or point mutations were identified. CL-HCC showed a gene expression profile indicative of zone 2 hepatocytes. Conclusions CL-HCC’s distinctive clinicopathologic features correspond to a unique gene expression profile, increased expression of invasive markers, features of zone 2 hepatocytes, and features suggestive of intratumoral nodule monoclonality.

The differentiation of B cells into antibody secreting plasma cells (PCs) is governed by a strict regulatory network that results in expression of specific transcriptomes along the activation continuum. In vitro models yielding significant numbers of PCs phenotypically identical to the in vivo state enable investigation of pathways, metabolomes, and non-coding (ncRNAs) not previously identified. The objective of our study was to characterize ncRNA expression during human B cell activation and differentiation. To achieve this, we used an in vitro system and performed RNA-seq on resting and activated B cells and PCs. Characterization of coding gene transcripts, including immunoglobulin (Ig), validated our system and also demonstrated that memory B cells preferentially differentiated into PCs. Importantly, we identified more than 980 ncRNA transcripts that are differentially expressed across the stages of activation and differentiation, some of which are known to target transcription, proliferation, cytoskeletal, autophagy and proteasome pathways. Interestingly, ncRNAs located within Ig loci may be targeting both Ig and non-Ig-related transcripts. ncRNAs associated with B cell malignancies were also identified. Taken together, this system provides a platform to study the role of specific ncRNAs in B cell differentiation and altered expression of those ncRNAs involved in B cell malignancies.

Abstract Polymorphous low-grade neuroepithelial tumor of the young (PLNTY) is a recently described epileptogenic tumor characterized by oligodendroglioma-like components, aberrant CD34 expression, and frequent mitogen-activated protein kinase (MAPK) pathway activation. We molecularly profiled 13 cases with diagnostic histopathological features of PLNTY (10 female; median age, 16 years; range, 5–52). Patients frequently presented with seizures (9 of 12 with available history) and temporal lobe tumors (9 of 13). MAPK pathway activating alterations were identified in all 13 cases. Fusions were present in the 7 youngest patients: FGFR2-CTNNA3 (n = 2), FGFR2-KIAA1598 (FGFR2-SHTN1) (n = 1), FGFR2-INA (n = 1), FGFR2-MPRIP (n = 1), QKI-NTRK2 (n = 1), and KIAA1549-BRAF (n = 1). BRAF V600E mutation was present in 6 patients (17 years or older). Two fusion-positive cases additionally harbored TP53/RB1 abnormalities suggesting biallelic inactivation. Copy number changes predominantly involving whole chromosomes were observed in all 10 evaluated cases, with losses of chromosome 10q occurring with FGFR2-KIAA1598 (SHTN1)/CTNNA3 fusions. The KIAA1549-BRAF and QKI-NTRK2 fusions were associated respectively with a 7q34 deletion and 9q21 duplication. This study shows that despite its name, PLNTY also occurs in older adults, who frequently show BRAF V600E mutation. It also expands the spectrum of the MAPK pathway activating alterations associated with PLNTY and demonstrates recurrent chromosomal copy number changes consistent with chromosomal instability.

Abstract Background: Next-generation sequencing provides comprehensive information about individuals’ genetic makeup and is commonplace in precision oncology practice. Due to the heterogeneity of individual patient’s disease conditions and treatment journeys, not all targeted therapies were initiated despite actionable mutations. To better understand and support the clinical decision-making process in precision oncology, there is a need to examine real-world associations of patients’ genetic information and treatment choice.Methods: To fill the gap of insufficient use of real-world data (RWD) in electronic health records (EHRs), we generated a single Resource Description Framework (RDF) resource, called PO2RDF (precision oncology to RDF) by integrating information regarding gene, variant, disease, and drug from genetic reports and EHRs. Results: There are total 2,309,014 triples contained in the PO2RDF. Among them 32,815 triples are related to Gene, 34,695 triples are related to Variant, 8,787 triples are related to Disease, 26,154 triples are related to Drug. We performed one use case analysis to demonstrate the usability of the PO2RDF: we examined real-world associations between EGFR mutations and targeted therapies to confirm existing knowledge and detect off-label use. Conclusions: In conclusion, our work proposed to use RDF to organize and distribute clinical RWD that is otherwise inaccessible externally. Our work serves as a pilot study that will lead to new clinical applications and could ultimately stimulate progress in the field of precision oncology.

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: DNA polymerase epsilon (POLE) is encoded by the POLE gene, and POLE-driven tumors are characterized by high mutational rates. POLE-driven tumors are relatively common in endometrial and colorectal cancer, and their presence is increasingly recognized in ovarian cancer (OC) of endometrioid type. POLE-driven cases possess an abundance of TCT>TAT and TCG>TTG somatic mutations characterized by mutational signature 10 from the Catalog of Somatic Mutations in Cancer (COSMIC). By quantifying the contribution of COSMIC mutational signature 10 in RNA sequencing (RNA-seq) we set out to identify POLE-driven tumors in a set of unselected Mayo Clinic OC. Methods: Mutational profiles were calculated using expressed single-nucleotide variants (eSNV) in the Mayo Clinic OC tumors (n=195), The Cancer Genome Atlas (TCGA) OC tumors (n=419), and the Genotype-Tissue Expression (GTEx) normal ovarian tissues (n=84). Non-negative Matrix Factorization (NMF) of the mutational profiles inferred the contribution per sample of four distinct mutational signatures, one of which corresponds to COSMIC mutational signature 10. Results: In the Mayo Clinic OC cohort we identified six tumors with a predicted contribution from COSMIC mutational signature 10 of over five mutations per megabase. These six cases harbored known POLE hotspot mutations (P286R, S297F, V411L, and A456P) and were of endometrioid histotype (P=5e-04). These six tumors were hypermutated with a higher tumor mutation load (mean, 54.02 mutations per megabase) compared to non-POLE endometrioid OC cases (mean, 7.69 mutations per megabase; P=5e-04), and had an early onset (average age of patients at onset, 48.33 years) when compared to non-POLE endometrioid OC cohort (average age at onset, 60.13 years; P=.008). Samples from TCGA and GTEx had a low COSMIC signature 10 contribution (median 0.16 mutations per megabase; maximum 1.78 mutations per megabase) and carried no POLE hotspot mutations.Conclusions: From the largest cohort of RNA-seq from endometrioid OC to date (n=53), we identified six hypermutated samples likely driven by POLE (frequency, 11%). Our result suggests the clinical need to screen for POLE driver mutations in endometrioid OC, which can guide enrollment in immunotherapy clinical trials.

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.