Development and validation of the JAX Cancer Treatment Profile™ for detection of clinically actionable mutations in solid tumors

The Cholangiocarcinoma in the Young (CITY) Study: Tumor Biology, Treatment Patterns, and Survival Outcomes in Adolescent Young Adults With Cholangiocarcinoma

PURPOSE

Increased awareness of the distinct tumor biology for adolescents and young adults (AYAs) with cancer has led to improvement in outcomes for this population. However, in cholangiocarcinoma (CCA), a paucity of data exist on the AYA population. To our knowledge, we present the largest study to date on AYA disease biology, treatment patterns, and survival outcomes in CCA.

METHODS

A multi-institutional cohort of patients with CCA diagnosed with intrahepatic cholangiocarcinoma (ICC) or extrahepatic cholangiocarcinoma (ECC) was used for analysis. Retrospective chart review was conducted on patients who were 50 years old and younger (young; n = 124) and older than 50 years (older; n = 723).

RESULTS

Among 1,039 patients screened, 847 patients met eligibility (72% ICC, 28% ECC). Young patients had a larger median tumor size at resection compared with older patients (4.2 v 3.6 cm; P = .048), more commonly had N1 disease (65% v 43%; P = .040), and were more likely to receive adjuvant therapy (odds ratio, 4.0; 95% CI, 1.64 to 9.74). Tumors of young patients were more likely to harbor an FGFR2 fusion, BRAF mutation, or ATM mutation (P < .05 for each). Young patients were more likely to receive palliative systemic therapy (96% v 69%; P < .001), targeted therapy (23% v 8%; P < .001), and treatment on a clinical trial (31% v 19%; P = .004). Among patients who presented with advanced disease, young patients had a higher median overall survival compared with their older counterparts (17.7 v 13.5 months; 95% CI, 12.6 to 22.6 v 11.4 to 14.8; P = .049).

CONCLUSION

Young patients with CCA had more advanced disease at resection, more commonly received both adjuvant and palliative therapies, and demonstrated improved survival compared with older patients. Given the low clinical trial enrollment and poor outcomes among some AYA cancer populations, data to the contrary in CCA are highly encouraging.

A Genomically and Clinically Annotated Patient-Derived Xenograft Resource for Preclinical Research in Non-Small Cell Lung Cancer

Patient-derived xenograft (PDX) models are an effective preclinical in vivo platform for testing the efficacy of novel drugs and drug combinations for cancer therapeutics. Here we describe a repository of 79 genomically and clinically annotated lung cancer PDXs available from The Jackson Laboratory that have been extensively characterized for histopathologic features, mutational profiles, gene expression, and copy-number aberrations. Most of the PDXs are models of non-small cell lung cancer (NSCLC), including 37 lung adenocarcinoma (LUAD) and 33 lung squamous cell carcinoma (LUSC) models. Other lung cancer models in the repository include four small cell carcinomas, two large cell neuroendocrine carcinomas, two adenosquamous carcinomas, and one pleomorphic carcinoma. Models with both de novo and acquired resistance to targeted therapies with tyrosine kinase inhibitors are available in the collection. The genomic profiles of the LUAD and LUSC PDX models are consistent with those observed in patient tumors from The Cancer Genome Atlas and previously characterized gene expression-based molecular subtypes. Clinically relevant mutations identified in the original patient tumors were confirmed in engrafted PDX tumors. Treatment studies performed in a subset of the models recapitulated the responses expected on the basis of the observed genomic profiles. These models therefore serve as a valuable preclinical platform for translational cancer research.

SIGNIFICANCE

Patient-derived xenografts of lung cancer retain key features observed in the originating patient tumors and show expected responses to treatment with standard-of-care agents, providing experimentally tractable and reproducible models for preclinical investigations.

Landscape of genetic variants in sporadic meningiomas captured with clinical genomics

BACKGROUND

Meningiomas are the most common primary central nervous system tumor. Previous studies have characterized recurrent genetic alterations that can predict patient prognosis and potentially provide new avenues for therapeutic intervention. Continued efforts to characterize the genomic changes in meningioma samples can aid in the discovery of therapeutic targets and appropriate patient stratification.

METHODS

We performed targeted genomic sequencing on 25 primary and 2 recurrent meningiomas using a 500-gene panel, including canonical meningioma drivers. We further detail the genomic profiles and relevant clinical findings in three cases of angiomatous meningiomas and two recurrent atypical meningiomas.

RESULTS

Our approach uncovers a diverse landscape of genomic variants in meningioma samples including mutations in established meningioma-related genes NF2, AKT1, PIK3CA, and TRAF7. In addition to known meningioma drivers, we uncover variants in genes encoding other PI3K subunits, Notch/hedgehog/Wnt signaling pathway components, and chromatin regulators. We additionally identify 22 genes mutated across multiple samples. Three patients included in the study were diagnosed with angiomatous WHO grade I meningiomas, all three of which contained variants in the PI3K-AKT signaling pathway previously described to regulate tumor angiogenesis. Analysis of patient-matched primary and recurrent atypical meningiomas revealed clonal enrichment for mutations in the SWI/SNF complex subunits ARID1A and SMARCA4.

CONCLUSIONS

Targeted genomics implemented in neuro-oncology care can enhance our understanding of the genetic underpinnings of central nervous system tumors, including meningiomas. These molecular signatures may be clinically useful in dictating treatment strategies and patient follow-up.

Genomic sequencing of a pregnancy associated symptomatic meningioma of the diaphragma sellae: a case report

Pregnancy-associated meningiomas have unique considerations and features regarding their pathophysiology, location, genetic profile, and neurosurgical management. These tumours have been reported to undergo rapid growth during gestation and regression post-partum, implicating a role for female sex hormones in tumour physiology. In addition, these tumours occur at a higher incidence in the skull base compared to sporadic meningiomas in the general population, often impinging neurovascular structures and requiring emergent resection. While the genomics of sporadic meningiomas have been described, there are no reports characterizing the genetic features of those associated with pregnancy. Here we describe a patient diagnosed with a diphragma sellae meningioma early in the third trimester after presenting with rapidly deteriorating vision. At 32 weeks gestation the baby was delivered by caesarean section and the tumour subsequently removed. Genomic profiling of the tumour sample revealed variants of unknown significant (VUS) in six genes, none of which were in canonical meningioma drivers. We describe our surgical approach and discuss the relevant pathology and genomics, as well as medical and surgical management considerations of meningiomas in pregnancy.

Application of targeted genome sequencing to brain metastasis from non-small cell lung carcinoma: Case report

Non-small cell lung cancer (NSCLC) is frequently associated with central nervous system metastases resulting in poor outcomes. As newer targeted therapies become available determining which patients can benefit from these therapies has remained challenging, and current molecular testing options rely on a panel of only a handful of known oncogenic drivers. Here, we demonstrate a targeted approach at uncovering clinically relevant variants in cancer-associated genes using genomic sequencing. Our patient underwent targeted sequencing of 212 cancer-associated genes, revealing mutations in six; two of which were in EGFR, an important target for therapy in NSCLC. A multidisciplinary approach involving surgical resection, radiation, and targeted therapy based on the genomic profile and tumor pathology ultimately lead to positive therapeutic response and stable disease. Our report provides a proof of principle for incorporating higher throughput genomic sequencing techniques directly into patient care. We also report an atypical response of an EGFR mutation positive metastatic tumor to immune checkpoint therapy, despite recent reports suggesting that these patients do not benefit from immune checkpoint inhibitors. A brief review of current literature is discussed here to explore links between EGFR mutations and PD-L1 expression, as well as response to targeted therapies.

Validity of patient-derived xenograft mouse models for lung cancer based on exome sequencing data

Patient-derived xenograft (PDX) mouse models are frequently used to test the drug efficacy in diverse types of cancer. They are known to recapitulate the patient characteristics faithfully, but a systematic survey with a large number of cases is yet missing in lung cancer. Here we report the comparison of genomic characters between mouse and patient tumor tissues in lung cancer based on exome sequencing data. We established PDX mouse models for 132 lung cancer patients and performed whole exome sequencing for trio samples of tumor-normal-xenograft tissues. Then we computed the somatic mutations and copy number variations, which were used to compare the PDX and patient tumor tissues. Genomic and histological conclusions for validity of PDX models agreed in most cases, but we observed eight (~7%) discordant cases. We further examined the changes in mutations and copy number alterations in PDX model production and passage processes, which highlighted the clonal evolution in PDX mouse models. Our study shows that the genomic characterization plays complementary roles to the histological examination in cancer studies utilizing PDX mouse models.

An Accurate and Comprehensive Clinical Sequencing Assay for Cancer Targeted and Immunotherapies

BACKGROUND

Incorporation of next-generation sequencing (NGS) technology into clinical utility in targeted and immunotherapies requires stringent validation, including the assessment of tumor mutational burden (TMB) and microsatellite instability (MSI) status by NGS as important biomarkers for response to immune checkpoint inhibitors.

MATERIALS AND METHODS

We designed an NGS assay, Cancer Sequencing YS panel (CSYS), and applied algorithms to detect five classes of genomic alterations and two genomic features of TMB and MSI.

RESULTS

By stringent validation, CSYS exhibited high sensitivity and predictive positive value of 99.7% and 99.9%, respectively, for single nucleotide variation; 100% and 99.9%, respectively, for short insertion and deletion (indel); and 95.5% and 100%, respectively, for copy number alteration (CNA). Moreover, CSYS achieved 100% specificity for both long indel (50-3,000 bp insertion and deletion) and gene rearrangement. Overall, we used 33 cell lines and 208 clinical samples to validate CSYS's NGS performance, and genomic alterations in clinical samples were also confirmed by fluorescence in situ hybridization, immunohistochemistry, and polymerase chain reaction (PCR). Importantly, the landscape of TMB across different cancers of Chinese patients (n = 3,309) was studied. TMB by CSYS exhibited a high correlation (Pearson correlation coefficient r = 0.98) with TMB by whole exome sequencing (WES). MSI measurement showed 98% accuracy and was confirmed by PCR. Application of CSYS in a clinical setting showed an unexpectedly high occurrence of long indel (6.3%) in a cohort of tumors from Chinese patients with cancer (n = 3,309), including TP53, RB1, FLT3, BRCA2, and other cancer driver genes with clinical impact.

CONCLUSION

CSYS proves to be clinically applicable and useful in disclosing genomic alterations relevant to cancer target therapies and revealing biomarkers for immune checkpoint inhibitors.

IMPLICATIONS FOR PRACTICE

The study describes a specially designed sequencing panel assay to detect genomic alterations and features of 450 cancer genes, including its overall workflow and rigorous clinical and analytical validations. The distribution of pan-cancer tumor mutational burden, microsatellite instability, gene rearrangement, and long insertion and deletion mutations was assessed for the first time by this assay in a broad array of Chinese patients with cancer. The Cancer Sequencing YS panel and its validation study could serve as a blueprint for developing next-generation sequencing-based assays, particularly for the purpose of clinical application.

Genomic data analysis workflows for tumors from patient-derived xenografts (PDXs): challenges and guidelines

BACKGROUND

Patient-derived xenograft (PDX) models are in vivo models of human cancer that have been used for translational cancer research and therapy selection for individual patients. The Jackson Laboratory (JAX) PDX resource comprises 455 models originating from 34 different primary sites (as of 05/08/2019). The models undergo rigorous quality control and are genomically characterized to identify somatic mutations, copy number alterations, and transcriptional profiles. Bioinformatics workflows for analyzing genomic data obtained from human tumors engrafted in a mouse host (i.e., Patient-Derived Xenografts; PDXs) must address challenges such as discriminating between mouse and human sequence reads and accurately identifying somatic mutations and copy number alterations when paired non-tumor DNA from the patient is not available for comparison.

RESULTS

We report here data analysis workflows and guidelines that address these challenges and achieve reliable identification of somatic mutations, copy number alterations, and transcriptomic profiles of tumors from PDX models that lack genomic data from paired non-tumor tissue for comparison. Our workflows incorporate commonly used software and public databases but are tailored to address the specific challenges of PDX genomics data analysis through parameter tuning and customized data filters and result in improved accuracy for the detection of somatic alterations in PDX models. We also report a gene expression-based classifier that can identify EBV-transformed tumors. We validated our analytical approaches using data simulations and demonstrated the overall concordance of the genomic properties of xenograft tumors with data from primary human tumors in The Cancer Genome Atlas (TCGA).

CONCLUSIONS

The analysis workflows that we have developed to accurately predict somatic profiles of tumors from PDX models that lack normal tissue for comparison enable the identification of the key oncogenic genomic and expression signatures to support model selection and/or biomarker development in therapeutic studies. A reference implementation of our analysis recommendations is available at https://github.com/TheJacksonLaboratory/PDX-Analysis-Workflows .

Interpretations of the Term "Actionable" when Discussing Genetic Test Results: What you Mean Is Not What I Heard

In genomic medicine, the familiarity and inexactness of the term "actionable" can lead to multiple interpretations and mistaken beliefs about realistic treatment options. As part of a larger study focusing on public attitudes toward policies for the return of secondary genomic results, we looked at how members of the lay public interpret the term "medically actionable" in the context of genetic testing. We also surveyed a convenience sample of oncologists as part of a separate study and asked them to define the term "medically actionable." After being provided with a definition of the term, 21 out of 60 (35%) layperson respondents wrote an additional action not specified in the provided definition (12 mentioned "cure" and 9 mentioned environment or behavioral change) and 17 (28%) indicated "something can be done" with no action specified. In contrast, 52 surveyed oncologists did not mention environment, behavioral change, or cure. Based on our findings, we propose that rather than using the term "actionable" alone, providers should also say "what they mean" to reduce miscommunication and confusion that could negatively impact medical decision-making. Lastly, to guide clinicians during patient- provider discussion about genetic test results, we provide examples of phrasing to facilitate clearer communication and understanding of the term "actionable."

Cancer diagnostics: The journey from histomorphology to molecular profiling

Although histomorphology has made significant advances into the understanding of cancer etiology, classification and pathogenesis, it is sometimes complicated by morphologic ambiguities, and other shortcomings that necessitate the development of ancillary tests to complement its diagnostic value. A new approach to cancer patient management consists of targeting specific molecules or gene mutations in the cancer genome by inhibitory therapy. Molecular diagnostic tests and genomic profiling methods are increasingly being developed to identify tumor targeted molecular profile that is the basis of targeted therapy. Novel targeted therapy has revolutionized the treatment of gastrointestinal stromal tumor, renal cell carcinoma and other cancers that were previously difficult to treat with standard chemotherapy. In this review, we discuss the role of histomorphology in cancer diagnosis and management and the rising role of molecular profiling in targeted therapy. Molecular profiling in certain diagnostic and therapeutic difficulties may provide a practical and useful complement to histomorphology and opens new avenues for targeted therapy and alternative methods of cancer patient management.

Somatic Mutation Analysis of Human Cancers: Challenges in Clinical Practice

Somatic mutation analysis of human cancers has become the standard of practice. Whether screening for single gene variants or sequencing hundreds of cancer-related genes, this genomic information is the basis for precision medicine initiatives in oncology. Genomic profiling results in information that allows oncologists to make a more educated selection of appropriate therapeutic strategies that more often combine traditional cytotoxic chemotherapy and radiation with novel targeted therapies. Here we discuss the nuances of implementing somatic mutation testing in a clinical setting.

The Case for Laboratory Developed Procedures: Quality and Positive Impact on Patient Care

An explosion of knowledge and technology is revolutionizing medicine and patient care. Novel testing must be brought to the clinic with safety and accuracy, but also in a timely and cost-effective manner, so that patients can benefit and laboratories can offer testing consistent with current guidelines. Under the oversight provided by the Clinical Laboratory Improvement Amendments, laboratories have been able to develop and optimize laboratory procedures for use in-house. Quality improvement programs, interlaboratory comparisons, and the ability of laboratories to adjust assays as needed to improve results, utilize new sample types, or incorporate new mutations, information, or technologies are positive aspects of Clinical Laboratory Improvement Amendments oversight of laboratory-developed procedures. Laboratories have a long history of successful service to patients operating under Clinical Laboratory Improvement Amendments. A series of detailed clinical examples illustrating the quality and positive impact of laboratory-developed procedures on patient care is provided. These examples also demonstrate how Clinical Laboratory Improvement Amendments oversight ensures accurate, reliable, and reproducible testing in clinical laboratories.

High prevalence of TP53 mutations is associated with poor survival and an EMT signature in gliosarcoma patients

Gliosarcoma (GS) is a rare variant (2%) of glioblastoma (GBM) that poses clinical genomic challenges because of its poor prognosis and limited genomic information. To gain a comprehensive view of the genomic alterations in GS and to understand the molecular etiology of GS, we applied whole-exome sequencing analyses for 28 GS cases (6 blood-matched fresh-frozen tissues for the discovery set, 22 formalin-fixed paraffin-embedded tissues for the validation set) and copy-number variation microarrays for 5 blood-matched fresh-frozen tissues. TP53 mutations were more prevalent in the GS cases (20/28, 70%) compared to the GBM cases (29/90, 32%), and the GS patients with TP53 mutations showed a significantly shorter survival (multivariate Cox analysis, hazard ratio=23.9, 95% confidence interval, 2.87-199.63, P=0.003). A pathway analysis showed recurrent alterations in MAPK signaling (EGFR, RASGRF2 and TP53), phosphatidylinositol/calcium signaling (CACNA1s, PLCs and ITPRs) and focal adhesion/tight junction (PTEN and PAK3) pathways. Genomic profiling of the matched recurrent GS cases detected the occurrence of TP53 mutations in two recurrent GS cases, which suggests that TP53 mutations play a role in treatment resistance. Functionally, we found that TP53 mutations are associated with the epithelial-mesenchymal transition (EMT) process of sarcomatous components of GS. We provide the first comprehensive genome-wide genetic alternation profiling of GS, which suggests novel prognostic subgroups in GS patients based on their TP53 mutation status and provides new insight in the pathogenesis and targeted treatment of GS.

Integrated analysis of gene expression and copy number identified potential cancer driver genes with amplification-dependent overexpression in 1,454 solid tumors

Identification of driver genes contributes to the understanding of cancer etiology and is imperative for the development of individualized therapies. Gene amplification is a major event in oncogenesis. Driver genes with tumor-specific amplification-dependent overexpression can be therapeutic targets. In this study, we aimed to identify amplification-dependent driver genes in 1,454 solid tumors, across more than 15 cancer types, by integrative analysis of gene expression and copy number. Amplification-dependent overexpression of 64 known driver oncogenes were found in 587 tumors (40%); genes frequently observed were MYC (25%) and MET (18%) in colorectal cancer; SKP2 (21%) in lung squamous cell carcinoma; HIST1H3B (19%) and MYCN (13%) in liver cancer; KIT (57%) in gastrointestinal stromal tumors; and FOXL2 (12%) in squamous cell carcinoma across tissues. Genomic aberrations in 138 known cancer driver genes and 491 established fusion genes were found in 1,127 tumors (78%). Further analyses of 820 cancer-related genes revealed 16 as potential driver genes, with amplification-dependent overexpression restricted to the remaining 22% of samples (327 tumors) initially undetermined genetic drivers. Among them, AXL, which encodes a receptor tyrosine kinase, was recurrently overexpressed and amplified in sarcomas. Our studies of amplification-dependent overexpression identified potential drug targets in individual tumors.

Molecular Testing in Breast Cancer: A Guide to Current Practices

CONTEXT

-Molecular diagnostics play a role in the management of many cancers, including breast cancer.

OBJECTIVE

-To provide an update on molecular testing in current clinical practice, targeted at practicing pathologists who are not breast cancer specialists.

DATA SOURCES

-This study is a narrative literature review.

CONCLUSIONS

-In addition to routine hormone (estrogen and progesterone) receptor testing, new and recurrent tumors are tested for HER2 amplification by in situ hybridization or overexpression by immunohistochemistry. Intrinsic subtyping of tumors represents a fundamental advance in our understanding of breast cancer biology, but currently it has an indirect role in patient management. Clinical next-generation sequencing (tumor profiling) is increasingly used to identify potentially actionable mutations in tumor tissue. Multianalyte assays with algorithmic analysis, including MammaPrint, Oncotype DX, and Prosigna, play a larger role in breast cancer than in many other malignancies. Given that a proportion of breast cancers are familial, testing of nontumor tissue for cancer predisposition mutations also plays a role in breast cancer care.

Next-Generation Sequencing in Oncology: Genetic Diagnosis, Risk Prediction and Cancer Classification

Next-generation sequencing (NGS) technology has expanded in the last decades with significant improvements in the reliability, sequencing chemistry, pipeline analyses, data interpretation and costs. Such advances make the use of NGS feasible in clinical practice today. This review describes the recent technological developments in NGS applied to the field of oncology. A number of clinical applications are reviewed, i.e., mutation detection in inherited cancer syndromes based on DNA-sequencing, detection of spliceogenic variants based on RNA-sequencing, DNA-sequencing to identify risk modifiers and application for pre-implantation genetic diagnosis, cancer somatic mutation analysis, pharmacogenetics and liquid biopsy. Conclusive remarks, clinical limitations, implications and ethical considerations that relate to the different applications are provided.

Mutations in TP53, PIK3CA, PTEN and other genes in EGFR mutated lung cancers: Correlation with clinical outcomes

INTRODUCTION

The degree and duration of response to epidermal growth factor receptor (EGFR) inhibitors in EGFR mutated lung cancer are heterogeneous. We hypothesized that the concurrent genomic landscape of these tumors, which is currently unknown in view of the prevailing single gene assay diagnostic paradigm in clinical practice, could play a role in clinical outcomes and/or mechanisms of resistance.

METHODS

We retrospectively probed our institutional lung cancer database for tumors with EGFR kinase domain mutations that were also evaluated by more comprehensive molecular profiling, and evaluated tumor response to EGFR tyrosine kinase inhibitors (TKIs).

RESULTS

Out of 171 EGFR mutated tumor-patient cases, 20 were sequenced using at least a limited comprehensive genomic profiling platform. 50% harbored concurrent TP53 mutation, 10% PIK3CA mutation, 5% PTEN mutation, among others. The response rate to EGFR TKIs, the median progression-free survival (PFS) to TKIs, the percentage of EGFR-T790M TKI resistance and survival had higher trends in EGFR mutant/TP53 wild-type cases when compared to EGFR mutant/TP53 mutant tumors (all p >0.05 without statistical significance); with a significantly longer median PFS in EGFR-exon 19 deletion mutant/TP53 wild-type cancers treated with 1st generation EGFR TKIs (p=0.035).

CONCLUSIONS

Concurrent mutations, specifically TP53, are common in EGFR mutated lung cancer and may alter clinical outcomes. Additional cohorts will be needed to determine if comprehensive molecular profiling adds clinically relevant information to single gene assay identification in oncogene-driven lung cancers.

Optimizing an ion semiconductor sequencing data analysis method to identify somatic mutations in the genomes of cancer cells in clinical tissue samples

Identification of causal genomic alterations is an indispensable step in the implementation of personalized cancer medicine. Analytical methods play a central role in identifying such changes because of the vast amount of data produced by next generation sequencer. Most analytical techniques are designed for the Illumina platform and are therefore suboptimal for analyzing datasets generated by whole exome sequencing (WES) using the Ion Proton System. Accurate identification of somatic mutations requires the characterization of platform-dependent error profiles and genomic properties that affect the accuracy of sequence data as well as platform-oriented optimization of the pipeline. Therefore, we used the Ion Proton System to perform WES of DNAs isolated from tumor and matched control tissues of 1,058 patients with cancer who were treated at the Shizuoka Cancer Center Hospital. Among the initially identified candidate somatic single-nucleotide variants (SNVs), 10,279 were validated by manual inspection of the WES data followed by Sanger sequencing. These validated SNVs were used as an objective standard to determine an optimum cutoff value to improve the pipeline. Using this optimized pipeline analysis, 189,381 SNVs were identified in 1,101 samples. The analytical technique presented here is a useful resource for conducting clinical WES, particularly using semiconductor-based sequencing technology.

Somatic gene mutation analysis of triple negative breast cancers

OBJECTIVES

The aims of this study were to analyze triple negative breast cancer (TNBC) using an expanded next generation sequencing (NGS) assay, assess the clinical relevance using a recently described database, and correlate tumor morphology with detected genetic alterations.

METHODS

DNA was isolated from twenty primary TNBCs and genes of interest were enriched and sequenced with hybrid capture, followed by variant detection and functional and clinical annotation. The JAX-CTP™ assay detects actionable variants in the form of single nucleotide variations, small insertions and deletions (≤50 bp), and copy number variants in 358 genes in specimens containing a neoplastic cell content of ≥50%. The JAX-CKB is a comprehensive database that curates tumor phenotype, genetic variant and protein effect, therapeutic relevance, and available treatment options.

RESULTS

18/20 (90%) of TNBCs contained at least one somatic mutation detected by the JAX-CTP™. MYC amplification was the most common alteration, present in 75% of tumors. TP53, AURKA, and KDR mutations were each present in 30% (6/20) of cases. Related recruiting clinical trials, extracted from JAX-CKB, included 166 for breast cancer, of which 17 were specific to only the TNBC subtype. All 17 trials were testing at least one therapy that targets a mutation identified in this sample set. The majority (89%) of tumors with basal-like histologic features had MYC amplification.

CONCLUSIONS

The expanded gene panel identified a variety of clinically actionable gene alterations in TNBCs. The identification of such variants increases the possibility for new therapeutic interventions and clinical trial eligibility for TNBC patients.

Advances in the Molecular Analysis of Soft Tissue Tumors and Clinical Implications

The emergence of high-throughput molecular technologies has accelerated the discovery of novel diagnostic, prognostic and predictive molecular markers. Clinical implementation of these technologies is expected to transform the practice of surgical pathology. In soft tissue tumor pathology, accurate interpretation of comprehensive genomic data provides useful diagnostic and prognostic information, and informs therapeutic decisions. This article reviews recently developed molecular technologies, focusing on their application to the study of soft tissue tumors. Emphasis is made on practical issues relevant to the surgical pathologist. The concept of genomically-informed therapies is presented as an essential motivation to identify targetable molecular alterations in sarcoma.

Validation and Application of a Custom-Designed Targeted Next-Generation Sequencing Panel for the Diagnostic Mutational Profiling of Solid Tumors

The inevitable switch from standard molecular methods to next-generation sequencing for the molecular profiling of tumors is challenging for most diagnostic laboratories. However, fixed validation criteria for diagnostic accreditation are not in place because of the great variability in methods and aims. Here, we describe the validation of a custom panel of hotspots in 24 genes for the detection of somatic mutations in non-small cell lung carcinoma, colorectal carcinoma and malignant melanoma starting from FFPE sections, using 14, 36 and 5 cases, respectively. The targeted hotspots were selected for their present or future clinical relevance in solid tumor types. The target regions were enriched with the TruSeq approach starting from limited amounts of DNA. Cost effective sequencing of 12 pooled libraries was done using a micro flow cell on the MiSeq and subsequent data analysis with MiSeqReporter and VariantStudio. The entire workflow was diagnostically validated showing a robust performance with maximal sensitivity and specificity using as thresholds a variant allele frequency >5% and a minimal amplicon coverage of 300. We implemented this method through the analysis of 150 routine diagnostic samples and identified clinically relevant mutations in 16 genes including KRAS (32%), TP53 (32%), BRAF (12%), APC (11%), EGFR (8%) and NRAS (5%). Importantly, the highest success rate was obtained when using also the low quality DNA samples. In conclusion, we provide a workflow for the validation of targeted NGS by a custom-designed pan-solid tumor panel in a molecular diagnostic lab and demonstrate its robustness in a clinical setting.

Molecular Genetic Analysis of Ovarian Brenner Tumors and Associated Mucinous Epithelial Neoplasms: High Variant Concordance and Identification of Mutually Exclusive RAS Driver Mutations and MYC Amplification

Benign ovarian Brenner tumors often are associated with mucinous cystic neoplasms, which are hypothesized to share a histogenic origin and progression, however, supporting molecular characterization is limited. Our goal was to identify molecular mechanisms linking these tumors. DNA from six Brenner tumors with paired mucinous tumors, two Brenner tumors not associated with a mucinous neoplasm, and two atypical proliferative (borderline) Brenner tumors was extracted from formalin-fixed, paraffin-embedded tumor samples and sequenced using a 358-gene next-generation sequencing assay. Variant calls were compared within tumor groups to assess somatic mutation profiles. There was high concordance of the variants between paired samples (40% to 75%; P < 0.0001). Four of the six tumor pairs showed KRAS hotspot driver mutations specifically in the mucinous tumor. In the two paired samples that lacked KRAS mutations, MYC amplification was detected in both of the mucinous and the Brenner components; MYC amplification also was detected in a third Brenner tumor. Five of the Brenner tumors had no reportable potential driver alterations. The two atypical proliferative (borderline) Brenner tumors both had RAS mutations. The high degree of coordinate variants between paired Brenner and mucinous tumors supports a shared origin or progression. Differences observed in affected genes and pathways, particularly involving RAS and MYC, may point to molecular drivers of a divergent phenotype and progression of these tumors.

The clinical trial landscape in oncology and connectivity of somatic mutational profiles to targeted therapies

Background

Precision medicine in oncology relies on rapid associations between patient-specific variations and targeted therapeutic efficacy. Due to the advancement of genomic analysis, a vast literature characterizing cancer-associated molecular aberrations and relative therapeutic relevance has been published. However, data are not uniformly reported or readily available, and accessing relevant information in a clinically acceptable time-frame is a daunting proposition, hampering connections between patients and appropriate therapeutic options. One important therapeutic avenue for oncology patients is through clinical trials. Accordingly, a global view into the availability of targeted clinical trials would provide insight into strengths and weaknesses and potentially enable research focus. However, data regarding the landscape of clinical trials in oncology is not readily available, and as a result, a comprehensive understanding of clinical trial availability is difficult.

Results

To support clinical decision-making, we have developed a data loader and mapper that connects sequence information from oncology patients to data stored in an in-house database, the JAX Clinical Knowledgebase (JAX-CKB), which can be queried readily to access comprehensive data for clinical reporting via customized reporting queries. JAX-CKB functions as a repository to house expertly curated clinically relevant data surrounding our 358-gene panel, the JAX Cancer Treatment Profile (JAX CTP), and supports annotation of functional significance of molecular variants. Through queries of data housed in JAX-CKB, we have analyzed the landscape of clinical trials relevant to our 358-gene targeted sequencing panel to evaluate strengths and weaknesses in current molecular targeting in oncology. Through this analysis, we have identified patient indications, molecular aberrations, and targeted therapy classes that have strong or weak representation in clinical trials.

Conclusions

Here, we describe the development and disseminate system methods for associating patient genomic sequence data with clinically relevant information, facilitating interpretation and providing a mechanism for informing therapeutic decision-making. Additionally, through customized queries, we have the capability to rapidly analyze the landscape of targeted therapies in clinical trials, enabling a unique view into current therapeutic availability in oncology.

Genomic alterations in BCL2L1 and DLC1 contribute to drug sensitivity in gastric cancer

Gastric cancer (GC) is the third leading cause of cancer-related deaths worldwide. Recent high-throughput analyses of genomic alterations revealed several driver genes and altered pathways in GC. However, therapeutic applications from genomic data are limited, largely as a result of the lack of druggable molecular targets and preclinical models for drug selection. To identify new therapeutic targets for GC, we performed array comparative genomic hybridization (aCGH) of DNA from 103 patients with GC for copy number alteration (CNA) analysis, and whole-exome sequencing from 55 GCs from the same patients for mutation profiling. Pathway analysis showed recurrent alterations in the Wnt signaling [APC, CTNNB1, and DLC1 (deleted in liver cancer 1)], ErbB signaling (ERBB2, PIK3CA, and KRAS), and p53 signaling/apoptosis [TP53 and BCL2L1 (BCL2-like 1)] pathways. In 18.4% of GC cases (19/103), amplification of the antiapoptotic gene BCL2L1 was observed, and subsequently a BCL2L1 inhibitor was shown to markedly decrease cell viability in BCL2L1-amplified cell lines and in similarly altered patient-derived GC xenografts, especially when combined with other chemotherapeutic agents. In 10.9% of cases (6/55), mutations in DLC1 were found and were also shown to confer a growth advantage for these cells via activation of Rho-ROCK signaling, rendering these cells more susceptible to a ROCK inhibitor. Taken together, our study implicates BCL2L1 and DLC1 as potential druggable targets for specific subsets of GC cases.

The Disease Ontology: fostering interoperability between biological and clinical human disease-related data

The Disease Ontology (DO) enables cross-domain data integration through a common standard of human disease terms and their etiological descriptions. Standardized disease descriptors that are integrated across mammalian genomic resources provide a human-readable, machine-interpretable, community-driven disease corpus that unifies the representation of human common and rare diseases. The DO is populated by consensus-driven disease data descriptors that incorporate disease terms utilized by genomic and genetic projects and resources engaged in studies to understand the genetics of human disease through the study of model organisms. The DO project serves multiple roles for the model organism community by providing: (1) a structured "backbone" of disease concepts represented among the model organism databases; (2) authoritative disease curation services to researchers and resource providers; and (3) development of subsets of the DO representative of human diseases annotated to animal models curated within the model organism databases.