Hong H-HL, Dunnick J, Herbert R, Devereux TR, Kim Y, Sills RC (2007): Genetic alterations in K-ras andp53 cancer genes in lung neoplasms from Swiss (CD-1) male mice exposed transplacentally to AZT. Environ Mol Mutagen 48:299–306.

e16042 Background: Esophageal cancer is the eighth most common cancer in the world and more than half of global cases occur in China. Studies demonstrated that esophageal squamous cell carcinomas (ESCC) and esophageal adenocarcinomas (EAC) are two distinct disease entities. Due to the lack of effective therapies, the five-year survival rates of ESCC patients remain dismal. Therefore, there is an urgent need to establish a framework through genomic profiling to facilitate the development of precision therapies for ESCC. Methods: To characterize therapeutic targets in 118 Chinese ESCC patients, deep panel sequencing of 831 cancer genes (OncoPanscan, Genetronhealth) was performed on their tumor tissues and paired genomic DNA samples. Results: The most frequently mutated genes in our ESCC cohort were TP53 (97%), PIK3CA (19%), CDKN2A (18%), NOTCH1 (17%), KMT2D (15%), LRP1B (15%) NOTCH3 (15%) NFE2L2 (13%), and EP300 (12%). Consistent with previous reports, we found significantly elevated mutations in cancer-related genes including NOTCH1 (16.9%), NOTCH2 (3.2%), NOTCH3 (15.3%) and RB1 (9.3%). Importantly, 17.8% (21/118) patients in our cohort harbored the 11q13 amplicon ( CCND1, FGF3, FGF4 and FGF19). The median copy number was 8.19 (range 6.07-42.3). These patients can participate in clinical trials with FGFR inhibitor alone or in combination with CDK4/6 inhibitors. Additionally, we also observed frequent genetic alterations in the KEAP1 (Kelch-like ECH-associated protein 1)-NFE2L2 (nuclear factor erythroid 2 like 2)-CUL3 (cullin 3) pathway. 80% (12/15) of missense mutations in NFE2L2 were located at the KEAP1 binding domain of NRF2 protein. These mutations were either around the ETGE motif (D77G, E79Q, G81V/D and E82D) or the DLG motif (D27V, I28T, D29G, L30F, G31E, V32E, R34G). We also identified four missense mutations of KEAP1 and one alternation of CUL3 in splicing site. Taken together, 17% (20/118) of ESCC patients harbored mutations in the NFE2L2/KEAP1/CUL3 pathway, which may be eligible for clinical trials of glutaminase inhibitor telaglenastat. Two patients had high level of ERBB2 amplification which can be targeted with anti-HER2 therapy. Furthermore, 11.9% (14/118) patients carried activating PIK3CA mutations including N345K, E542K, E545K, M1043I and H1047R which may be targeted by PIK3CA inhibitor alpelisib. Lastly, patients with loss-of-function mutation in NF1 (n = 4), STK11 (n = 1) and PTEN (n = 3) can be respectively targeted with MEK inhibitor and mTOR inhibitor. Overall, 43% of patients in our ESCC cohort had actionable genetic mutations with corresponding precision therapy options. Conclusions: Our findings indicated that amplification of the 11q13 amplicon and dysfunction of the KEAP1-NRF2-CUL3 axis are the major driving events of ESCC. The results of genomic profiling can guide physicians to enroll a significant portion of ESCC patients into genomically matched clinical trials.

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Comparative Analysis of Public Knowledge Bases for Precision Oncology

JCO Precision Oncology ◽

10.1200/po.18.00371 ◽

2019 ◽

pp. 1-8 ◽

Cited By ~ 3

Author(s):

Steffen Pallarz ◽

Manuela Benary ◽

Mario Lamping ◽

Damian Rieke ◽

Johannes Starlinger ◽

...

Keyword(s):

Genetic Alterations ◽

Knowledge Bases ◽

Tumor Board ◽

Comprehensive Cancer Center ◽

Cancer Center ◽

Accurate Information ◽

Precision Oncology ◽

Cancer Genes ◽

Qualitative Comparison ◽

Data Set

PURPOSE Precision oncology depends on the availability of up-to-date, comprehensive, and accurate information about associations between genetic variants and therapeutic options. Recently, a number of knowledge bases (KBs) have been developed that gather such information on the basis of expert curation of the scientific literature. We performed a quantitative and qualitative comparison of Clinical Interpretations of Variants in Cancer, OncoKB, Cancer Gene Census, Database of Curated Mutations, CGI Biomarkers (the cancer genome interpreter biomarker database), Tumor Alterations Relevant for Genomics-Driven Therapy, and the Precision Medicine Knowledge Base. METHODS We downloaded each KB and restructured their content to describe variants, genes, drugs, and gene-drug associations in a common format. We normalized gene names to Entrez Gene IDs and drug names to ChEMBL and DrugBank IDs. For the analysis of clinically relevant gene-drug associations, we obtained lists of genes affected by genetic alterations and putative drug therapies for 113 patients with cancer whose cases were presented at the Molecular Tumor Board (MTB) of the Charité Comprehensive Cancer Center. RESULTS Our analysis revealed that the KBs are largely overlapping but also that each source harbors a notable amount of unique information. Although some KBs cover more genes, others contain more data about gene-drug associations. Retrospective comparisons with findings of the Charitè MTB at the gene level showed that use of multiple KBs may considerably improve retrieval results. The relative importance of a KB in terms of cancer genes was assessed in more detail by logistic regression, which revealed that all but one source had a notable impact on result quality. We confirmed these findings using a second data set obtained from an independent MTB. CONCLUSION To date, none of the existing publicly available KBs on gene-drug associations in precision oncology fully subsumes the others, but all of them exhibit specific strengths and weaknesses. Consideration of multiple KBs, therefore, is essential to obtain comprehensive results.

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Immunohistological Expression of SOX-10 in Triple-Negative Breast Cancer: A Descriptive Analysis of 113 Samples

International Journal of Molecular Sciences ◽

10.3390/ijms21176407 ◽

2020 ◽

Vol 21 (17) ◽

pp. 6407 ◽

Cited By ~ 1

Author(s):

Katharina Kriegsmann ◽

Christa Flechtenmacher ◽

Jörg Heil ◽

Jörg Kriegsmann ◽

Gunhild Mechtersheimer ◽

...

Keyword(s):

Breast Cancer ◽

Triple Negative Breast Cancer ◽

Triple Negative ◽

Descriptive Analysis ◽

Biological Significance ◽

Genetic Alterations ◽

Prognostic Impact ◽

Cancer Genes ◽

Sequencing Data ◽

Disease Free

Background: SRY-related HMG-box 10 (SOX-10) is commonly expressed in triple negative breast cancer (TNBC). However, data on the biological significance of SOX-10 expression is limited. Therefore, we investigated immunhistological SOX-10 expression in TNBC and correlated the results with genetic alterations and clinical data. Methods: A tissue microarray including 113 TNBC cases was stained by SOX-10. Immunohistological data of AR, BCL2, CD117, p53 and Vimentin was available from a previous study. Semiconductor-based panel sequencing data including commonly altered breast cancer genes was also available from a previous investigation. SOX-10 expression was correlated with clinicopathological, immunohistochemical and genetic data. Results: SOX-10 was significantly associated with CD117 and Vimentin, but not with AR expression. An association of SOX-10 with BCL2, EGFR or p53 staining was not observed. SOX-10-positive tumors harbored more often TP53 mutations but less frequent mutations of PIK3CA or alterations of the PIK3K pathway. SOX-10 expression had no prognostic impact either on disease-free, distant disease-free, or overall survival. Conclusions: While there might be a value of SOX-10 as a differential diagnostic marker to identify metastases of TNBC, its biological role remains to be investigated.

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ENDOCRINE TUMOURS: Advances in the molecular pathogenesis of thyroid cancer: lessons from the cancer genome

Acta Endocrinologica ◽

10.1530/eje-16-0202 ◽

2016 ◽

Vol 175 (5) ◽

pp. R203-R217 ◽

Cited By ~ 25

Author(s):

Garcilaso Riesco-Eizaguirre ◽

Pilar Santisteban

Keyword(s):

Thyroid Cancer ◽

Cancer Genomics ◽

Treatment Strategies ◽

Genetic Alterations ◽

Cancer Genome ◽

Molecular Pathogenesis ◽

Cancer Genes ◽

New Information ◽

Novel Treatment Strategies ◽

And Behavior

Thyroid cancer is the most common endocrine malignancy giving rise to one of the most indolent solid cancers, but also one of the most lethal. In recent years, systematic studies of the cancer genome, most importantly those derived from The Cancer Genome Altas (TCGA), have catalogued aberrations in the DNA, chromatin, and RNA of the genomes of thousands of tumors relative to matched normal cellular genomes and have analyzed their epigenetic and protein consequences. Cancer genomics is therefore providing new information on cancer development and behavior, as well as new insights into genetic alterations and molecular pathways. From this genomic perspective, we will review the main advances concerning some essential aspects of the molecular pathogenesis of thyroid cancer such as mutational mechanisms, new cancer genes implicated in tumor initiation and progression, the role of non-coding RNA, and the advent of new susceptibility genes in thyroid cancer predisposition. This look across these genomic and cellular alterations results in the reshaping of the multistep development of thyroid tumors and offers new tools and opportunities for further research and clinical development of novel treatment strategies.

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A heuristic platform for clinical interpretation of cancer genome sequencing data.

Journal of Clinical Oncology ◽

10.1200/jco.2012.30.15_suppl.10502 ◽

2012 ◽

Vol 30 (15_suppl) ◽

pp. 10502-10502

Author(s):

Eliezer Mendel Van Allen ◽

Nikhil Wagle ◽

Gregory Kryukov ◽

Alexis Ramos ◽

Gad Getz ◽

...

Keyword(s):

Prostate Cancer ◽

Genome Sequencing ◽

Heuristic Algorithm ◽

Genetic Alterations ◽

Cancer Genome ◽

Clinical Samples ◽

Whole Genome ◽

Cancer Genes ◽

Sequencing Data ◽

Clinical Interpretation

10502 Background: The ability to identify and effectively sort the full spectrum of biologically and therapeutically relevant genetic alterations identified by massively parallel sequencing may improve cancer care. A major challenge involves rapid and rational categorization of data-intensive output, including somatic mutations, insertions/deletions, copy number alterations, and rearrangements into ranked categories for clinician review. Methods: A database of clinically actionable alterations was created, consisting of over 100 annotated genes known to undergo somatic genomic alterations in cancer that may impact clinical decision-making. A heuristic algorithm was developed, which selectively identifies somatic alterations based on the clinically actionable alterations database. Remaining variants are sorted based on additional heuristics, including high priority alterations based on presence in the Cancer Gene Census, biologically significant cancer genes based on presence in COSMIC or MSigDB, and low priority alterations in the same gene family as biologically significant cancer genes. The heuristic algorithm was applied to whole exome sequencing data of clinical samples and whole genome sequencing data from a cohort of prostate cancer samples processed using established Broad Institute pipelines. Results: Application of the heuristic algorithm to the prostate cancer whole genome rearrangement data identified 172 (out of 5978) rearrangements involving actionable genes (averaging 2-3 events per tumor). Furthermore, two clinical samples processed prospectively were analyzed, yielding three potentially actionable alterations for clinical review. Conclusions: The heuristic model for clinical interpretation of next generation sequencing data may facilitate rapid analysis of tumor genomic information for clinician review by identifying and prioritizing alterations that can directly impact care. Our platform can also be applied to research data to prospectively explore clinically relevant findings from existing cohorts. Future analytical approaches using heuristic or probabilistic algorithms should underpin a robust prospective assessment of clinical cancer genome data.

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Performance of next-generation sequencing for detection of clinically actionable genetic variants in cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2013.31.15_suppl.11099 ◽

2013 ◽

Vol 31 (15_suppl) ◽

pp. 11099-11099

Author(s):

Mohammed Omar Hussaini ◽

Ian S. Hagemann ◽

Teresa Mary Cox ◽

Christina Lockwood ◽

Karen Seibert ◽

...

Keyword(s):

Next Generation Sequencing ◽

Genetic Variants ◽

Simultaneous Detection ◽

Genetic Alterations ◽

Sequence Variants ◽

Tumor Type ◽

Cancer Genes ◽

Next Generation ◽

Therapeutic Implications ◽

Generation Sequencing

11099 Background: Next-generation sequencing (NGS) allows for simultaneous detection of numerous actionable somatic variants in cancer. We have implemented a clinical NGS panel to detect genetic alterations in 25 genes with established roles in cancer and report here the frequency of clinically actionable genetic variants in a variety of cancer types. Methods: NGS testing was performed in a CAP-certified, CLIA-licensed environment on DNA extracted from FFPE tissue in 209 cases spanning 41 histologic tumor types. DNA was enriched by hybrid capture and sequenced to >1,000x average coverage on Illumina sequencers with 2x101bp or 2x150bp reads. Variants were called using clinically validated parameters using the Genome Analysis Toolkit, Pindel, and the custom-written Clinical Genomicist Workstation. Results: Non-small cell lung cancer (45%), pancreatic cancer (10%), and colorectal cancer (8%) were the most common tumors sent for NGS analysis. An average of 3 (range 1- 16) non-synonymous, non-SNP sequence variants per case (SNVs and indels) were detected in the 130kb exonic target. Variants were most commonly seen in TP53, KRAS, and EGFR. 27% of cases (56/209) had one or more variants with therapeutic implications for the tumor type tested (e.g., EGFR mutation in NSCLC). 15% of cases (32/209) showed actionable variants not generally associated with the malignancy tested (e.g., detection of an activating KITvariant in thymic carcinoma). 10% of cases (21/209) had variants that were prognostically significant but not directly targetable. Some cases (9%) had variants that were prognostic/diagnostic and targetable. In 117 cases (56% of total), no therapeutically or prognostically significant variants were identified. Overall, in 92 cases (44%), NGS testing yielded information with therapeutic (majority), prognostic, or diagnostic ramifications. Conclusions: We found that 44% of unselected cancer cases have clinically relevant sequence variants in a set of 25 commonly mutated cancer genes. Our data suggest that clinical NGS testing may serve as an integral tool in realizing the potential of precision medicine in oncology.

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Circulating tumor DNA analysis using targeted sequencing of 508 clinically actionable genes in patients with high grade serous ovarian cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2017.35.15_suppl.5582 ◽

2017 ◽

Vol 35 (15_suppl) ◽

pp. 5582-5582

Author(s):

Anniina Färkkilä ◽

Liina Salminen ◽

Kaisa Huhtinen ◽

Sakari Hietanen ◽

Seija Elisa Grenman ◽

...

Keyword(s):

Ovarian Cancer ◽

Tumor Tissue ◽

Genetic Alterations ◽

Gene Panel ◽

Targeted Sequencing ◽

Primary Therapy ◽

High Grade ◽

Serous Ovarian Cancer ◽

Cancer Genes ◽

Treatment Toxicity

5582 Background: The prediction of tumor chemoresponse and treatment toxicity is crucial for optimal patient care in high grade serous ovarian cancer (HGSC). We employed a targeted sequencing panel of 508 clinically annotated cancer genes to screen for actionable genetic variants in tumor tissue and ctDNA of patients with advanced HGSC. Methods: Tumor tissue, and serial plasma samples at diagnosis and during primary therapy were obtained from five patients with FIGO Stage IIIc HGSC. All patients were surgically debulked and received standard carboplatin and paclitaxel chemotherapy. DNA isolated from tumor tissue and plasma was analyzed for genetic alterations by targeted deep-sequencing of 508 previously annotated cancer genes. Somatic variants were systematically reported for alterations related to drug sensitivity and treatment toxicity, and analyzed with respect to clinical parameters and primary therapy outcomes. Results: In tumor tissues, and the corresponding pre-treatment ctDNA, oncogenic mutations were detected at a median of 13.0 and 1.6 allelic frequencies, respectively. The mutation frequency was higher, and also more unique mutations were detected in ctDNA of patients presenting with high tumor spread. Interestingly, a de-novo ctDNA MAPK1 mutation was detected in a sample taken during chemotherapy with partial response, while, no new mutations emerged in a patient with complete response. Analysis of the pretreatment plasma ctDNA revealed profiles of low and high drug sensitivities consistent with the clinical course of the patients. In two patients, increased risk profiles for treatment toxicities were identified via e.g. GSTP1. Consistently, these two patients were forced to discontinue standard therapy. Conclusions: Panel-based targeted sequencing of ctDNA identified potentially actionable mutations, and reflected tumor heterogeneity of HGSC. Further, the ctDNA gene panel annotations showed concordance with the chemoresponse- and treatment toxicity profiles, suggesting that ctDNA gene panel maybe a feasible approach to individualize treatment of HGSC patients.

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