Clinical Value of Timely Targeted Therapy for Patients With Advanced Non-Small Cell Lung Cancer With Actionable Driver Oncogenes.

BACKGROUND: A recent real-world study observed that 24% of patients with advanced non-small cell lung cancer (aNSCLC) with actionable driver oncogenes (ADOs) initiated nontargeted therapies before biomarker test results became available. This study assessed the clinical impact of the timing of first-line (1L) targeted therapies (TTs) in aNSCLC. MATERIALS AND METHODS: This retrospective analysis of a nationwide electronic health record-derived deidentified database included patients aged ≥18 years diagnosed with aNSCLC with ADOs (ALK, BRAF, EGFR, RET, MET, ROS-1, and NTRK) from January 1, 2015, to October 18, 2022, by biomarker testing within 90 days after advanced diagnosis and received 1L treatment. Cohorts were defined by treatment patterns ≤42 days after test results: "Upfront TT" received 1L TT ≤42 days; "Switchers" initiated 1L non-TT before or after testing but switched to TT ≤42 days; and "Non-switchers" initiated non-TT before or after testing and did not switch at any time. Adjusted multivariate Cox regression evaluated real-world progression-free survival, real-world time to next treatment or death, and real-world overall survival. RESULTS: A total of 3540 patients met the study criteria; 78% were treated in a community setting, and 50% underwent next-generation sequencing (NGS). There was no significant difference in outcomes between Switchers and Upfront TT; inferior outcomes were observed in Non-switchers versus Upfront TT. CONCLUSION: Our findings demonstrated improved outcomes with upfront 1L TT versus non-TT in patients with aNSCLC with ADOs and observed timely switching to TT after biomarker test result had similar outcomes to Upfront TT. Opportunities remain to improve the use of NGS for early ADO identification and determination of 1L TT.

Selective inhibition of MCL1 overcomes venetoclax resistance in a murine model of myelodysplastic syndromes.

Treatment for myelodysplastic syndromes (MDS) remains insufficient due to clonal heterogeneity and lack of effective clinical therapies. Dysregulation of apoptosis is observed across MDS subtypes regardless of mutations and represents an attractive therapeutic opportunity. Venetoclax (VEN), a selective inhibitor of anti-apoptotic protein B-cell lymphoma- 2 (BCL2), has yielded impressive responses in older patients with acute myeloid leukemia (AML) and high risk MDS. BCL2 family anti-apoptotic proteins BCL-XL and induced myeloid cell leukemia 1 (MCL1) are implicated in leukemia survival, and upregulation of MCL1 is seen in VEN-resistant AML and MDS. We determined in vitro sensitivity of MDS patient samples to selective inhibitors of BCL2, BCL-XL and MCL1. While VEN response positively correlated with MDS with excess blasts, all MDS subtypes responded to MCL1 inhibition. Treatment with combined VEN + MCL1 inhibtion was synergistic in all MDS subtypes without significant injury to normal hematopoiesis and reduced MDS engraftment in MISTRG6 mice, supporting the pursuit of clinical trials with combined BCL2 + MCL1 inhibition in MDS.

The World Health Organization COVID-19 surveillance database.

In January 2020, SARS-CoV-2 virus was identified as a cause of an outbreak in China. The disease quickly spread worldwide, and the World Health Organization (WHO) declared the pandemic in March 2020.From the first notifications of spread of the disease, the WHO's Emergency Programme implemented a global COVID-19 surveillance system in coordination with all WHO regional offices. The system aimed to monitor the spread of the epidemic over countries and across population groups, severity of the disease and risk factors, and the impact of control measures. COVID-19 surveillance data reported to WHO is a combination of case-based data and weekly aggregated data, focusing on a minimum global dataset for cases and deaths including disaggregation by age, sex, occupation as a Health Care Worker, as well as number of cases tested, and number of cases newly admitted for hospitalization. These disaggregations aim to monitor inequities in COVID-19 distribution and risk factors among population groups.SARS-CoV-2 epidemic waves continue to sweep the world; as of March 2022, over 445 million cases and 6 million deaths have been reported worldwide. Of these, over 327 million cases (74%) have been reported in the WHO surveillance database, of which 255 million cases (57%) are disaggregated by age and sex. A public dashboard has been made available to visualize trends, age distributions, sex ratios, along with testing and hospitalization rates. It includes a feature to download the underlying dataset.This paper will describe the data flows, database, and frontend public dashboard, as well as the challenges experienced in data acquisition, curation and compilation and the lessons learnt in overcoming these. Two years after the pandemic was declared, COVID-19 continues to spread and is still considered a Public Health Emergency of International Concern (PHEIC). While WHO regional and country offices have demonstrated tremendous adaptability and commitment to process COVID-19 surveillance data, lessons learnt from this major event will serve to enhance capacity and preparedness at every level, as well as institutional empowerment that may lead to greater sharing of public health evidence during a PHEIC, with a focus on equity.

Framework for Implementing and Tracking a Molecular Tumor Board at a National Cancer Institute-Designated Comprehensive Cancer Center.

BACKGROUND: Over the past few years, tumor next-generation sequencing (NGS) panels have evolved in complexity and have changed from selected gene panels with a handful of genes to larger panels with hundreds of genes, sometimes in combination with paired germline filtering and/or testing. With this move toward increasingly large NGS panels, we have rapidly outgrown the available literature supporting the utility of treatments targeting many reported gene alterations, making it challenging for oncology providers to interpret NGS results and make a therapy recommendation for their patients. METHODS: To support the oncologists at Vanderbilt-Ingram Cancer Center (VICC) in interpreting NGS reports for patient care, we initiated two molecular tumor boards (MTBs)-a VICC-specific institutional board for our patients and a global community MTB open to the larger oncology patient population. Core attendees include oncologists, hematologist, molecular pathologists, cancer geneticists, and cancer genetic counselors. Recommendations generated from MTB were documented in a formal report that was uploaded to our electronic health record system. RESULTS: As of December 2020, we have discussed over 170 patient cases from 77 unique oncology providers from VICC and its affiliate sites, and a total of 58 international patient cases by 25 unique providers from six different countries across the globe. Breast cancer and lung cancer were the most presented diagnoses. CONCLUSION: In this article, we share our learning from the MTB experience and document best practices at our institution. We aim to lay a framework that allows other institutions to recreate MTBs. IMPLICATIONS FOR PRACTICE: With the rapid pace of molecularly driven therapies entering the oncology care spectrum, there is a need to create resources that support timely and accurate interpretation of next-generation sequencing reports to guide treatment decision for patients. Molecular tumor boards (MTB) have been created as a response to this knowledge gap. This report shares implementation strategies and best practices from the Vanderbilt experience of creating an institutional MTB and a virtual global MTB for the larger oncology community. This report describe a reproducible framework that can be adopted to initiate MTBs at other institutions.

Adduct annotation in liquid chromatography/high-resolution mass spectrometry to enhance compound identification.

Annotation and interpretation of full scan electrospray mass spectra of metabolites is complicated by the presence of a wide variety of ions. Not only protonated, deprotonated, and neutral loss ions but also sodium, potassium, and ammonium adducts as well as oligomers are frequently observed. This diversity challenges automatic annotation and is often poorly addressed by current annotation tools. In many cases, annotation is integrated in metabolomics workflows and is based on specific chromatographic peak-picking tools. We introduce mzAdan, a nonchromatography-based multipurpose standalone application that was developed for the annotation and exploration of convolved high-resolution ESI-MS spectra. The tool annotates single or multiple accurate mass spectra using a customizable adduct annotation list and outputs a list of [M+H]+ candidates. MzAdan was first tested with a collection of 408 analytes acquired with flow injection analysis. This resulted in 402 correct [M+H]+ identifications and, with combinations of sodium, ammonium, and potassium adducts and water and ammonia losses within a tolerance of 10 mmu, explained close to 50% of the total ion current. False positives were monitored with mass accuracy and bias as well as chromatographic behavior which led to the identification of adducts with calcium instead of the expected potassium. MzAdan was then integrated in a workflow with XCMS for the untargeted LC-MS data analysis of a 52 metabolite standard mix and a human urine sample. The results were benchmarked against three other annotation tools, CAMERA, findMAIN, and CliqueMS: findMAIN and mzAdan consistently produced higher numbers of [M+H]+ candidates compared with CliqueMS and CAMERA, especially with co-eluting metabolites. Detection of low-intensity ions and correct grouping were found to be essential for annotation performance. Graphical abstract.

Genomic Underpinnings of Tumor Behavior in In Situ and Early Lung Adenocarcinoma.

Rationale: We have a limited understanding of the molecular underpinnings of early adenocarcinoma (ADC) progression. We hypothesized that the behavior of early ADC can be predicted based on genomic determinants.Objectives: To identify genomic alterations associated with resected indolent and aggressive early lung ADCs.Methods: DNA was extracted from 21 ADCs in situ (AISs), 27 minimally invasive ADCs (MIAs), and 54 fully invasive ADCs. This DNA was subjected to deep next-generation sequencing and tested against a custom panel of 347 cancer genes.Measurements and Main Results: Sequencing data was analyzed for associations among tumor mutation burden, frequency of mutations or copy number alterations, mutation signatures, intratumor heterogeneity, pathway alterations, histology, and overall survival. We found that deleterious mutation burden was significantly greater in invasive ADC, whereas more copy number loss was observed in AIS and MIA. Intratumor heterogeneity establishes early, as in AIS. Twenty-one significantly mutated genes were shared among the groups. Mutation signature profiling did not vary significantly, although the APOBEC signature was associated with ADC and poor survival. Subclonal KRAS mutations and a gene signature consisting of PIK3CG, ATM, EPPK1, EP300, or KMT2C mutations were also associated with poor survival. Mutations of KRAS, TP53, and NF1 were found to increase in frequency from AIS and MIA to ADC. A cancer progression model revealed selective early and late drivers.Conclusions: Our results reveal several genetic driver events, clonality, and mutational signatures associated with poor outcome in early lung ADC, with potential future implications for the detection and management of ADC.

Robust stratification of breast cancer subtypes using differential patterns of transcript isoform expression.

Breast cancer, the second leading cause of cancer death of women worldwide, is a heterogenous disease with multiple different subtypes. These subtypes carry important implications for prognosis and therapy. Interestingly, it is known that these different subtypes not only have different biological behaviors, but also have distinct gene expression profiles. However, it has not been rigorously explored whether particular transcriptional isoforms are also differentially expressed among breast cancer subtypes, or whether transcript isoforms from the same sets of genes can be used to differentiate subtypes. To address these questions, we analyzed the patterns of transcript isoform expression using a small set of RNA-sequencing data for eleven Estrogen Receptor positive (ER+) subtype and fourteen triple negative (TN) subtype tumors. We identified specific sets of isoforms that distinguish these tumor subtypes with higher fidelity than standard mRNA expression profiles. We found that alternate promoter usage, alternative splicing, and alternate 3'UTR usage are differentially regulated in breast cancer subtypes. Profiling of isoform expression in a second, independent cohort of 68 tumors confirmed that expression of splice isoforms differentiates breast cancer subtypes. Furthermore, analysis of RNAseq data from 594 cases from the TCGA cohort confirmed the ability of isoform usage to distinguish breast cancer subtypes. Also using our expression data, we identified several RNA processing factors that were differentially expressed between tumor subtypes and/or regulated by estrogen receptor, including YBX1, YBX2, MAGOH, MAGOHB, and PCBP2. RNAi knock-down of these RNA processing factors in MCF7 cells altered isoform expression. These results indicate that global dysregulation of splicing in breast cancer occurs in a subtype-specific and reproducible manner and is driven by specific differentially expressed RNA processing factors.

Mitochondria sequence mapping strategies and practicability of mitochondria variant detection from exome and RNA sequencing data.

The rapid progress in high-throughput sequencing has significantly enriched our capacity for studying the mitochondrial DNA (mtDNA). In addition to performing specific mitochondrial targeted sequencing, an increasingly popular alternative approach is using the off-target reads from exome sequencing to infer mtDNA variants, including single nucleotide polymorphisms (SNPs) and heteroplasmy. However, the effectiveness and practicality of this approach have not been tested. Recently, RNAseq data have also been suggested as a good source for alternative data mining, but whether mitochondrial variants can be detected from RNAseq data has not been validated. We designed a study to evaluate the practicability of mtDNA variant detection using exome and RNA sequencing data. Five breast cancer cell lines were sequenced through mitochondrial targeted, exome, and RNA sequencing. Mitochondrial targeted sequencing was used as the gold standard to compute the validation and false discovery rates of SNP and heteroplasmy detection in exome and RNAseq data. We found that exome and RNA sequencing can accurately detect mitochondrial SNPs. However, the lower false discovery rate makes exome sequencing a better choice for heteroplasmy detection than RNAseq. Furthermore, we examined three alignment strategies and found that aligning reads directly to the mitochondrial reference genome or aligning reads to the nuclear and mitochondrial references genomes simultaneously produced the best results, and that aligning to the nuclear genome first and afterwards to the mitochondrial genome performed poorly. In conclusion, our study provides important guidelines for future studies that intend to use either exome sequencing or RNAseq data to infer mitochondrial SNPs and heteroplasmy.

Systematic mapping of occluded genes by cell fusion reveals prevalence and stability of cis-mediated silencing in somatic cells.

Both diffusible factors acting in trans and chromatin components acting in cis are implicated in gene regulation, but the extent to which either process causally determines a cell's transcriptional identity is unclear. We recently used cell fusion to define a class of silent genes termed "cis-silenced" (or "occluded") genes, which remain silent even in the presence of trans-acting transcriptional activators. We further showed that occlusion of lineage-inappropriate genes plays a critical role in maintaining the transcriptional identities of somatic cells. Here, we present, for the first time, a comprehensive map of occluded genes in somatic cells. Specifically, we mapped occluded genes in mouse fibroblasts via fusion to a dozen different rat cell types followed by whole-transcriptome profiling. We found that occluded genes are highly prevalent and stable in somatic cells, representing a sizeable fraction of silent genes. Occluded genes are also highly enriched for important developmental regulators of alternative lineages, consistent with the role of occlusion in safeguarding cell identities. Alongside this map, we also present whole-genome maps of DNA methylation and eight other chromatin marks. These maps uncover a complex relationship between chromatin state and occlusion. Furthermore, we found that DNA methylation functions as the memory of occlusion in a subset of occluded genes, while histone deacetylation contributes to the implementation but not memory of occlusion. Our data suggest that the identities of individual cell types are defined largely by the occlusion status of their genomes. The comprehensive reference maps reported here provide the foundation for future studies aimed at understanding the role of occlusion in development and disease.

Optimization by infusion of multiple reaction monitoring transitions for sensitive quantification of peptides by liquid chromatography/mass spectrometry.

RATIONALE: In peptide quantification by liquid chromatography/mass spectrometry (LC/MS), the optimization of multiple reaction monitoring (MRM) parameters is essential for sensitive detection. We have compared different approaches to build MRM assays, based either on flow injection analysis (FIA) of isotopically labelled peptides, or on the knowledge and the prediction of the best settings for MRM transitions and collision energies (CE). In this context, we introduce MRMOptimizer, an open-source software tool that processes spectra and assists the user in selecting transitions in the FIA workflow. METHODS: MS/MS spectral libraries with CE voltages from 10 to 70 V are automatically acquired in FIA mode for isotopically labelled peptides. Then MRMOptimizer determines the optimal MRM settings for each peptide. To assess the quantitative performance of our approach, 155 peptides, representing 84 proteins, were analysed by LC/MRM-MS and the peak areas were compared between: (A) the MRMOptimizer-based workflow, (B1) the SRMAtlas transitions set used 'as-is'; (B2) the same SRMAtlas set with CE parameters optimized by Skyline. RESULTS: 51% of the three most intense transitions per peptide were shown to be common to both A and B1/B2 methods, and displayed similar sensitivity and peak area distributions. The peak areas obtained with MRMOptimizer for transitions sharing either the precursor ion charge state or the fragment ions with the SRMAtlas set at unique transitions were increased 1.8- to 2.3-fold. The gain in sensitivity using MRMOptimizer for transitions with different precursor ion charge state and fragment ions (8% of the total), reaches a ~ 11-fold increase. CONCLUSIONS: Isotopically labelled peptides can be used to optimize MRM transitions more efficiently in FIA than by searching databases. The MRMOptimizer software is MS independent and enables the post-acquisition selection of MRM parameters. Coefficients of variation for optimal CE values are lower than those obtained with the SRMAtlas approach (B2) and one additional peptide was detected. Copyright © 2017 John Wiley & Sons, Ltd.

Activating PIK3CA Mutations Induce an Epidermal Growth Factor Receptor (EGFR)/Extracellular Signal-regulated Kinase (ERK) Paracrine Signaling Axis in Basal-like Breast Cancer.

Mutations in PIK3CA, the gene encoding the p110α catalytic subunit of phosphoinositide 3-kinase (PI3K) have been shown to transform human mammary epithelial cells (MECs). These mutations are present in all breast cancer subtypes, including basal-like breast cancer (BLBC). Using liquid chromatography-tandem mass spectrometry (LC-MS/MS), we identified 72 protein expression changes in human basal-like MECs with knock-in E545K or H1047R PIK3CA mutations versus isogenic MECs with wild-type PIK3CA. Several of these were secreted proteins, cell surface receptors or ECM interacting molecules and were required for growth of PIK3CA mutant cells as well as adjacent cells with wild-type PIK3CA. The proteins identified by MS were enriched among human BLBC cell lines and pointed to a PI3K-dependent amphiregulin/EGFR/ERK signaling axis that is activated in BLBC. Proteins induced by PIK3CA mutations correlated with EGFR signaling and reduced relapse-free survival in BLBC. Treatment with EGFR inhibitors reduced growth of PIK3CA mutant BLBC cell lines and murine mammary tumors driven by a PIK3CA mutant transgene, all together suggesting that PIK3CA mutations promote tumor growth in part by inducing protein changes that activate EGFR.

CUX1 is a haploinsufficient tumor suppressor gene on chromosome 7 frequently inactivated in acute myeloid leukemia.

Loss of chromosome 7 and del(7q) [-7/del(7q)] are recurring cytogenetic abnormalities in hematologic malignancies, including acute myeloid leukemia and therapy-related myeloid neoplasms, and associated with an adverse prognosis. Despite intensive effort by many laboratories, the putative myeloid tumor suppressor(s) on chromosome 7 has not yet been identified.We performed transcriptome sequencing and SNP array analysis on de novo and therapy-related myeloid neoplasms, half with -7/del(7q). We identified a 2.17-Mb commonly deleted segment on chromosome band 7q22.1 containing CUX1, a gene encoding a homeodomain-containing transcription factor. In 1 case, CUX1 was disrupted by a translocation, resulting in a loss-of-function RNA fusion transcript. CUX1 was the most significantly differentially expressed gene within the commonly deleted segment and was expressed at haploinsufficient levels in -7/del(7q) leukemias. Haploinsufficiency of the highly conserved ortholog, cut, led to hemocyte overgrowth and tumor formation in Drosophila melanogaster. Similarly, haploinsufficiency of CUX1 gave human hematopoietic cells a significant engraftment advantage on transplantation into immunodeficient mice. Within the RNA-sequencing data, we identified a CUX1-associated cell cycle transcriptional gene signature, suggesting that CUX1 exerts tumor suppressor activity by regulating proliferative genes. These data identify CUX1 as a conserved, haploinsufficient tumor suppressor frequently deleted in myeloid neoplasms.

Aberrant activation of NF-κB signaling in mammary epithelium leads to abnormal growth and ductal carcinoma in situ.

BACKGROUND: Approximately 1 in 5 women diagnosed with breast cancer are considered to have in situ disease, most often termed ductal carcinoma in situ (DCIS). Though recognized as a risk factor for the development of more invasive cancer, it remains unclear what factors contribute to DCIS development. It has been shown that inflammation contributes to the progression of a variety of tumor types, and nuclear factor kappa B (NF-κB) is recognized as a master-regulator of inflammatory signaling. However, the contributions of NF-κB signaling to tumor initiation are less well understood. Aberrant up-regulation of NF-κB activity, either systemically or locally within the breast, could occur due to a variety of commonly experienced stimuli such as acute infection, obesity, or psychological stress. In this study, we seek to determine if activation of NF-κB in mammary epithelium could play a role in the formation of hyperplastic ductal lesions. METHODS: Our studies utilize a doxycycline-inducible transgenic mouse model in which constitutively active IKKß is expressed specifically in mammary epithelium. All previously published models of NF-κB modulation in the virgin mammary gland have been constitutive models, with transgene or knock-out present throughout the life and development of the animal. For the first time, we will induce activation at later time points after normal ducts have formed, thus being able to determine if NF-κB activation can promote pre-malignant changes in previously normal mammary epithelium. RESULTS: We found that even a short pulse of NF-κB activation could induce profound remodeling of mammary ductal structures. Short-term activation created hyperproliferative, enlarged ducts with filled lumens. Increased expression of inflammatory markers was concurrent with the down-regulation of hormone receptors and markers of epithelial differentiation. Furthermore, the oncoprotein mucin 1, known to be up-regulated in human and mouse DCIS, was over-expressed and mislocalized in the activated ductal tissue. CONCLUSIONS: These results indicate that aberrant NF-κB activation within mammary epithelium can lead to molecular and morphological changes consistent with the earliest stages of breast cancer. Thus, inhibition of NF-κB signaling following acute inflammation or the initial signs of hyperplastic ductal growth could represent an important opportunity for breast cancer prevention.

SMARCB1 expression in epithelioid sarcoma is regulated by miR-206, miR-381, and miR-671-5p on Both mRNA and protein levels.

Proximal type epithelioid sarcoma shares similarities with malignant rhabdoid tumor, including the lack of nuclear immunoreactivity of SMARCB1. Biallelic mutation of SMARCB1 has been convincingly established as the cause of loss of protein expression in rhabdoid tumor, but the cause in epithelioid sarcoma remains unknown. In our previous work, we demonstrated that DNA hypermethylation and post-translational modification mechanisms were not involved. In this current work, we explored the hypothesis that miRNAs regulate SMARCB1 gene expression in epithelioid sarcomas. In silico target prediction analysis revealed eight candidate miRNAs, and quantitative PCR-in 32 formalin-fixed, paraffin-embedded tumor samples comprising 30 epithelioid sarcomas and two malignant rhabdoid tumors-demonstrated significant (P < 0.001) overexpression of four miRNAs in epithelioid sarcomas: miR-206, miR-381, miR-671-5p, and miR-765. Two human tumors (fibrosarcoma and colon adenocarcinoma) and a normal cell line (human dermal fibroblast) with retained SMARCB1 expression were cultured for miRNA transient transfection (electroporation) experiments. SMARCB1 mRNA expression was analyzed by quantitative real-time PCR and immunostaining of SMARCB1 was performed to examine the effect of miRNAs transfections on both RNA and protein levels. Only three of the overexpressed miRNAs (miR-206, miR-381, and miR-671-5p) could silence the SMARCB1 mRNA expression in cell cultures; most effectively miR-206. Transfection of miR-206, miR-381, miR-671-5p, and some combination of them also eliminated SMARCB1 nuclear staining, demonstrating a strong effect on not only mRNA but also protein levels. Our results suggest loss of SMARCB1 protein expression in epithelioid sarcoma is due to the epigenetic mechanism of gene silencing by oncomiRs.

Detection of internal exon deletion with exon Del.

BACKGROUND: Exome sequencing allows researchers to study the human genome in unprecedented detail. Among the many types of variants detectable through exome sequencing, one of the most over looked types of mutation is internal deletion of exons. Internal exon deletions are the absence of consecutive exons in a gene. Such deletions have potentially significant biological meaning, and they are often too short to be considered copy number variation. Therefore, to the need for efficient detection of such deletions using exome sequencing data exists. RESULTS: We present ExonDel, a tool specially designed to detect homozygous exon deletions efficiently. We tested ExonDel on exome sequencing data generated from 16 breast cancer cell lines and identified both novel and known IEDs. Subsequently, we verified our findings using RNAseq and PCR technologies. Further comparisons with multiple sequencing-based CNV tools showed that ExonDel is capable of detecting unique IEDs not found by other CNV tools. CONCLUSIONS: ExonDel is an efficient way to screen for novel and known IEDs using exome sequencing data. ExonDel and its source code can be downloaded freely at https://github.com/slzhao/ExonDel.

The genomic map of breast cancer: which roads lead to better targeted therapies?

Recent advances in whole-genome technologies have supplied the field of cancer research with an overwhelming amount of molecular data. Improvements in massively parallel sequencing approaches have led to logarithmic decreases in costs, and so these methods are becoming almost commonplace in the analysis of clinical trials and other cohorts of interest. Furthermore, whole-transcriptome quantification by RNA sequencing is quickly replacing microarrays. However, older chip-based methodologies such as comparative genomic hybridization and single-nucleotide polymorphism arrays have benefited from this technological explosion and are now so accessible that they can be employed in increasingly larger cohorts of patients. The study of breast cancer lends itself particularly well to these technologies. It is the most commonly diagnosed neoplasm in women, giving rise to nearly 230,000 new cases each year. Many patients are given a diagnosis of early-stage disease, for which surgery is the standard of care. These attributes result in excellent availability of tissues for whole-genome/transcriptome analysis. The Cancer Genome Atlas project has generated comprehensive catalogs of publically available genomic breast cancer data. In addition, other studies employing the power of genomic technologies in medium to large cohorts were recently published. These data are now publically available for the generation of novel hypotheses. However, these studies differed in the methods, patient cohorts, and analytical techniques employed and represent complementary snapshots of the molecular underpinnings of breast cancer. Here, we will discuss the convergences and divergences of these reports as well as the scientific and clinical implications of their findings.

Expression profiling of 519 kinase genes in matched malignant peripheral nerve sheath tumor/plexiform neurofibroma samples is discriminatory and identifies mitotic regulators BUB1B, PBK and NEK2 as overexpressed with transformation.

About 50% of all malignant peripheral nerve sheath tumors (MPNSTs) arise as neurofibromatosis type 1 associated lesions. In those patients malignant peripheral nerve sheath tumors are thought to arise through malignant transformation of a preexisting plexiform neurofibroma. The molecular changes associated with this transformation are still poorly understood. We sought to test the hypothesis that dysregulation of expression of kinases contributes to this malignant transformation. We analyzed expression of all 519 kinase genes in the human genome using the nanostring nCounter system. Twelve cases of malignant peripheral nerve sheath tumor arising in a background of preexisting plexiform neurofibroma were included. Both components were separately sampled. Statistical analysis compared global changes in expression levels as well as changes observed in the pairwise comparison of samples taken from the same surgical specimen. Immunohistochemical studies were performed on tissue array slides to confirm expression of selected proteins. The expression pattern of kinase genes can separate malignant peripheral nerve sheath tumors and preexisting plexiform neurofibromas. The majority of kinase genes is downregulated rather than overexpressed with malignant transformation. The patterns of expression changes are complex without simple recurring alteration. Pathway analysis demonstrates that differentially expressed kinases are enriched for kinases involved in the direct regulation of mitosis, and several of these show increased expression in malignant peripheral nerve sheath tumors. Immunohistochemical studies for the mitotic regulators BUB1B, PBK and NEK2 confirm higher expression levels at the protein level. These results suggest that the malignant transformation of plexiform neurofibroma is associated with distinct changes in the expression of kinase genes. The patterns of these changes are complex and heterogeneous. There is no single unifying alteration. Kinases involved in mitotic regulation are particularly enriched in the pool of differentially expressed kinases. Some of these are overexpressed and are therefore possible targets for kinase inhibitors.

SMARCB1 protein and mRNA loss is not caused by promoter and histone hypermethylation in epithelioid sarcoma.

About 10% of epithelioid sarcomas have biallelic mutation of the SMARCB1 (SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily b, member 1) gene resulting in a lack of this nuclear protein. It has been suggested that SMARCB1 may be silenced by epigenetic changes in the remaining 90% of tumors. Thus, we hypothesized that the promoter of SMARCB1 is hypermethylated. We also examined SMARCB1 mRNA level to determine if a post-translational change was possible. Thirty-six cases of epithelioid sarcomas were studied. Immunohistochemistry and mutation analysis of the SMARCB1 gene were performed to select appropriate cases. Methylation status was assessed by methylation-specific PCR. Laser capture microdissection of tumor cells followed by real-time PCR was applied to examine the expression of SMARCB1 mRNA. Of 36 epithelioid sarcomas, 31 (86%) displayed a lack of SMARCB1 nuclear protein. In all, 4 (13%) of 31 SMARCB1-negative cases harbored biallelic deletion while 9 (33%) cases showed single-allelic deletion. One (4%) frameshift deletion of exon 3 and one point mutation of exon 7 were also found. In 16 (59%) cases, both alleles were intact. Altogether, 25/31 (81%) SMARCB1-negative cases had at least one intact allele. None of these cases demonstrated promoter hypermethylation. Low levels of SMARCB1 mRNA were found in all cases with tumor tissue extracted RNA (because of the minimal normal cell contamination) but no mRNA could be detected in laser dissected cases (containing only tumor cells). Enhancer of zeste homolog 2 (EZH2) overexpression was not characteristic of epithelioid sarcoma. Thus, loss of SMARCB1 expression in epithelioid sarcoma is caused neither by DNA hypermethylation nor by post-translational modifications. Most likely it is the microRNA destruction of SMARCB1 mRNA but further investigations are needed to elucidate this issue.