SynthEx: a synthetic-normal-based DNA sequencing tool for copy number alteration detection and tumor heterogeneity profiling

Mutation divergence over space in tumour expansion

Mutation accumulation in tumour evolution is one major cause of intra-tumour heterogeneity (ITH), which often leads to drug resistance during treatment. Previous studies with multi-region sequencing have shown that mutation divergence among samples within the patient is common, and the importance of spatial sampling to obtain a complete picture in tumour measurements. However, quantitative comparisons of the relationship between mutation heterogeneity and tumour expansion modes, sampling distances as well as the sampling methods are still few. Here, we investigate how mutations diverge over space by varying the sampling distance and tumour expansion modes using individual-based simulations. We measure ITH by the Jaccard index between samples and quantify how ITH increases with sampling distance, the pattern of which holds in various sampling methods and sizes. We also compare the inferred mutation rates based on the distributions of variant allele frequencies under different tumour expansion modes and sampling sizes. In exponentially fast expanding tumours, a mutation rate can always be inferred for any sampling size. However, the accuracy compared with the true value decreases when the sampling size decreases, where small sampling sizes result in a high estimate of the mutation rate. In addition, such an inference becomes unreliable when the tumour expansion is slow, such as in surface growth.

Dermokine mutations contribute to epithelial-mesenchymal transition and advanced melanoma through ERK/MAPK pathways

To discover vulnerabilities associated with dermokine (DMKN) as a new trigger of the epithelial-mesenchymal transition (EMT) -driven melanoma, we undertook a genome-wide genetic screening using transgenic. Here, we showed that DMKN expression could be constitutively increased in human malignant melanoma (MM) and that this correlates with poor overall survival in melanoma patients, especially in BRAF-mutated MM samples. Furthermore, in vitro, knockdown of DMKN inhibited the cell proliferation, migration, invasion, and apoptosis of MM cancer cells by the activation of ERK/MAPK signaling pathways and regulator of STAT3 in downstream molecular. By interrogating the in vitro melanoma dataset and characterization of advanced melanoma samples, we found that DMKN downregulated the EMT-like transcriptional program by disrupting EMT cortical actin, increasing the expression of epithelial markers, and decreasing the expression of mesenchymal markers. In addition, whole exome sequencing was presented with p.E69D and p.V91A DMKN mutations as a novel somatic loss of function mutations in those patients. Moreover, our purposeful proof-of-principle modeled the interaction of ERK with p.E69D and p.V91A DMKN mutations in the ERK-MAPK kinas signaling that may be naturally associated with triggering the EMT during melanomagenesis. Altogether, these findings provide preclinical evidence for the role of DMKN in shaping the EMT-like melanoma phenotype and introduced DMKN as a new exceptional responder for personalized MM therapy.

Detection of DNA copy number alterations by matrix-assisted laser desorption/ionization time-of-flight mass spectrometric analysis of single nucleotide polymorphisms

OBJECTIVES

Copy number alterations (CNAs) are frequently found in malignant tissues. Different approaches have been used for CNA detection. However, it is not easy to detect a large panel of CNA targets in heterogenous tumors.

METHODS

We have developed a CNAs detection approach through quantitatively analyzed allelic imbalance by allelotyping single nucleotide polymorphisms (SNPs) by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Furthermore, the copy number changes were quantified by real-competitive PCR (rcPCR) to distinguish loss of heterozygosity (LOH) and genomic amplification. The approach was used to validate the CNA regions detected by next generation sequencing (NGS) in early-stage lung carcinoma.

RESULTS

CNAs were detected in heterogeneous DNA samples where tumor DNA is present at only 10% through the SNP based allelotyping. In addition, two different types of CNAs (loss of heterozygosity and chromosome amplification) were able to be distinguished quantitatively by rcPCR. Validation on a total of 41 SNPs from the selected CNA regions showed that copy number changes did occur, and the tissues from early-stage lung carcinoma were distinguished from normal.

CONCLUSIONS

CNA detection by MALDI-TOF MS can be used for validating potentially interesting genomic regions identified from next generation sequencing, and for detecting CNAs in tumor tissues consisting of a mixture of neoplastic and normal cells.

Integrated DNA and RNA Sequencing Reveals Drivers of Endocrine Resistance in Estrogen Receptor-Positive Breast Cancer

PURPOSE

Endocrine therapy resistance (ETR) remains the greatest challenge in treating patients with hormone receptor-positive breast cancer. We set out to identify molecular mechanisms underlying ETR through in-depth genomic analysis of breast tumors.

EXPERIMENTAL DESIGN

We collected pre-treatment and sequential on-treatment tumor samples from 35 patients with estrogen receptor-positive breast cancer treated with neoadjuvant then adjuvant endocrine therapy; 3 had intrinsic resistance, 19 acquired resistance, and 13 remained sensitive. Response was determined by changes in tumor volume neoadjuvantly and by monitoring for adjuvant recurrence. Twelve patients received two or more lines of endocrine therapy, with subsequent treatment lines being initiated at the time of development of resistance to the previous endocrine therapy. DNA whole-exome sequencing and RNA sequencing were performed on all samples, totalling 169 unique specimens. DNA mutations, copy-number alterations, and gene expression data were analyzed through unsupervised and supervised analyses to identify molecular features related to ETR.

RESULTS

Mutations enriched in ETR included ESR1 and GATA3. The known ESR1 D538G variant conferring ETR was identified, as was a rarer E380Q variant that confers endocrine hypersensitivity. Resistant tumors which acquired resistance had distinct gene expression profiles compared with paired sensitive tumors, showing elevated pathways including ER, HER2, GATA3, AKT, RAS, and p63 signaling. Integrated analysis in individual patients highlighted the diversity of ETR mechanisms.

CONCLUSIONS

The mechanisms underlying ETR are multiple and characterized by diverse changes in both somatic genetic and transcriptomic profiles; to overcome resistance will require an individualized approach utilizing genomic and genetic biomarkers and drugs tailored to each patient.

Quantifying smoking exposure, genomic correlates, and related risk of treatment failure in p16+ squamous cell carcinoma of the oropharynx

OBJECTIVES

HPV-associated (p16+) squamous cell carcinoma of the oropharynx (OPSCC) has improved survival as compared to HPV-negative, smoking-associated disease. Intermediate outcomes have been noted in patients with p16+ tumors and smoking exposure. However, the extent of smoking exposure required for outcomes to decrease has not been delineated due to low failure rates and poor availability of quantitative tobacco smoke exposure data. Our primary objective is to characterize the dose-dependent relationship between recurrence-free survival (RFS) and tobacco smoke exposure in p16+ OPSCC and secondarily correlate tobacco smoke exposure with genomic alterations.

METHODS

Single institution chart review was performed of patients diagnosed with p16+ OPSCC from 2003 to 2015. Patients were excluded if staging, treatment details, recurrence status, or smoking exposure in pack-years were not available. Two hundred and forty-four patients were included.

RESULTS

Patients with 25 pack-years or greater smoking history exhibited a dose-dependent decrease in RFS compared to never smokers. This was robust to multivariate analysis for including staging and demographic factors. Forty-three patients with available targeted tumor sequencing data were identified. A strong trend was observed for increased C to A transversion mutations above 25 pack-years, which are known to be associated with exposure to tobacco smoke. Similarly, the proportion of COSMIC Signature 4 mutations were also found to be more common in patients with more than 25 pack-years of smoking exposure.

CONCLUSION

Evidence-based smoking exposure thresholds are needed to define inclusion criteria for trials of de-escalation therapy for p16+ OPSCC. Patients with smoking exposure greater than 20 pack-years have increased risk of recurrence and a distinct pattern of genomic alterations. Further studies are needed to delineate the potential consequences of mild smoking exposure. Smoking-related mutational signatures may hold potential for biomarker development in p16+ OPSCC.

LEVEL OF EVIDENCE

2B.

UNMASC: tumor-only variant calling with unmatched normal controls

Despite years of progress, mutation detection in cancer samples continues to require significant manual review as a final step. Expert review is particularly challenging in cases where tumors are sequenced without matched normal control DNA. Attempts have been made to call somatic point mutations without a matched normal sample by removing well-known germline variants, utilizing unmatched normal controls, and constructing decision rules to classify sequencing errors and private germline variants. With budgetary constraints related to computational and sequencing costs, finding the appropriate number of controls is a crucial step to identifying somatic variants. Our approach utilizes public databases for canonical somatic variants as well as germline variants and leverages information gathered about nearby positions in the normal controls. Drawing from our cohort of targeted capture panel sequencing of tumor and normal samples with varying tumortypes and demographics, these served as a benchmark for our tumor-only variant calling pipeline to observe the relationship between our ability to correctly classify variants against a number of unmatched normals. With our benchmarked samples, approximately ten normal controls were needed to maintain 94% sensitivity, 99% specificity and 76% positive predictive value, far outperforming comparable methods. Our approach, called UNMASC, also serves as a supplement to traditional tumor with matched normal variant calling workflows and can potentially extend to other concerns arising from analyzing next generation sequencing data.

Correlation of alterations in the KEAP1/CUL3/NFE2L2 pathway with radiation failure in larynx squamous cell carcinoma

OBJECTIVES

Patients with laryngeal squamous cell carcinoma (LSCC) often fail radiation therapy (RT), when received as monotherapy or in combination with other treatment modalities. Mechanisms for RT failure are poorly understood. We hypothesized that tumors failing RT would have increased rates of somatic mutations in genes associated with radiation resistance, particularly in genes associated with the NFE2L2 oxidative stress pathway. Using targeted exome sequencing on pretreated LSCC tumors, we retrospectively compared somatic mutation profile with clinical data and response to treatment.

METHODS

Tumors were classified as either radiation-resistant (RR) or radiation-sensitive (RS). RR was defined as persistent or recurrent disease within 2 years of receiving full-dose RT. Early stage (ES) LSCC was defined as Stage I or II tumors without lymph node involvement. Eight genes associated with radiation resistance were prioritized for analysis. RT-qPCR was performed on five NFE2L2 pathway genes.

RESULTS

Twenty LSCC tumors were included and classified as either RR (n = 8) or RS (n = 12). No differences in individual rates of somatic mutations by genes associated with radiation resistance were identified. Higher rates of total mutational burden (TMB) and increased alterations associated with the NFE2L2 pathway was observed in RR vs RS tumors (P < .05). In an analysis of only ES-LSCC patients (RR, n = 3 and RS, n = 3), RR tumors had increased NFE2L2 somatic pathway mutations (P = .014) and increased NQO1 mRNA expression (P = .05).

CONCLUSION

Increased TMB and NFE2L2 pathway alterations were associated with radiation resistance in LSCC. NQO1 mRNA expression may serve as a biomarker for RT response in ES-LSCC.Level of Evidence: II1.

Genomic heterogeneity and copy number variant burden are associated with poor recurrence-free survival and 11q loss in human papillomavirus-positive squamous cell carcinoma of the oropharynx

BACKGROUND

Human papillomavirus-positive (HPV+) squamous cell carcinoma of the oropharynx (OPSCC) is the most prevalent HPV-associated malignancy in the United States. Favorable treatment outcomes have led to increased interest in treatment de-escalation to reduce treatment morbidity as well as the development of prognostic markers to identify appropriately low-risk patients. Intratumoral genomic heterogeneity and copy number alteration burden have been demonstrated to be predictive of poor outcomes in many other cancers; therefore, we sought to determine whether intratumor heterogeneity and genomic instability are associated with poor outcomes in HPV+ OPSCC.

METHODS

Tumor heterogeneity estimates were made based on targeted exome sequencing of 45 patients with HPV+ OPSCC tumors. Analysis of an additional cohort of HPV+ OPSCC tumors lacking matched normal sequencing allowed copy number analysis of 99 patient tumors.

RESULTS

High intratumorally genomic heterogeneity and high numbers of copy number alterations were strongly associated with worse recurrence-free survival. Tumors with higher heterogeneity and frequent copy number alterations were associated with loss of distal 11q, which encodes key genes related to double-strand break repair, including ATM and MRE11A.

CONCLUSIONS

Both intratumor genomic heterogeneity and high-burden copy number alterations are strongly associated with poor recurrence-free survival in patients with HPV+ OPSCC. The drivers of genomic instability and heterogeneity in these tumors remains to be elucidated. However, 11q loss and defective DNA double-strand break repair have been associated with genomic instability in other solid tumors. Copy number alteration burden and intratumoral heterogeneity represent promising avenues for risk stratification of patients with HPV+OPSCC.

Identification of the distinct genomic features in gastroesophageal junction adenocarcinoma and its Siewert subtypes

Rates of gastroesophageal junction adenocarcinomas (GEJAs) have shown an alarming increase; however, the genetic background of GEJA and its Siewert classification have yet to be uncovered. Here, 60 paired tumor and normal DNA samples from GEJA patients were analyzed by whole-exome sequencing. Among them, 13 were Siewert type I, 14 were type II, and 33 were type III. A predominance of C/G>T/A substitutions was discovered in GEJA, followed by C/G>A/T substitutions. Notably, Siewert type I and type II/III display distinct sets of driver genes, mutational spectrum, and recurrently disrupted pathways. Siewert type I showed similarity to esophageal adenocarcinomas (EACs) and the chromosomal instability subtype of stomach adenocarcinomas, while Siewert type II/III showed similarity to the genomic stable subtype of stomach adenocarcinoma. We also found that mutation of FBXW7, a driver gene of GEJA, was enriched in Siewert type I. Our data identify differences between GEJA and stomach/EACs at the genomic level and provide evidence for differential treatment based on Siewert classification of GEJA. © 2020 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Genome‑wide copy number analysis of circulating tumor cells in breast cancer patients with liver metastasis

The genome‑wide copy number analysis of circulating tumor cells (CTCs) provides a promising prognostic biomarker for survival in breast cancer liver metastasis (BCLM) patients. The present study aimed to confirm the prognostic value of the presence of CTCs in BCLM patients. We previously developed an assay for the genome‑wide pattern differences in copy number variations (CNVs) as an adjunct test for the routine imaging and histopathologic diagnosis methods to distinguish newly diagnosed liver metastases and recurrent liver metastases. Forty‑three breast cancer patients were selected for this study in which 23 newly diagnosed and 20 recurrent liver metastases were diagnosed by histopathology and 18F‑FDG PET/CT imaging. CTCs were counted from all patients using the CellSearch system and were confirmed by cytomorphology and three‑color immunocytochemistry. Genomic DNA of single CTCs was amplified using multiple annealing and looping based amplification cycles (MALBAC). Then, we compared the CTC numbers of newly diagnosed and recurrent BCLM patients using Illumina platforms. A high CTC frequency (>15 CTCs/7.5 ml blood) was found to be correlated with disease severity and metastatic progression, which suggests the value for CTCs in the diagnosis of BCLM in comparison with pathohistology and PET/CT imaging (P>0.05). Moreover, CTCs isolated from BCLM patients remained an independent prognostic detection factor associated with overall survival (P=0.0041). Comparison between newly diagnosed and recurrent liver metastases revealed different frequencies of CNVs (P>0.05). Notably, the CNV pattern of isolated CTCs of recurrent BCLM patients was similar to recurrent liver metastases (nearly 82% of the gain/loss regions). Functional enrichment analysis identified 25 genes as a CNV signature of BCLM. Among them, were defensin and β‑defensin genes, which are significantly associated with anti‑angiogenesis and immunomodulation signaling pathways. High CTC frequencies are effective in the evaluation and differentiation between newly diagnosed liver metastases from recurrent liver metastases. Future clinical studies will be necessary to fully determine the prognostic potential of CTC cluster signatures in patients with BCLM.

Analysis of Pre- and Posttreatment Tissues from the SWOG S0800 Trial Reveals an Effect of Neoadjuvant Chemotherapy on the Breast Cancer Genome

PURPOSE

We performed whole-exome sequencing (WES) of pre- and posttreatment cancer tissues to assess the somatic mutation landscape of tumors before and after neoadjuvant taxane and anthracycline chemotherapy with or without bevacizumab.

EXPERIMENTAL DESIGN

Twenty-nine pretreatment biopsies from the SWOG S0800 trial were subjected to WES to identify mutational patterns associated with response to neoadjuvant chemotherapy. Nine matching samples with residual cancer after therapy were also analyzed to assess changes in mutational patterns in response to therapy.

RESULTS

In pretreatment samples, a higher proportion of mutation signature 3, a BRCA-mediated DNA repair deficiency mutational signature, was associated with higher rate of pathologic complete response (pCR; median signature weight 24%, range 0%-38% in pCR vs. median weight 0%, range 0%-19% in residual disease, Wilcoxon rank sum, Bonferroni P = 0.007). We found no biological pathway level mutations associated with pCR or enriched in posttreatment samples. We observed statistically significant enrichment of high functional impact mutations in the "E2F targets" and "G2-M checkpoint" pathways in residual cancer samples implicating these pathways in resistance to therapy and a significant depletion of mutations in the "myogenesis pathway" suggesting the cells harboring these variants were effectively eradicated by therapy.

CONCLUSIONS

These results suggest that genomic disturbances in BRCA-related DNA repair mechanisms, reflected by a dominant mutational signature 3, confer increased chemotherapy sensitivity. Cancers that survive neoadjuvant chemotherapy frequently have alterations in cell-cycle-regulating genes but different genes of the same pathways are affected in different patients.

A systematic evaluation of copy number alterations detection methods on real SNP array and deep sequencing data

BACKGROUND

The Copy Number Alterations (CNAs) are discovered to be tightly associated with cancers, so accurately detecting them is one of the most important tasks in the cancer genomics. A series of CNAs detection methods have been proposed and new ones are still being developed. Due to the complexity of CNAs in cancers, no CNAs detection method has been accepted as the gold standard caller. Several evaluation works have made attempts to reveal typical CNAs detection methods' performance. Limited by the scale of evaluation data, these different comparison works don't reach a consensus and the researchers are still confused on how to choose one proper CNAs caller for their analysis. Therefore, it needs a more comprehensive evaluation of typical CNAs detection methods' performance.

RESULTS

In this work, we use a large-scale real dataset from CAGEKID consortium to evaluate total 12 typical CNAs detection methods. These methods are most widely used in cancer researches and always used as benchmark for the newly proposed CNAs detection methods. This large-scale dataset comprises of SNP array data on 94 samples and the whole genome sequencing data on 10 samples. Evaluations are comprehensively implemented in current scenarios of CNAs detection, which include that detect CNAs on SNP array data, on sequencing data with tumor and normal matched samples and on sequencing data with single tumor sample. Three SNP based methods are firstly ranked. Subsequently, the best SNP based method's results are used as benchmark to compare six matched samples based methods and three single tumor sample based methods in terms of the preprocessing, recall rate, Jaccard index and segmentation characteristics.

CONCLUSIONS

Our survey thoroughly reveals 12 typical methods' superiority and inferiority. We explain why methods show specific characteristics from a methodological standpoint. Finally, we present the guiding principle for choosing one proper CNAs detection method under specific conditions. Some unsolved problems and expectations are also addressed for upcoming CNAs detection methods.

Genomic evolution of cancer models: perils and opportunities

Cancer research relies on model systems, which reflect the biology of actual human tumours to only a certain extent. One important feature of human cancer is its intra-tumour genomic heterogeneity and instability. However, the extent of such genomic instability in cancer models has received limited attention in research. Here, we review the state of knowledge of genomic instability of cancer models and discuss its biological origins and implications for basic research and for cancer precision medicine. We discuss strategies to cope with such genomic evolution and evaluate both the perils and the emerging opportunities associated with it.

Identification of Jun loss promotes resistance to histone deacetylase inhibitor entinostat through Myc signaling in luminal breast cancer

BACKGROUND

Based on promising phase II data, the histone deacetylase inhibitor entinostat is in phase III trials for patients with metastatic estrogen receptor-positive breast cancer. Predictors of sensitivity and resistance, however, remain unknown.

METHODS

A total of eight cell lines and nine mouse models of breast cancer were treated with entinostat. Luminal cell lines were treated with or without entinostat at their IC₅₀ doses, and MMTV/Neu luminal mouse tumors were untreated or treated with entinostat until progression. We investigated these models using their gene expression profiling by microarray and copy number by arrayCGH. We also utilized the network-based DawnRank algorithm that integrates DNA and RNA data to identify driver genes of resistance. The impact of candidate drivers was investigated in The Cancer Genome Atlas and METABRIC breast cancer datasets.

RESULTS

Luminal models displayed enhanced sensitivity to entinostat as compared to basal-like or claudin-low models. Both in vitro and in vivo luminal models showed significant downregulation of Myc gene signatures following entinostat treatment. Myc gene signatures became upregulated on tumor progression in vivo and overexpression of Myc conferred resistance to entinostat in vitro. Further examination of resistance mechanisms in MMTV/Neu tumors identified a portion of mouse chromosome 4 that had DNA copy number loss and low gene expression. Within this region, Jun was computationally identified to be a driver gene of resistance. Jun knockdown in cell lines resulted in upregulation of Myc signatures and made these lines more resistant to entinostat. Jun-deleted samples, found in 17-23% of luminal patients, had significantly higher Myc signature scores that predicted worse survival.

CONCLUSIONS

Entinostat inhibited luminal breast cancer through Myc signaling, which was upregulated by Jun DNA loss to promote resistance to entinostat in our models. Jun DNA copy number loss, and/or high MYC signatures, might represent biomarkers for entinostat responsiveness in luminal breast cancer.

Integrated Analysis of RNA and DNA from the Phase III Trial CALGB 40601 Identifies Predictors of Response to Trastuzumab-Based Neoadjuvant Chemotherapy in HER2-Positive Breast Cancer

Purpose: Response to a complex trastuzumab-based regimen is affected by multiple features of the tumor and its microenvironment. Developing a predictive algorithm is key to optimizing HER2-targeting therapy.Experimental Design: We analyzed 137 pretreatment tumors with mRNA-seq and DNA exome sequencing from CALGB 40601, a neoadjuvant phase III trial of paclitaxel plus trastuzumab with or without lapatinib in stage II to III HER2-positive breast cancer. We adopted an Elastic Net regularized regression approach that controls for covarying features within high-dimensional data. First, we applied 517 known gene expression signatures to develop an Elastic Net model to predict pCR, which we validated on 143 samples from four independent trials. Next, we performed integrative analyses incorporating clinicopathologic information with somatic mutation status, DNA copy number alterations (CNA), and gene signatures.Results: The Elastic Net model using only gene signatures predicted pCR in the validation sets (AUC = 0.76). Integrative analyses showed that models containing gene signatures, clinical features, and DNA information were better pCR predictors than models containing a single data type. Frequently selected variables from the multiplatform models included amplifications of chromosome 6p, TP53 mutation, HER2-enriched subtype, and immune signatures. Variables predicting resistance included Luminal/ER⁺ features.Conclusions: Models using RNA only, as well as integrated RNA and DNA models, can predict pCR with improved accuracy over clinical variables. Somatic DNA alterations (mutation, CNAs), tumor molecular subtype (HER2E, Luminal), and the microenvironment (immune cells) were independent predictors of response to trastuzumab and paclitaxel-based regimens. This highlights the complexity of predicting response in HER2-positive breast cancer. Clin Cancer Res; 24(21); 5292-304. ©2018 AACR.

Disease burden and conditioning regimens in ASCT1221, a randomized phase II trial in children with juvenile myelomonocytic leukemia: A Children's Oncology Group study

BACKGROUND

Most patients with juvenile myelomonocytic leukemia (JMML) are curable only with allogeneic hematopoietic cell transplantation (HCT). However, the current standard conditioning regimen, busulfan-cyclophosphamide-melphalan (Bu-Cy-Mel), may be associated with higher risks of morbidity and mortality. ASCT1221 was designed to test whether the potentially less-toxic myeloablative conditioning regimen containing busulfan-fludarabine (Bu-Flu) would be associated with equivalent outcomes.

PROCEDURE

Twenty-seven patients were enrolled on ASCT1221 from 2013 to 2015. Pre- and post-HCT (starting Day +30) mutant allele burden was measured in all and pre-HCT therapy was administered according to physician discretion.

RESULTS

Fifteen patients were randomized (six to Bu-Cy-Mel and nine to Bu-Flu) after meeting diagnostic criteria for JMML. Pre-HCT low-dose chemotherapy did not appear to reduce pre-HCT disease burden. Two patients, however, received aggressive chemotherapy pre-HCT and achieved low disease-burden state; both are long-term survivors. All four patients with detectable mutant allele burden at Day +30 post-HCT eventually progressed compared to two of nine patients with unmeasurable allele burden (P = 0.04). The 18-month event-free survival of the entire cohort was 47% (95% CI, 21-69%), and was 83% (95% CI, 27-97%) and 22% (95% CI, 03-51%) for Bu-Cy-Mel and Bu-Flu, respectively (P = 0.04). ASCT1221 was terminated early due to concerns that the Bu-Flu arm had inferior outcomes.

CONCLUSIONS

The regimen of Bu-Flu is inadequate to provide disease control in patients with JMML who present to HCT with large burdens of disease. Advances in molecular testing may allow better characterization of biologic risk, pre-HCT responses to chemotherapy, and post-HCT management.

LCCC 1025: a phase II study of everolimus, trastuzumab, and vinorelbine to treat progressive HER2-positive breast cancer brain metastases

PURPOSE

HER2 + breast cancer (BC) is an aggressive subtype with high rates of brain metastases (BCBM). Two-thirds of HER2 + BCBM demonstrate activation of the PI3K/mTOR pathway driving resistance to anti-HER2 therapy. This phase II study evaluated everolimus (E), a brain-permeable mTOR inhibitor, trastuzumab (T), and vinorelbine (V) in patients with HER2 + BCBM.

PATIENTS AND METHODS

Eligible patients had progressive HER2 + BCBM. The primary endpoint was intracranial response rate (RR); secondary objectives were CNS clinical benefit rate (CBR), extracranial RR, time to progression (TTP), overall survival (OS), and targeted sequencing of tumors from enrolled patients. A two-stage design distinguished intracranial RR of 5% versus 20%.

RESULTS

32 patients were evaluable for toxicity, 26 for efficacy. Intracranial RR was 4% (1 PR). CNS CBR at 6 mos was 27%; at 3 mos 65%. Median intracranial TTP was 3.9 mos (95% CI 2.2-5). OS was 12.2 mos (95% CI 0.6-20.2). Grade 3-4 toxicities included neutropenia (41%), anemia (16%), and stomatitis (16%). Mutations in TP53 and PIK3CA were common in BCBM. Mutations in the PI3K/mTOR pathway were not associated with response. ERBB2 amplification was higher in BCBM compared to primary BC; ERBB2 amplification in the primary BC trended toward worse OS.

CONCLUSION

While intracranial RR to ETV was low in HER2 + BCBM patients, one-third achieved CNS CBR; TTP/OS was similar to historical control. No new toxicity signals were observed. Further analysis of the genomic underpinnings of BCBM to identify tractable prognostic and/or predictive biomarkers is warranted.

CLINICAL TRIAL

(NCT01305941).

Integrated RNA and DNA sequencing reveals early drivers of metastatic breast cancer

Breast cancer metastasis remains a clinical challenge, even within a single patient across multiple sites of the disease. Genome-wide comparisons of both the DNA and gene expression of primary tumors and metastases in multiple patients could help elucidate the underlying mechanisms that cause breast cancer metastasis. To address this issue, we performed DNA exome and RNA sequencing of matched primary tumors and multiple metastases from 16 patients, totaling 83 distinct specimens. We identified tumor-specific drivers by integrating known protein-protein network information with RNA expression and somatic DNA alterations and found that genetic drivers were predominantly established in the primary tumor and maintained through metastatic spreading. In addition, our analyses revealed that most genetic drivers were DNA copy number changes, the TP53 mutation was a recurrent founding mutation regardless of subtype, and that multiclonal seeding of metastases was frequent and occurred in multiple subtypes. Genetic drivers unique to metastasis were identified as somatic mutations in the estrogen and androgen receptor genes. These results highlight the complexity of metastatic spreading, be it monoclonal or multiclonal, and suggest that most metastatic drivers are established in the primary tumor, despite the substantial heterogeneity seen in the metastases.

Single-Cell Genomic Analysis in Plants

Individual cells in an organism are variable, which strongly impacts cellular processes. Advances in sequencing technologies have enabled single-cell genomic analysis to become widespread, addressing shortcomings of analyses conducted on populations of bulk cells. While the field of single-cell plant genomics is in its infancy, there is great potential to gain insights into cell lineage and functional cell types to help understand complex cellular interactions in plants. In this review, we discuss current approaches for single-cell plant genomic analysis, with a focus on single-cell isolation, DNA amplification, next-generation sequencing, and bioinformatics analysis. We outline the technical challenges of analysing material from a single plant cell, and then examine applications of single-cell genomics and the integration of this approach with genome editing. Finally, we indicate future directions we expect in the rapidly developing field of plant single-cell genomic analysis.

Using single-cell multiple omics approaches to resolve tumor heterogeneity

It has become increasingly clear that both normal and cancer tissues are composed of heterogeneous populations. Genetic variation can be attributed to the downstream effects of inherited mutations, environmental factors, or inaccurately resolved errors in transcription and replication. When lesions occur in regions that confer a proliferative advantage, it can support clonal expansion, subclonal variation, and neoplastic progression. In this manner, the complex heterogeneous microenvironment of a tumour promotes the likelihood of angiogenesis and metastasis. Recent advances in next-generation sequencing and computational biology have utilized single-cell applications to build deep profiles of individual cells that are otherwise masked in bulk profiling. In addition, the development of new techniques for combining single-cell multi-omic strategies is providing a more precise understanding of factors contributing to cellular identity, function, and growth. Continuing advancements in single-cell technology and computational deconvolution of data will be critical for reconstructing patient specific intra-tumour features and developing more personalized cancer treatments.