Protocol optimization of a targeted sequencing panel for genomic profiling of bronchoalveolar lavage fluid in lung cancer.

INTRODUCTION: We investigated a commercially available sequencing panel to study the effect of sequencing depth, variant calling strategy, and targeted sequencing region on identifying tumor-derived variants in cell-free bronchoalveolar lavage (cfBAL) DNA compared with plasma cfDNA. METHODS: Sequencing was performed at low or high coverage using two filtering algorithms to identify tumor variants on two panels targeting 77 and 197 genes respectively. RESULTS: One hundred and four sequencing files from 40 matched DNA samples of cfBAL, plasma, germline leukocytes, and archival tumor specimens in 10 patients with early-stage lung cancer were analyzed. By low-coverage sequencing, tumor-derived cfBAL variants were detected in 5/10 patients (50%) compared with 2/10 (20%) for plasma. High-coverage sequencing did not affect the number of tumor-derived variants detected in either biospecimen type. Accounting for germline mutations eliminated false-positive plasma calls regardless of coverage (0/10 patients with tumor-derived variants identified) and increased the number of cfBAL calls (5/10 patients with tumor-derived variants identified). These results were not affected by the number of targeted genes.

Verification of prognostic expression biomarkers is improved by examining enriched leukemic blasts rather than mononuclear cells from acute myeloid leukemia patients.

BACKGROUND: Studies have not systematically compared the ability to verify performance of prognostic transcripts in paired bulk mononuclear cells versus viable CD34-expressing leukemic blasts from patients with acute myeloid leukemia. We hypothesized that examining the homogenous leukemic blasts will yield different biological information and may improve prognostic performance of expression biomarkers. METHODS: To assess the impact of cellular heterogeneity on expression biomarkers in acute myeloid leukemia, we systematically examined paired mononuclear cells and viable CD34-expressing leukemic blasts from SWOG diagnostic specimens. After enrichment, patients were assigned into discovery and validation cohorts based on availability of extracted RNA. Analyses of RNA sequencing data examined how enrichment impacted differentially expressed genes associated with pre-analytic variables, patient characteristics, and clinical outcomes. RESULTS: Blast enrichment yielded significantly different expression profiles and biological pathways associated with clinical characteristics (e.g., cytogenetics). Although numerous differentially expressed genes were associated with clinical outcomes, most lost their prognostic significance in the mononuclear cells and blasts after adjusting for age and ELN risk, with only 11 genes remaining significant for overall survival in both cell populations (CEP70, COMMD7, DNMT3B, ECE1, LNX2, NEGR1, PIK3C2B, SEMA4D, SMAD2, TAF8, ZNF444). To examine the impact of enrichment on biomarker verification, these 11 candidate biomarkers were examined by quantitative RT/PCR in the validation cohort. After adjusting for ELN risk and age, expression of 4 genes (CEP70, DNMT3B, ECE1, and PIK3CB) remained significantly associated with overall survival in the blasts, while none met statistical significance in mononuclear cells. CONCLUSIONS: This study provides insights into biological information gained/lost by examining viable CD34-expressing leukemic blasts versus mononuclear cells from the same patient and shows an improved verification rate for expression biomarkers in blasts.

Somatic mutation but not aneuploidy differentiates lung cancer in never-smokers and smokers.

Lung cancer in never-smokers disproportionately affects older women. To understand the mutational landscape of this cohort, we performed detailed genome characterization of 73 lung adenocarcinomas from participants of the Women’s Health Initiative (WHI). We find enrichment of EGFR mutations in never-/light-smokers and KRAS mutations in heavy smokers as expected, but we also show that the specific variants of these genes differ by smoking status, with important therapeutic implications. Mutational signature analysis revealed signatures of clock, APOBEC, and DNA repair deficiency in never-/light-smokers; however, the mutational load of these signatures did not differ significantly from those found in smokers. Last, tumors from both smokers and never-/light-smokers shared copy number subtypes, with no significant differences in aneuploidy. Thus, the genomic landscape of lung cancer in never-/light-smokers and smokers is predominantly differentiated by somatic mutations and not copy number alterations.

Tumor-Infiltrating Merkel Cell Polyomavirus-Specific T Cells Are Diverse and Associated with Improved Patient Survival.

Tumor-infiltrating CD8+ T cells are associated with improved survival of patients with Merkel cell carcinoma (MCC), an aggressive skin cancer causally linked to Merkel cell polyomavirus (MCPyV). However, CD8+ T-cell infiltration is robust in only 4% to 18% of MCC tumors. We characterized the T-cell receptor (TCR) repertoire restricted to one prominent epitope of MCPyV (KLLEIAPNC, "KLL") and assessed whether TCR diversity, tumor infiltration, or T-cell avidity correlated with clinical outcome. HLA-A*02:01/KLL tetramer+ CD8+ T cells from MCC patient peripheral blood mononuclear cells (PBMC) and tumor-infiltrating lymphocytes (TIL) were isolated via flow cytometry. TCRß (TRB) sequencing was performed on tetramer+ cells from PBMCs or TILs (n = 14) and matched tumors (n = 12). Functional avidity of T-cell clones was determined by IFNγ production. We identified KLL tetramer+ T cells in 14% of PBMC and 21% of TIL from MCC patients. TRB repertoires were strikingly diverse (397 unique TRBs were identified from 12 patients) and mostly private (only one TCRb clonotype shared between two patients). An increased fraction of KLL-specific TIL (>1.9%) was associated with significantly increased MCC-specific survival P = 0.0009). T-cell cloning from four patients identified 42 distinct KLL-specific TCRa/b pairs. T-cell clones from patients with improved MCC-specific outcomes were more avid (P < 0.05) and recognized an HLA-appropriate MCC cell line. T cells specific for a single MCPyV epitope display marked TCR diversity within and between patients. Intratumoral infiltration by MCPyV-specific T cells was associated with significantly improved MCC-specific survival, suggesting that augmenting the number or avidity of virus-specific T cells may have therapeutic benefit. Cancer Immunol Res; 5(2); 137-47. ©2017 AACR.

Expression and functional characterization of CD33 transcript variants in human acute myeloid leukemia.

With the demonstration of improved survival of some acute myeloid leukemia (AML) patients with the CD33 antibody-drug conjugate, gemtuzumab ozogamicin (GO), CD33 has been validated as a target for antigen-specific immunotherapy. Since previous studies identified a CD33 splice variant missing exon 2 (CD33∆E2) and, consequently, the immune-dominant membrane-distal V-set domain, we investigated the expression and functional characteristics of CD33 transcript variants in AML. In primary AML specimens, we not only found full-length CD33 (CD33FL) and CD33∆E2 but also corresponding variants containing an alternate exon 7 predicted to encode a CD33 protein lacking most of the intracellular domain (CD33E7a and, not previously described, CD33∆E2,E7a) in almost all cases. In acute leukemia cell sublines engineered to express individual CD33 splice variants, all splice variants had endocytic properties. CD33FL and CD33E7a mediated similar degrees of GO cytotoxicity, whereas CD33∆E2 and CD33∆E2,E7a could not serve as target for GO. Co-expression of CD33∆E2 did not interfere with CD33FL endocytosis and did not impact CD33FL-mediated GO cytotoxicity. Together, our findings document a greater-than-previously thought complexity of CD33 expression in human AML. They identify CD33 variants that lack exon 2 and are not recognized by current CD33-directed therapeutics as potential target for future unconjugated or conjugated antibodies.

Phenotypic and transcriptional fidelity of patient-derived colon cancer xenografts in immune-deficient mice.

Xenografts of human colorectal cancer (CRC) in immune-deficient mice have great potential for accelerating the study of tumor biology and therapy. We evaluated xenografts established in NOD/scid/IL2Rγ-null mice from the primary or metastatic tumors of 27 patients with CRC to estimate their capacity for expanding tumor cells for in vitro studies and to assess how faithfully they recapitulated the transcriptional profile of their parental tumors. RNA-seq analysis of parental human CRC tumors and their derivative xenografts demonstrated that reproducible transcriptional changes characterize the human tumor to murine xenograft transition. In most but not all cases, the human stroma, vasculature, and hematopoietic elements were systematically replaced by murine analogues while the carcinoma component persisted. Once established as xenografts, human CRC cells that could be propagated by serial transplantation remained transcriptionally stable. Three histologically atypical xenografts, established from patients with peritoneal metastases, contained abundant human stromal elements and blood vessels in addition to human tumor cells. The transcriptomes of these mixed tumor/stromal xenografts did not closely resemble those of their parental tumors, and attempts to propagate such xenografts by serial transplantation were unsuccessful. Stable expression of numerous genes previously identified as high priority targets for immunotherapy was observed in most xenograft lineages. Aberrant expression in CRC cells of human genes that are normally only expressed in hematopoietic cells was also observed. Our results suggest that human CRC cells expanded in murine xenografts have great utility for studies of tumor immunobiology and targeted therapies such as immunotherapy but also identify potential limitations.

Significance of expression of ITGA5 and its splice variants in acute myeloid leukemia: a report from the Children's Oncology Group.

Acute myeloid leukemia (AML) encompasses a heterogeneous group of diseases, and novel biomarkers for risk refinement and stratification are needed to optimize patient care. To identify novel risk factors, we performed transcriptome sequencing on 68 diagnostic AML samples and identified 2 transcript variants (-E2 and -E2/3) of the α-subunit (ITGA5) of the very late antigen-5 integrin. We then quantified expression of ITGA5 and these splice variants in specimens from participants of the AAML03P1 trial. We found no association between ITGA5 expression and clinical outcome. In contrast, patients with the highest relative expression (Q4) of the -E2/3 ITGA5 splice variant less likely had low-risk disease than Q1-3 patients (21% vs. 38%, P = 0.027). Q4 patients had worse response to chemotherapy with a higher proportion having persistent minimal residual disease (50% vs. 23%, P = 0.003) and inferior overall survival (at 5 years: 48% vs. 67%, P = 0.015); the latter association was limited to low-risk patients (Q4 vs. Q1-3: 56% vs. 85%, P = 0.043) and was not seen in standard-risk (51% vs. 60%, P = 0.340) or high-risk (33% vs. 38%, P = 0.952) patients. Our exploratory studies indicate that transcriptome sequencing is useful for biomarker discovery, as exemplified by the identification of ITGA5 -E2/3 splice variant as potential novel adverse prognostic marker for low-risk AML that, if confirmed, could serve to further risk-stratify this patient subset.

Integrative proteomic analysis of serum and peritoneal fluids helps identify proteins that are up-regulated in serum of women with ovarian cancer.

BACKGROUND: We used intensive modern proteomics approaches to identify predictive proteins in ovary cancer. We identify up-regulated proteins in both serum and peritoneal fluid. To evaluate the overall performance of the approach we track the behavior of 20 validated markers across these experiments. METHODOLOGY: Mass spectrometry based quantitative proteomics following extensive protein fractionation was used to compare serum of women with serous ovarian cancer to healthy women and women with benign ovarian tumors. Quantitation was achieved by isotopically labeling cysteine amino acids. Label-free mass spectrometry was used to compare peritoneal fluid taken from women with serous ovarian cancer and those with benign tumors. All data were integrated and annotated based on whether the proteins have been previously validated using antibody-based assays. FINDINGS: We selected 54 quantified serum proteins and 358 peritoneal fluid proteins whose case-control differences exceeded a predefined threshold. Seventeen proteins were quantified in both materials and 14 are extracellular. Of 19 validated markers that were identified all were found in cancer peritoneal fluid and a subset of 7 were quantified in serum, with one of these proteins, IGFBP1, newly validated here. CONCLUSION: Proteome profiling applied to symptomatic ovarian cancer cases identifies a large number of up-regulated serum proteins, many of which are or have been confirmed by immunoassays. The number of currently known validated markers is highest in peritoneal fluid, but they make up a higher percentage of the proteins observed in both serum and peritoneal fluid, suggesting that the 10 additional markers in this group may be high quality candidates.

A statistical method for chromatographic alignment of LC-MS data.

Integrated liquid-chromatography mass-spectrometry (LC-MS) is becoming a widely used approach for quantifying the protein composition of complex samples. The output of the LC-MS system measures the intensity of a peptide with a specific mass-charge ratio and retention time. In the last few years, this technology has been used to compare complex biological samples across multiple conditions. One challenge for comparative proteomic profiling with LC-MS is to match corresponding peptide features from different experiments. In this paper, we propose a new method--Peptide Element Alignment (PETAL) that uses raw spectrum data and detected peak to simultaneously align features from multiple LC-MS experiments. PETAL creates spectrum elements, each of which represents the mass spectrum of a single peptide in a single scan. Peptides detected in different LC-MS data are aligned if they can be represented by the same elements. By considering each peptide separately, PETAL enjoys greater flexibility than time warping methods. While most existing methods process multiple data sets by sequentially aligning each data set to an arbitrarily chosen template data set, PETAL treats all experiments symmetrically and can analyze all experiments simultaneously. We illustrate the performance of PETAL on example data sets.