A Phase Ib Trial of Personalized Neoantigen Therapy Plus Anti-PD-1 in Patients with Advanced Melanoma, Non-small Cell Lung Cancer, or Bladder Cancer.

Neoantigens arise from mutations in cancer cells and are important targets of T cell-mediated anti-tumor immunity. Here, we report the first open-label, phase Ib clinical trial of a personalized neoantigen-based vaccine, NEO-PV-01, in combination with PD-1 blockade in patients with advanced melanoma, non-small cell lung cancer, or bladder cancer. This analysis of 82 patients demonstrated that the regimen was safe, with no treatment-related serious adverse events observed. De novo neoantigen-specific CD4+ and CD8+ T cell responses were observed post-vaccination in all of the patients. The vaccine-induced T cells had a cytotoxic phenotype and were capable of trafficking to the tumor and mediating cell killing. In addition, epitope spread to neoantigens not included in the vaccine was detected post-vaccination. These data support the safety and immunogenicity of this regimen in patients with advanced solid tumors (Clinicaltrials.gov: NCT02897765).

Defining HLA-II Ligand Processing and Binding Rules with Mass Spectrometry Enhances Cancer Epitope Prediction.

Increasing evidence indicates CD4+ T cells can recognize cancer-specific antigens and control tumor growth. However, it remains difficult to predict the antigens that will be presented by human leukocyte antigen class II molecules (HLA-II), hindering efforts to optimally target them therapeutically. Obstacles include inaccurate peptide-binding prediction and unsolved complexities of the HLA-II pathway. To address these challenges, we developed an improved technology for discovering HLA-II binding motifs and conducted a comprehensive analysis of tumor ligandomes to learn processing rules relevant in the tumor microenvironment. We profiled >40 HLA-II alleles and showed that binding motifs were highly sensitive to HLA-DM, a peptide-loading chaperone. We also revealed that intratumoral HLA-II presentation was dominated by professional antigen-presenting cells (APCs) rather than cancer cells. Integrating these observations, we developed algorithms that accurately predicted APC ligandomes, including peptides from phagocytosed cancer cells. These tools and biological insights will enable improved HLA-II-directed cancer therapies.

Subtype and pathway specific responses to anticancer compounds in breast cancer.

Breast cancers are comprised of molecularly distinct subtypes that may respond differently to pathway-targeted therapies now under development. Collections of breast cancer cell lines mirror many of the molecular subtypes and pathways found in tumors, suggesting that treatment of cell lines with candidate therapeutic compounds can guide identification of associations between molecular subtypes, pathways, and drug response. In a test of 77 therapeutic compounds, nearly all drugs showed differential responses across these cell lines, and approximately one third showed subtype-, pathway-, and/or genomic aberration-specific responses. These observations suggest mechanisms of response and resistance and may inform efforts to develop molecular assays that predict clinical response.

Development and deployment of a histopathology-based deep learning algorithm for patient prescreening in a clinical trial.

Accurate identification of genetic alterations in tumors, such as Fibroblast Growth Factor Receptor, is crucial for treating with targeted therapies; however, molecular testing can delay patient care due to the time and tissue required. Successful development, validation, and deployment of an AI-based, biomarker-detection algorithm could reduce screening cost and accelerate patient recruitment. Here, we develop a deep-learning algorithm using >3000 H&E-stained whole slide images from patients with advanced urothelial cancers, optimized for high sensitivity to avoid ruling out trial-eligible patients. The algorithm is validated on a dataset of 350 patients, achieving an area under the curve of 0.75, specificity of 31.8% at 88.7% sensitivity, and projected 28.7% reduction in molecular testing. We successfully deploy the system in a non-interventional study comprising 89 global study clinical sites and demonstrate its potential to prioritize/deprioritize molecular testing resources and provide substantial cost savings in the drug development and clinical settings.

Antitumor activity of an allosteric inhibitor of centromere-associated protein-E.

Centromere-associated protein-E (CENP-E) is a kinetochore-associated mitotic kinesin that is thought to function as the key receptor responsible for mitotic checkpoint signal transduction after interaction with spindle microtubules. We have identified GSK923295, an allosteric inhibitor of CENP-E kinesin motor ATPase activity, and mapped the inhibitor binding site to a region similar to that bound by loop-5 inhibitors of the kinesin KSP/Eg5. Unlike these KSP inhibitors, which block release of ADP and destabilize motor-microtubule interaction, GSK923295 inhibited release of inorganic phosphate and stabilized CENP-E motor domain interaction with microtubules. Inhibition of CENP-E motor activity in cultured cells and tumor xenografts caused failure of metaphase chromosome alignment and induced mitotic arrest, indicating that tight binding of CENP-E to microtubules is insufficient to satisfy the mitotic checkpoint. Consistent with genetic studies in mice suggesting that decreased CENP-E function can have a tumor-suppressive effect, inhibition of CENP-E induced tumor cell apoptosis and tumor regression.

Systematic analysis of genotype-specific drug responses in cancer.

A systematic understanding of genotype-specific sensitivity or resistance to anticancer agents is required to provide improved patient therapy. The availability of an expansive panel of annotated cancer cell lines enables comparative surveys of associations between genotypes and compounds of various target classes. Thus, one can better predict the optimal treatment for a specific tumor. Here, we present a statistical framework, cell line enrichment analysis (CLEA), to associate the response of anticancer agents with major cancer genotypes. Multilevel omics data, including transcriptome, proteome and phosphatome data, were integrated with drug data based on the genotypic classification of cancer cell lines. The results reproduced known patterns of compound sensitivity associated with particular genotypes. In addition, this approach reveals multiple unexpected associations between compounds and mutational genotypes. The mutational genotypes led to unique protein activation and gene expression signatures, which provided a mechanistic understanding of their functional effects. Furthermore, CLEA maps revealed interconnections between TP53 mutations and other mutations in the context of drug responses. The TP53 mutational status appears to play a dominant role in determining clustering patterns of gene and protein expression profiles for major cancer genotypes. This study provides a framework for the integrative analysis of mutations, drug responses and omics data in cancers.

Mutation and copy number detection in human cancers using a custom genotyping assay.

Identification of biomarkers for positive and negative predictors of response to cancer therapeutics can help direct clinical strategies. However, challenges with tissue availability and costs are significant limiting factors for diagnostic assays. To address these challenges, we have customized a high-throughput single nucleotide polymorphism genotyping assay with the objective of simultaneously surveying known somatic mutations and copy number alterations for translational studies in cancer. As constructed, this assay can interrogate 376 known somatic mutations and quantify copy number alterations of genes commonly implicated in tumorigenesis or progression. Validation of this assay on a panel of 321 cell lines demonstrates sensitivity to accurately detect mutations, robust accuracy in the presence of infiltrating normal tissue, and the ability to detect both DNA copy number amplifications and deletions. This technology, with its high sensitivity, small DNA requirements, and low costs is an attractive platform for biomarker exploration in cancer.

Combined phosphatase and tensin homolog (PTEN) loss and fatty acid synthase (FAS) overexpression worsens the prognosis of Chinese patients with hepatocellular carcinoma.

We aimed to investigate the expression pattern of phosphatase and tensin homolog (PTEN), to evaluate the relationship between PTEN expression and clinicopathological characteristics, including fatty acid synthase (FAS) expression, and to determine the correlations of PTEN and FAS expression with survival in Chinese patients with hepatocellular carcinoma (HCC). The expression patterns of PTEN and FAS were determined using tissue microarrays and immunohistochemistry. The expression of PTEN was compared with the clinicopathological characteristics of HCC, including FAS expression. Receiver operator characteristic curves were used to calculate the clinical sensitivity and specificity of PTEN expression. Kaplan-Meier survival curves were constructed to evaluate the correlations of PTEN loss and FAS overexpression with overall survival. We found that the loss of PTEN expression occurred predominantly in the cytoplasm, while FAS was mainly localized to the cytoplasm. Cytoplasmic and total PTEN expression levels were significantly decreased in HCC compared with adjacent non-neoplastic tissue (both, p < 0.0001). Decreased cytoplasmic and total PTEN expression showed significant clinical sensitivity and specificity for HCC (both, p < 0.0001). Downregulation of PTEN in HCC relative to non-neoplastic tissue was significantly correlated with histological grade (p = 0.043 for histological grades I-II versus grade III). Loss of total PTEN was significantly correlated with FAS overexpression (p = 0.014). Loss of PTEN was also associated with poor prognosis of patients with poorly differentiated HCC (p = 0.049). Moreover, loss of PTEN combined with FAS overexpression was associated with significantly worse prognosis compared with other HCC cases (p = 0.011). Our data indicate that PTEN may serve as a potential diagnostic and prognostic marker of HCC. Upregulating PTEN expression and inhibiting FAS expression may offer a novel therapeutic approach for HCC.

Frequent genetic abnormalities of the PI3K/AKT pathway in primary ovarian cancer predict patient outcome.

Identification and characterization of underlying genetic aberrations could facilitate diagnosis and treatment of ovarian cancer. Copy number analysis using array Comparative Genomic Hybridization (aCGH) on 93 primary ovarian tumors identified PI3K/AKT pathway as the most frequently altered cancer related pathway. Furthermore, survival analyses to correlate gene copy number and mutation data with patient outcome showed that copy number gains of PIK3CA, PIK3CB, and PIK3R4 in these tumors were associated with decreased survival. To confirm these findings at the protein level, immunohistochemistry (IHC) for PIK3CA product p110α and p-Akt was performed on tissue microarrays from 522 independent serous ovarian cancers. Overexpression of either of these two proteins was found to be associated with decreased survival. Multivariant analysis from these samples further showed that overexpression of p-AKT and/or p110α is an independent prognostic factor for these tumors. siRNAs targeting altered PI3K/AKT pathway genes inhibited proliferation and induced apoptosis in ovarian cancer cell lines. In addition, the effect of the siRNAs in different cell lines seemed to correlate with the particular genetic alterations that the cell line carries. These results strongly support the utilization of PI3K pathway inhibitors in ovarian cancer. They also suggest identifying the specific component in the PI3K pathway that is genetically altered has the potential to help select the most effective therapy. Both mutation as well as copy number changes can be used as predictive markers for this purpose.

High chromosome number in hematological cancer cell lines is a negative predictor of response to the inhibition of Aurora B and C by GSK1070916.

BACKGROUND: Aurora kinases play critical roles in mitosis and are being evaluated as therapeutic targets in cancer. GSK1070916 is a potent, selective, ATP competitive inhibitor of Aurora kinase B and C. Translation of predictive biomarkers to the clinic can benefit patients by identifying the tumors that are more likely to respond to therapies, especially novel inhibitors such as GSK1070916. METHODS: 59 Hematological cancer-derived cell lines were used as models for response where in vitro sensitivity to GSK1070916 was based on both time and degree of cell death. The response data was analyzed along with karyotype, transcriptomics and somatic mutation profiles to determine predictors of response. RESULTS: 20 cell lines were sensitive and 39 were resistant to treatment with GSK1070916. High chromosome number was more prevalent in resistant cell lines (p-value = 0.0098, Fisher Exact Test). Greater resistance was also found in cell lines harboring polyploid subpopulations (p-value = 0.00014, Unpaired t-test). A review of NOTCH1 mutations in T-ALL cell lines showed an association between NOTCH1 mutation status and chromosome number (p-value = 0.0066, Fisher Exact Test). CONCLUSIONS: High chromosome number associated with resistance to the inhibition of Aurora B and C suggests cells with a mechanism to bypass the high ploidy checkpoint are resistant to GSK1070916. High chromosome number, a hallmark trait of many late stage hematological malignancies, varies in prevalence among hematological malignancy subtypes. The high frequency and relative ease of measurement make high chromosome number a viable negative predictive marker for GSK1070916.

Genomic and epigenetic alterations deregulate microRNA expression in human epithelial ovarian cancer.

MicroRNAs (miRNAs) are an abundant class of small noncoding RNAs that function as negative gene regulators. miRNA deregulation is involved in the initiation and progression of human cancer; however, the underlying mechanism and its contributions to genome-wide transcriptional changes in cancer are still largely unknown. We studied miRNA deregulation in human epithelial ovarian cancer by integrative genomic approach, including miRNA microarray (n = 106), array-based comparative genomic hybridization (n = 109), cDNA microarray (n = 76), and tissue array (n = 504). miRNA expression is markedly down-regulated in malignant transformation and tumor progression. Genomic copy number loss and epigenetic silencing, respectively, may account for the down-regulation of approximately 15% and at least approximately 36% of miRNAs in advanced ovarian tumors and miRNA down-regulation contributes to a genome-wide transcriptional deregulation. Last, eight miRNAs located in the chromosome 14 miRNA cluster (Dlk1-Gtl2 domain) were identified as potential tumor suppressor genes. Therefore, our results suggest that miRNAs may offer new biomarkers and therapeutic targets in epithelial ovarian cancer.

Distinct MHC gene expression patterns during progression of melanoma.

Abnormal expression of major histocompatibility complex (MHC) molecules in melanoma has been reported previously. However, the MHC molecule expression patterns in different growth phases of melanoma and the underlying mechanisms are not well understood. Here, we demonstrate that in vertical growth phase (VGP) melanomas, MHC genes are subject to increased rates of DNA copy number gains, accompanied by increased expression, in comparison to normal melanocytes. In contrast, MHC expression in metastatic melanomas drastically decreased compared to VGP melanomas, despite still prevalent DNA copy number gains. Subsequent investigations found that the master transactivator of MHC genes, CIITA, was also significantly downregulated in metastatic melanomas when compared to VGP melanomas. This could be one of the mechanisms accounting for the discrepancy between DNA copy number and expression level in metastatic melanomas, a potentially separate mechanism of gene regulation. These results infer a dynamic role of MHC function in melanoma progression. We propose potential mechanisms for the overexpression of MHC molecules in earlier stages of melanoma as well as for its downregulation in metastatic melanomas.

Harnessing Real-World Evidence for the Development of Novel Cancer Therapies.

Resourcing real-world evidence (RWE) is becoming an increasingly important asset in developing novel therapies for cancer. In this article, an overview of the benefits and challenges of using these data is provided. Through several case examples we highlight future applications and potential.

Cancer cell lines as genetic models of their parent histology: analyses based on array comparative genomic hybridization.

Tumor-derived cell lines are used as in vitro cancer models, but their ability to accurately reflect the phenotype and genotype of the parental histology remains questionable, given the prevalence of documented cell line-specific cytogenetic changes. We have addressed the issue of whether copy number alterations seen in tumor-derived cell lines reflect those observed in studies of fresh tissue by carrying out a meta-analysis of array-based comparative genomic hybridization data that considers both copy number alteration frequencies and the occurrence of cancer gene amplifications and homozygous deletions. Pairwise correlation comparisons between the data sets of seven diagnosis-specific matched tumor and cell line groups indicate that the trends in aberration frequencies are highly correlated between tumors and cell line sets of matched cancer histology relative to unmatched pairings. Despite their similarities, cell lines showed uniformly higher locus-specific alteration frequencies (P = 0.004) and several recurring cell line-specific alterations emerged. These include the previously documented losses of 13q and 9p and gains of 20q, as well as additional undescribed cell line-specific gains of 5p, 7p, and 17q and losses of 18q and 4q. These results indicate that, on average, cell lines preserve in vitro the genetic aberrations that are unique to the parent histology from which they were derived while acquiring additional locus-specific alterations. These data may enable a more predictive understanding of individual cell lines as in vitro models of cancer biology and therapy.

Genome-wide DNA copy number predictors of lapatinib sensitivity in tumor-derived cell lines.

A common aim of pharmacogenomic studies that use genome-wide assays on panels of cancers is the unbiased discovery of genomic alterations that are associated with clinical outcome and drug response. Previous studies of lapatinib, a selective dual-kinase inhibitor of epidermal growth factor receptor (EGFR) and HER2 tyrosine kinases, have shown predictable relationships between the activity of these target genes and response. Under the hypothesis that additional genes may play a role in drug sensitivity, a predictive model for lapatinib response was constructed from genome-wide DNA copy number data from 24 cancer cell lines. An optimal predictive model which consists of aberrations at nine distinct genetic loci, includes gains of HER2, EGFR, and loss of CDKN2A. This model achieved an area under the receiver operating characteristic curve of approximately 0.85 (80% confidence interval, 0.70-0.98; P < 0.01), and correctly classified the sensitivity status of 8 of 10 head and neck cancer cell lines. This study shows that biomarkers predictive for lapatinib sensitivity, including the previously described copy number gains of EGFR and HER2, can be discovered using novel genomic assays in an unbiased manner. Furthermore, these results show the utility of DNA copy number profiles in pharmacogenomic studies.

Method of primary tumor detection as a risk factor for local and distant recurrence after breast-conservation treatment for early-stage breast cancer.

BACKGROUND: Recent studies have shown that breast cancer detected by screening has a more favorable prognosis than interval breast cancer. To further understand the biologic significance of this finding, we investigated the association of disease recurrence, local and distant, with the method of detection of the primary breast cancer in a cohort of 1686 women treated with breast conservation. PATIENTS AND METHODS: The charts of 1686 women with primarily stage I or II invasive breast cancer treated by breast conservation between 1977 and 2002 were reviewed. The median length of follow-up was 6 years. Univariate and multivariate analyses using binary logistic regression were performed for 2 subgroups: (1) those with local recurrence versus those without; and (2) those with distant metastasis versus those without distant metastasis. RESULTS: Our data confirmed several of the well-known risk factors for local and distant recurrence. In addition, we found that individuals with breast cancer detected on physical examination alone have a significantly higher risk for local recurrence compared with patients with cancer detected on mammogram alone, independent of tumor size (odds ratio [OR], 2.369; 95% CI, 1.235-4.547; P = .01). We also found a similar correlation for risk of distant metastasis in these 2 groups of women (OR, 2.201; 95% CI, 1.211-3.998; P = .01). CONCLUSION: Breast cancers that are palpable might represent an aggressive biologic subtype with an increased risk of local and distant recurrence. Risk stratification might need to include this clinical feature in addition to conventional prognostic factors.

Ultraconserved elements: genomics, function and disease.

Evolutionary conservation has become a powerful tool to identify functionally important genomic sequences/elements in the human genome. There are 481 genomic segments longer than 200 base pairs (bp) that are absolutely conserved (100% identity with no insertions or deletions) between human, mouse and rat genomes. Such segments are known as ultraconserved elements (UCEs). Although our knowledge of UCEs is limited, most recent studies suggest that UCEs play a functional role in vertebrate genomes, such as serving as long-range enhancers of flanking genes, regulating splicing and epigenetic modifications, and functioning as transcriptional coactivator. Most recent studies show that expression of UCEs is consistently altered in tumors, strongly suggesting these elements may also be involved in human disease such as cancer development.

Integrative genomic analysis of phosphatidylinositol 3'-kinase family identifies PIK3R3 as a potential therapeutic target in epithelial ovarian cancer.

PURPOSE: The phosphatidylinositol 3'-kinase (PI3K) family plays a key regulatory role in various cancer-associated signal transduction pathways. Here, we investigated the genomic alterations and gene expression of most known PI3K family members in human epithelial ovarian cancer. EXPERIMENTAL DESIGN: The DNA copy number of PI3K family genes was screened by a high-resolution array comparative genomic hybridization in 89 human ovarian cancer specimens. The mRNA expression level of PI3K genes was analyzed by microarray retrieval approach, and further validated by real-time reverse transcription-PCR. The expression of p55gamma protein in ovarian cancer was analyzed on tissue arrays. Small interfering RNA was used to study the function of PIK3R3 in ovarian cancer. RESULTS: In ovarian cancer, 6 of 12 PI3K genes exhibited significant DNA copy number gains (>20%), including PIK3CA (23.6%), PIK3CB (27.0%), PIK3CG (25.8%), PIK3R2 (29.2%), PIK3R3 (21.3%), and PIK3C2B (40.4%). Among those, only PIK3R3 had significantly up-regulated mRNA expression level in ovarian cancer compared with normal ovary. Up-regulated PIK3R3 mRNA expression was also observed in liver, prostate, and breast cancers. The PIK3R3 mRNA expression level was significantly higher in ovarian cancer cell lines (n = 18) than in human ovarian surface epithelial cells (n = 6, P = 0.002). Overexpression of p55gamma protein in ovarian cancer was confirmed by tissue array analysis. In addition, we found that knockdown of PIK3R3 expression by small interfering RNA significantly increased the apoptosis in cultured ovarian cancer cell lines. CONCLUSION: We propose that PIK3R3 may serve as a potential therapeutic target in human ovarian cancer.

DNA copy number data analysis using the CGHAnalyzer software suite.

Recently developed microarray-based copy number measurement assays have drastically improved the accuracy and resolution to which DNA copy number alterations can be detected. As with any microarray assay, those designed to measure genome copy number produce large data sets for each sample. Furthermore, many successful studies of genome copy number require the concurrent comparison of many samples. Identifying software packages that provide the proper analytic tools is essential to effectively mine these valuable data. CGHAnalyzer is a freely available, open source software suite designed specifically for the purpose of analyzing multiple-experiment microarray-based genome copy number data. This package can load data from a variety of formats, query large data sets for minimal common regions of gain and loss, integrate other genomic features into analyses (e.g., known/predicted genes), conduct higher order analyses such as hierarchical/k-means clustering and perform statistical tests to identify regions that are differentially altered between classes of samples. Each of these utilities represents common hurdles in approaching microarray copy number data sets. This passage provides an overview of practical, step by step analysis of array-based comparative genomic hybridization data using CGHAnalyzer and demonstrates specific techniques to improve the efficiency and accuracy of analysis.