Adnan Derti

Convergent loss of PTEN leads to clinical resistance to a PI(3)Kα inhibitor

Broad and deep tumour genome sequencing has shed new light on tumour heterogeneity and provided important insights into the evolution of metastases arising from different clones. There is an additional layer of complexity, in that tumour evolution may be influenced by selective pressure provided by therapy, in a similar fashion to that occurring in infectious diseases. Here we studied tumour genomic evolution in a patient (index patient) with metastatic breast cancer bearing an activating PIK3CA (phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha, PI(3)Kα) mutation. The patient was treated with the PI(3)Kα inhibitor BYL719, which achieved a lasting clinical response, but the patient eventually became resistant to this drug (emergence of lung metastases) and died shortly thereafter. A rapid autopsy was performed and material from a total of 14 metastatic sites was collected and sequenced. All metastatic lesions, when compared to the pre-treatment tumour, had a copy loss of PTEN (phosphatase and tensin homolog) and those lesions that became refractory to BYL719 had additional and different PTEN genetic alterations, resulting in the loss of PTEN expression. To put these results in context, we examined six other patients also treated with BYL719. Acquired bi-allelic loss of PTEN was found in one of these patients, whereas in two others PIK3CA mutations present in the primary tumour were no longer detected at the time of progression. To characterize our findings functionally, we examined the effects of PTEN knockdown in several preclinical models (both in cell lines intrinsically sensitive to BYL719 and in PTEN-null xenografts derived from our index patient), which we found resulted in resistance to BYL719, whereas simultaneous PI(3)K p110β blockade reverted this resistance phenotype. We conclude that parallel genetic evolution of separate metastatic sites with different PTEN genomic alterations leads to a convergent PTEN-null phenotype resistant to PI(3)Kα inhibition.

Mammalian ultraconserved elements are strongly depleted among segmental duplications and copy number variants

An earlier search in the human, mouse and rat genomes for sequences that are 100% conserved in orthologous segments and ≥200 bp in length identified 481 distinct sequences. These human-mouse-rat sequences, which represent ultraconserved elements (UCEs), are believed to be important for functions involving DNA binding, RNA processing and the regulation of transcription and development. In vivo and additional computational studies of UCEs and other highly conserved sequences are consistent with these functional associations, with some observations indicating enhancer-like activity for these elements. Here, we show that UCEs are significantly depleted among segmental duplications and copy number variants. Notably, of the UCEs that are found in segmental duplications or copy number variants, the majority overlap exons, indicating, along with other findings presented, that UCEs overlapping exons represent a distinct subset.

Computational comparison of two draft sequences of the human genome

We are in the enviable position of having two distinct drafts of the human genome sequence. Although gaps, errors, redundancy and incomplete annotation mean that individually each falls short of the ideal, many of these problems can be assessed by comparison. Here we present some comparative analyses of these drafts. We look at a number of features of the sequences, including sequence gaps, continuity, consistency between the two sequences and patterns of DNA-binding protein motifs.

Genome analysis reveals interplay between 5'UTR introns and nuclear mRNA export for secretory and mitochondrial genes.

In higher eukaryotes, messenger RNAs (mRNAs) are exported from the nucleus to the cytoplasm via factors deposited near the 5′ end of the transcript during splicing. The signal sequence coding region (SSCR) can support an alternative mRNA export (ALREX) pathway that does not require splicing. However, most SSCR–containing genes also have introns, so the interplay between these export mechanisms remains unclear. Here we support a model in which the furthest upstream element in a given transcript, be it an intron or an ALREX–promoting SSCR, dictates the mRNA export pathway used. We also experimentally demonstrate that nuclear-encoded mitochondrial genes can use the ALREX pathway. Thus, ALREX can also be supported by nucleotide signals within mitochondrial-targeting sequence coding regions (MSCRs). Finally, we identified and experimentally verified novel motifs associated with the ALREX pathway that are shared by both SSCRs and MSCRs. Our results show strong correlation between 5′ untranslated region (5′UTR) intron presence/absence and sequence features at the beginning of the coding region. They also suggest that genes encoding secretory and mitochondrial proteins share a common regulatory mechanism at the level of mRNA export.

Absence of Evidence for MHC–Dependent Mate Selection within HapMap Populations

The major histocompatibility complex (MHC) of immunity genes has been reported to influence mate choice in vertebrates, and a recent study presented genetic evidence for this effect in humans. Specifically, greater dissimilarity at the MHC locus was reported for European-American mates (parents in HapMap Phase 2 trios) than for non-mates. Here we show that the results depend on a few extreme data points, are not robust to conservative changes in the analysis procedure, and cannot be reproduced in an equivalent but independent set of European-American mates. Although some evidence suggests an avoidance of extreme MHC similarity between mates, rather than a preference for dissimilarity, limited sample sizes preclude a rigorous investigation. In summary, fine-scale molecular-genetic data do not conclusively support the hypothesis that mate selection in humans is influenced by the MHC locus.

Abstract LB-65: Towards defining the genetic framework for clinical response to treatment with BYL719, a PI3Kalpha-specific inhibitor.

Proceedings: AACR 104th Annual Meeting 2013; Apr 6-10, 2013; Washington, DC Defining predictive biomarkers and deriving appropriate patient populations for treatment are key areas of interest in the clinical development of phosphatidyl-inositol-3-kinase (PI3K) inhibitors, but currently most clinical trials do not pre-select patients using defined genetic markers. Pre-clinical studies indicated previously that in vitro sensitivity to BYL719, a potent and selective small molecule inhibitor of the α-isoform of PI3K, was increased in cell lines derived from a subset of indications, such as HER2-positive or luminal breast cancer. Moreover, BYL719 sensitivity in vitro was positively correlated with PIK3CA mutation or amplification and HER2 amplification. PTEN or BRAF mutation, on the other hand, was associated with BYL719 insensitivity. Consequently, presence of an activating PIK3CA alteration in the tumor was a pre-requisite for patients to enroll into the BYL719 first-in-human (FIM) clinical trial. In this study, we applied massive parallel sequencing to tumor specimens from patients enrolled in the BYL719 FIM trial to comprehensively assess the genetic determinants of clinical sensitivity to BYL719. Paraffin-embedded formalin-fixed archival or pre-treatment tumor specimens were obtained from 44 patients with advanced solid tumors upon enrolment into the clinical trial. DNA was isolated and then assayed by massive parallel sequencing covering either a panel of 182 cancer-related genes at Foundation Medicine or the whole exome at the Broad Institute. Mutations were identified by focusing on genes with alterations in the COSMIC data base and excluding germline variants and were subsequently correlated with clinical benefit as defined by stable disease ≥ 4 months, tumor shrinkage ≥ 20% or objective tumor response to BYL719 using a two-tailed Fishers exact test. Focusing on a panel of 51 genes with known relevance to PI3K signaling, we observed that all pre-treatment tumor samples harbored at least one genetic abnormality and that each of the genes was altered in one or several tumor samples. TP53 (59%), APC (25%), KRAS (23%) and PTEN (18%) were the most frequently altered in addition to PIK3CA. Alterations in TP53 and KRAS were identified as statistically significant negative predictors of BYL719 sensitivity (p < 0.05), while mutations in the APC and PTEN genes were associated with a trend towards lack of benefit from treatment with BYL719. Our results suggest that definition of the genetic biomarkers that govern sensitivity to treatment with BYL719 and–most likely–other PI3Kα inhibitors in the clinic is possible upon analysis of patients tumors by massive parallel sequencing. We also demonstrate that it is feasible to routinely obtain this information in the clinical trial setting. This implies that exploration of the genetic determinants driving sensitivity or primary resistance to targeted agents in general can now be undertaken clinically. Citation Format: Jordi Rodon, Dejan Juric, Ana-Maria Gonzalez-Angulo, Johanna Bendell, Jordan Berlin, Douglas Bootle, Kathlene Gravelin, Alan Huang, Adnan Derti, Joseph Lehar, Jens Wurthner, Markus Boehm, Eliezer van Allen, Nikhil Wagle, Levi A. Garraway, Roman Yelensky, Philip J. Stephens, Vincent A. Miller, Robert Schlegel, Cornelia Quadt, Jose Baselga. Towards defining the genetic framework for clinical response to treatment with BYL719, a PI3Kalpha-specific inhibitor. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr LB-65. doi:10.1158/1538-7445.AM2013-LB-65

Response to “MHC-dependent mate choice in humans: Why genomic patterns from the HapMap European American data set support the hypothesis”

This is a commentary on article Laurent R, Chaix R. MHC-dependent mate choice in humans: why genomic patterns from the HapMap European American dataset support the hypothesis. Bioessays. 2007;34(4):267-71.

Abstract 629: An integrated genomic and proteomic analysis of human tumors reveals key factors in neoantigen identification and enables epitope prediction for cancer immunotherapy

Background: Immunotherapy has become essential in the treatment of advanced cancer, with the advent of drug approvals in multiple indications and functional cures for a minority of patients. However, overall survival gains from immunotherapy have been limited and substantial progress remains. The discovery of tumor-specific neoantigens as principal targets of T cells unleashed by immune checkpoint blockade was a key breakthrough in immunotherapy research. Although example neoantigens have been reported, the impact of genomic features on HLA presentation and neoantigen identification has not been comprehensively assessed. Moreover, in silico methods for predicting which mutations lead to neoantigens are currently inadequate for most therapeutic applications, with a false positive rate of >95%. Methods: We performed deep tumor/normal exome sequencing (Illumina-based, average unique depth 557x/149x), tumor transcriptome sequencing (avg. 111M unique reads), and mass spec HLA class I peptide sequencing (Thermo Lumos, avg. 3,482 peptides) on fresh-frozen primary tumor specimens from 23 patients (22 NSCLC, 1 OC). Somatic mutations were called with a custom GATK-based pipeline, gene expression assessed with RSEM, and peptides matched to mass spectra using COMET/Percolator. We examined the effect of NGS parameters on neoantigen identification, analyzed HLA presentation as a function of genomic features, and created a novel deep learning model for epitope prediction. Results: We identified 6,252 nonsynonymous somatic mutations across the cohort (avg. 272 per patient) and found 3,874 (62%) transcribed in mRNA. Down-sampling tumor DNA NGS data to a more typical average unique coverage of ~200x and RNA to ~60M reads revealed 3,275 transcribed mutations, an overall 15% loss of candidate neoantigens and >25% loss in low tumor content samples, demonstrating the importance of sequencing depth. Gene expression measurement at the RNA level predicted HLA presentation more strongly than expected, with peptides from genes detected in RNA found presented >20X more often than peptides from non-detected genes. With this and public datasets we trained a model to predict HLA presentation and compared it to standard binding affinity prediction (e.g., NetMHC or MHCflurry) at the strong-binder 50nM threshold for well-characterized alleles. Whereas binding affinity-based prediction gave a positive predictive value (PPV) of only 3%, our integrated deep learning approach showed a PPV of >25% at equivalent recall, a near ten-fold gain. Conclusions: A novel genomic and proteomic analysis of human tumors establishes NGS requirements for neoantigen identification, characterizes key correlates of HLA presentation, and enables prediction for personalized cancer immunotherapy research. Citation Format: Brendan Bulik-Sullivan, Jennifer Busby, Matthew Davis, Andrew Clark, Tyler Murphy, Michele Busby, Fujiko Duke, Jessica Smith, Jason Hudak, Adnan Derti, Josh Francis, Roman Yelensky. An integrated genomic and proteomic analysis of human tumors reveals key factors in neoantigen identification and enables epitope prediction for cancer immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 629. doi:10.1158/1538-7445.AM2017-629

Response to “MHC-dependent mate choice in humans: Why genomic patterns from the HapMap European American data set support the hypothesis” (DOI: 10.1002/bies.201100150): HapMap genotypes do not confidently support a role for the MHC locus in human mate selection

This is a commentary on article Laurent R, Chaix R. MHC-dependent mate choice in humans: why genomic patterns from the HapMap European American dataset support the hypothesis. Bioessays. 2007;34(4):267-71.