N-MYC impairs innate immune signaling in high-grade serous ovarian carcinoma.

High-grade serous ovarian cancer (HGSC) is a challenging disease, especially for patients with immunologically "cold" tumors devoid of tumor-infiltrating lymphocytes (TILs). We found that HGSC exhibits among the highest levels of MYCN expression and transcriptional signature across human cancers, which is strongly linked to diminished features of antitumor immunity. N-MYC repressed basal and induced IFN type I signaling in HGSC cell lines, leading to decreased chemokine expression and T cell chemoattraction. N-MYC inhibited the induction of IFN type I by suppressing tumor cell-intrinsic STING signaling via reduced STING oligomerization, and by blunting RIG-I-like receptor signaling through inhibition of MAVS aggregation and localization in the mitochondria. Single-cell RNA sequencing of human clinical HGSC samples revealed a strong negative association between cancer cell-intrinsic MYCN transcriptional program and type I IFN signaling. Thus, N-MYC inhibits tumor cell-intrinsic innate immune signaling in HGSC, making it a compelling target for immunotherapy of cold tumors.

Heritable defects in telomere and mitotic function selectively predispose to sarcomas.

Cancer genetics has to date focused on epithelial malignancies, identifying multiple histotype-specific pathways underlying cancer susceptibility. Sarcomas are rare malignancies predominantly derived from embryonic mesoderm. To identify pathways specific to mesenchymal cancers, we performed whole-genome germline sequencing on 1644 sporadic cases and 3205 matched healthy elderly controls. Using an extreme phenotype design, a combined rare-variant burden and ontologic analysis identified two sarcoma-specific pathways involved in mitotic and telomere functions. Variants in centrosome genes are linked to malignant peripheral nerve sheath and gastrointestinal stromal tumors, whereas heritable defects in the shelterin complex link susceptibility to sarcoma, melanoma, and thyroid cancers. These studies indicate a specific role for heritable defects in mitotic and telomere biology in risk of sarcomas.

Targeted gene panels identify a high frequency of pathogenic germline variants in patients diagnosed with a hematological malignancy and at least one other independent cancer.

The majority of studies assessing the contribution of pathogenic germline variants (PGVs) to cancer predisposition have focused on patients with single cancers. We analyzed 45 known cancer predisposition genes (CPGs) in germline samples of 202 patients with hematological malignancies (HMs) plus one or more other independent cancer managed at major tertiary medical centers on two different continents. This included 120 patients with therapy-related myeloid neoplasms (t-MNs), where the HM occurred after cytotoxic treatment for a first malignancy, and 82 patients with multiple cancers in which the HM was not preceded by cytotoxic therapy (MC-HM). Using American College of Medical Genetics/Association for Molecular Pathology variant classification guidelines, 13% of patients had PGVs, most frequently identified in CHEK2 (17% of PGVs), BRCA1 (13%), DDX41 (13%), and TP53 (7%). The frequency of PGVs in MC-HM was higher than in t-MN, although not statistically significant (18 vs. 9%; p = 0.085). The frequency of PGVs in lymphoid and myeloid HM patients was similar (19 vs. 17.5%; p > 0.9). Critically, patients with PGVs in BRCA1, BRCA2 or TP53 did not satisfy current clinical phenotypic criteria for germline testing. Our data suggest that a personal history of multiple cancers, one being a HM, should trigger screening for PGVs.

Cancer stemness, intratumoral heterogeneity, and immune response across cancers.

Regulatory programs that control the function of stem cells are active in cancer and confer properties that promote progression and therapy resistance. However, the impact of a stem cell-like tumor phenotype ("stemness") on the immunological properties of cancer has not been systematically explored. Using gene-expression-based metrics, we evaluated the association of stemness with immune cell infiltration and genomic, transcriptomic, and clinical parameters across 21 solid cancers. We found pervasive negative associations between cancer stemness and anticancer immunity. This occurred despite high stemness cancers exhibiting increased mutation load, cancer-testis antigen expression, and intratumoral heterogeneity. Stemness was also strongly associated with cell-intrinsic suppression of endogenous retroviruses and type I IFN signaling, and increased expression of multiple therapeutically accessible immunosuppressive pathways. Thus, stemness is not only a fundamental process in cancer progression but may provide a mechanistic link between antigenicity, intratumoral heterogeneity, and immune suppression across cancers.

Multiple ABCB1 transcriptional fusions in drug resistant high-grade serous ovarian and breast cancer.

ABCB1 encodes Multidrug Resistance protein (MDR1), an ATP-binding cassette member involved in the cellular efflux of chemotherapeutic drugs. Here we report that ovarian and breast samples from chemotherapy treated patients are positive for multiple transcriptional fusions involving ABCB1, placing it under the control of a strong promoter while leaving its open reading frame intact. We identified 15 different transcriptional fusion partners involving ABCB1, as well as patients with multiple distinct fusion events. The partner gene selected depended on its structure, promoter strength, and chromosomal proximity to ABCB1. Fusion positivity was strongly associated with the number of lines of MDR1-substrate chemotherapy given. MDR1 inhibition in a fusion positive ovarian cancer cell line increased sensitivity to paclitaxel more than 50-fold. Convergent evolution of ABCB1 fusion is therefore frequent in chemotherapy resistant recurrent ovarian cancer. As most currently approved PARP inhibitors (PARPi) are MDR1 substrates, prior chemotherapy may precondition resistance to PARPi.

Reversion of BRCA1/2 Germline Mutations Detected in Circulating Tumor DNA From Patients With High-Grade Serous Ovarian Cancer.

Purpose Germline BRCA1 or BRCA2 mutations in patients with high-grade serous ovarian cancer (HGSC) are associated with favorable responses to chemotherapy. However, secondary intragenic (reversion) mutations that restore protein function lead to clinically significant rates of acquired resistance. The goal of this study was to determine whether reversion mutations could be found in an unbiased manner in circulating cell-free DNA (cfDNA) to predict treatment response in HGSC. Patients and Methods Plasma and tumor samples were obtained from 30 patients with HGSC with either BRCA1 or BRCA2 germline mutation. Two cohorts were ascertained: patients with a malignancy before undergoing primary HGSC debulking surgery (n = 14) or patients at disease recurrence (n = 16). Paired tumor and plasma samples were available for most patients (24 of 30). Targeted amplicon, next-generation sequencing was performed using primers that flanked germline mutations, whose design did not rely on prior knowledge of reversion sequences. Results Five patients were identified with intragenic mutations predicted to restore BRCA1/2 open reading frames, including two patients with multiple independent reversion alleles. Reversion mutations were only detected in tumor samples from patients with recurrent disease (five of 16) and only in cfDNA from patients with a tumor-detected reversion (three of five). Findings from a rapid autopsy of a patient with multiple independent reversions indicated that reversion-allele frequency in metastatic sites is an important determinant of assay sensitivity. Abundance of tumor-derived DNA in total cell-free DNA, as measured by TP53 mutant allele frequency, also affected assay sensitivity. All patients with reversions detected in tumor-derived DNA were resistant to platin- or poly ADP ribose polymerase inhibitor-based chemotherapy. Conclusion Reversion mutations can be detected in an unbiased analysis of cfDNA, suggesting clinical utility for predicting chemotherapy response in recurrent HGSC.

Integrated analysis of oral tongue squamous cell carcinoma identifies key variants and pathways linked to risk habits, HPV, clinical parameters and tumor recurrence.

Oral tongue squamous cell carcinomas (OTSCC) are a homogeneous group of tumors characterized by aggressive behavior, early spread to lymph nodes and a higher rate of regional failure. Additionally, the incidence of OTSCC among younger population (<50yrs) is on the rise; many of whom lack the typical associated risk factors of alcohol and/or tobacco exposure. We present data on single nucleotide variations (SNVs), indels, regions with loss of heterozygosity (LOH), and copy number variations (CNVs) from fifty-paired oral tongue primary tumors and link the significant somatic variants with clinical parameters, epidemiological factors including human papilloma virus (HPV) infection and tumor recurrence. Apart from the frequent somatic variants harbored in TP53, CASP8, RASA1, NOTCH and CDKN2A genes, significant amplifications and/or deletions were detected in chromosomes 6-9, and 11 in the tumors. Variants in CASP8 and CDKN2A were mutually exclusive. CDKN2A, PIK3CA, RASA1 and DMD variants were exclusively linked to smoking, chewing, HPV infection and tumor stage. We also performed a whole-genome gene expression study that identified matrix metalloproteases to be highly expressed in tumors and linked pathways involving arachidonic acid and NF-k-B to habits and distant metastasis, respectively. Functional knockdown studies in cell lines demonstrated the role of CASP8 in a HPV-negative OTSCC cell line. Finally, we identified a 38-gene minimal signature that predicts tumor recurrence using an ensemble machine-learning method. Taken together, this study links molecular signatures to various clinical and epidemiological factors in a homogeneous tumor population with a relatively high HPV prevalence.

SInC: an accurate and fast error-model based simulator for SNPs, Indels and CNVs coupled with a read generator for short-read sequence data.

BACKGROUND: The rapid advancements in the field of genome sequencing are aiding our understanding on many biological systems. In the last five years, computational biologists and bioinformatics specialists have come up with newer, better and more efficient tools towards the discovery, analysis and interpretation of different genomic variants from high-throughput sequencing data. Availability of reliable simulated dataset is essential and is the first step towards testing any newly developed analytical tools for variant discovery. Although there are tools currently available that can simulate variants, none present the possibility of simulating all the three major types of variations (Single Nucleotide Polymorphisms, Insertions and Deletions and Copy Number Variations) and can generate reads taking a realistic error-model into consideration. Therefore, an efficient simulator and read generator is needed that can simulate variants taking the error rates of true biological samples into consideration. RESULTS: We report SInC (Snp, Indel and Cnv) an open-source variant simulator and read generator capable of simulating all the three common types of biological variants taking into account a distribution of base quality score from a most commonly used next-generation sequencing instrument from Illumina. SInC is capable of generating single- and paired-end reads with user-defined insert size and with high efficiency compared to the other existing tools. SInC, due to its multi-threaded capability during read generation, has a low time footprint. SInC is currently optimised to work in limited infrastructure setup and can efficiently exploit the commonly used quad-core desktop architecture to simulate short sequence reads with deep coverage for large genomes. CONCLUSIONS: We have come up with a user-friendly multi-variant simulator and read-generator tools called SInC. SInC can be downloaded from http://sourceforge.net/projects/sincsimulator.

A draft of the genome and four transcriptomes of a medicinal and pesticidal angiosperm Azadirachta indica.

BACKGROUND: The Azadirachta indica (neem) tree is a source of a wide number of natural products, including the potent biopesticide azadirachtin. In spite of its widespread applications in agriculture and medicine, the molecular aspects of the biosynthesis of neem terpenoids remain largely unexplored. The current report describes the draft genome and four transcriptomes of A. indica and attempts to contextualise the sequence information in terms of its molecular phylogeny, transcript expression and terpenoid biosynthesis pathways. A. indica is the first member of the family Meliaceae to be sequenced using next generation sequencing approach. RESULTS: The genome and transcriptomes of A. indica were sequenced using multiple sequencing platforms and libraries. The A. indica genome is AT-rich, bears few repetitive DNA elements and comprises about 20,000 genes. The molecular phylogenetic analyses grouped A. indica together with Citrus sinensis from the Rutaceae family validating its conventional taxonomic classification. Comparative transcript expression analysis showed either exclusive or enhanced expression of known genes involved in neem terpenoid biosynthesis pathways compared to other sequenced angiosperms. Genome and transcriptome analyses in A. indica led to the identification of repeat elements, nucleotide composition and expression profiles of genes in various organs. CONCLUSIONS: This study on A. indica genome and transcriptomes will provide a model for characterization of metabolic pathways involved in synthesis of bioactive compounds, comparative evolutionary studies among various Meliaceae family members and help annotate their genomes. A better understanding of molecular pathways involved in the azadirachtin synthesis in A. indica will pave ways for bulk production of environment friendly biopesticides.

Customisation of the exome data analysis pipeline using a combinatorial approach.

The advent of next generation sequencing (NGS) technologies have revolutionised the way biologists produce, analyse and interpret data. Although NGS platforms provide a cost-effective way to discover genome-wide variants from a single experiment, variants discovered by NGS need follow up validation due to the high error rates associated with various sequencing chemistries. Recently, whole exome sequencing has been proposed as an affordable option compared to whole genome runs but it still requires follow up validation of all the novel exomic variants. Customarily, a consensus approach is used to overcome the systematic errors inherent to the sequencing technology, alignment and post alignment variant detection algorithms. However, the aforementioned approach warrants the use of multiple sequencing chemistry, multiple alignment tools, multiple variant callers which may not be viable in terms of time and money for individual investigators with limited informatics know-how. Biologists often lack the requisite training to deal with the huge amount of data produced by NGS runs and face difficulty in choosing from the list of freely available analytical tools for NGS data analysis. Hence, there is a need to customise the NGS data analysis pipeline to preferentially retain true variants by minimising the incidence of false positives and make the choice of right analytical tools easier. To this end, we have sampled different freely available tools used at the alignment and post alignment stage suggesting the use of the most suitable combination determined by a simple framework of pre-existing metrics to create significant datasets.

Re-engineering an in-vitro evolved ribozyme.

Ribox02 is an in-vitro evolved RNA molecule that exhibits the activity analogous to that of alcohol dehydrogenase, catalyzing redox reactions in a cofactor dependent manner. It forms a compact pseudo-knotted structure and oxidizes an alcohol seven orders of magnitude faster than the estimated spontaneous rate. To gain insights into the structure-function relationship of Ribox02, we firstly performed mutational studies to identify the critical nucleotide bases for catalysis and then engineered the ribozyme structure to improve its overall fold. The re-engineered Ribox02, named Robust, was able to catalyze the reaction approximately 25% more efficiently, leading us to generate a transacting system.

Reduction of an aldehyde by a NADH/Zn2+ -dependent redox active ribozyme.

We report here the ability of an alcohol dehydrogenase (ADH) ribozyme to reduce a benzaldehyde. While the ribozyme was initially evolved in vitro based on the activity for the NAD+-dependent oxidation of the benzyl alcohol, we found that this ADH ribozyme is also capable of reducing the aldehyde in the presence of NADH and Zn2+. The rate acceleration gained by ribozyme catalysis was more than 6 orders of magnitude larger than the spontaneous reaction. Although the reversibility of phosphordiester and acyl transfer reactions catalyzed by ribozymes was known, that of other chemical reactions has not been well established. This study has demonstrated the reversibility of a hydride transfer chemistry catalyzed by the ADH ribozyme. Most interestingly, the ribozyme shares many features with the protein ADHs, e.g., reversibility and NADH/Zn2+ dependence.

An alcohol dehydrogenase ribozyme.

We report an RNA molecule that exhibits activity analogous to that of alcohol dehydrogenase (ADH). Directed in vitro evolution was used to enrich nicotinamide adenine dinucleotide (NAD+)-dependent redox-active RNAs from a combinatorial pool. The most active ribozyme in the population forms a compact pseudoknotted structure and oxidizes an alcohol seven orders of magnitude faster than the estimated spontaneous rate. Moreover, this ADH RNA was coupled with a redox relay between NADH and flavin adenine dinucleotide to give a NAD+-regeneration system. Our demonstration of the redox ability of RNA adds support to an RNA-based metabolic system in ancient life.