Publications by authors named "Nicholas J Haradhvala"

13 Publications

  • Page 1 of 1

Single-cell RNA sequencing reveals compromised immune microenvironment in precursor stages of multiple myeloma.

Nat Cancer 2020 May 27;1(5):493-506. Epub 2020 Apr 27.

Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, 02215, USA.

Precursor states of Multiple Myeloma (MM) and its native tumor microenvironment need in-depth molecular characterization to better stratify and treat patients at risk. Using single-cell RNA sequencing of bone marrow cells from precursor stages, MGUS and smoldering myeloma (SMM), to full-blown MM alongside healthy donors, we demonstrate early immune changes during patient progression. We find NK cell abundance is frequently increased in early stages, and associated with altered chemokine receptor expression. As early as SMM, we show loss of GrK memory cytotoxic T-cells, and show their critical role in MM immunosurveillance in mouse models. Finally, we report MHC class II dysregulation in CD14 monocytes, which results in T cell suppression . These results provide a comprehensive map of immune changes at play over the evolution of pre-malignant MM, which will help develop strategies for immune-based patient stratification.
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http://dx.doi.org/10.1038/s43018-020-0053-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785110PMC
May 2020

DNA Polymerase and Mismatch Repair Exert Distinct Microsatellite Instability Signatures in Normal and Malignant Human Cells.

Cancer Discov 2021 May 18;11(5):1176-1191. Epub 2020 Dec 18.

Department of Pediatric Hematology-Oncology, Children's Hospital of Pittsburgh of UPMC, Pittsburgh, Pennsylvania.

Although replication repair deficiency, either by mismatch repair deficiency (MMRD) and/or loss of DNA polymerase proofreading, can cause hypermutation in cancer, microsatellite instability (MSI) is considered a hallmark of MMRD alone. By genome-wide analysis of tumors with germline and somatic deficiencies in replication repair, we reveal a novel association between loss of polymerase proofreading and MSI, especially when both components are lost. Analysis of indels in microsatellites (MS-indels) identified five distinct signatures (MS-sigs). MMRD MS-sigs are dominated by multibase losses, whereas mutant-polymerase MS-sigs contain primarily single-base gains. MS deletions in MMRD tumors depend on the original size of the MS and converge to a preferred length, providing mechanistic insight. Finally, we demonstrate that MS-sigs can be a powerful clinical tool for managing individuals with germline MMRD and replication repair-deficient cancers, as they can detect the replication repair deficiency in normal cells and predict their response to immunotherapy. SIGNIFICANCE: Exome- and genome-wide MSI analysis reveals novel signatures that are uniquely attributed to mismatch repair and DNA polymerase. This provides new mechanistic insight into MS maintenance and can be applied clinically for diagnosis of replication repair deficiency and immunotherapy response prediction..
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http://dx.doi.org/10.1158/2159-8290.CD-20-0790DOI Listing
May 2021

A post-transcriptional program of chemoresistance by AU-rich elements and TTP in quiescent leukemic cells.

Genome Biol 2020 02 10;21(1):33. Epub 2020 Feb 10.

Massachusetts General Hospital Cancer Center, Harvard Medical School, 185 Cambridge St, CPZN4202, Boston, MA, 02114, USA.

Background: Quiescence (G0) is a transient, cell cycle-arrested state. By entering G0, cancer cells survive unfavorable conditions such as chemotherapy and cause relapse. While G0 cells have been studied at the transcriptome level, how post-transcriptional regulation contributes to their chemoresistance remains unknown.

Results: We induce chemoresistant and G0 leukemic cells by serum starvation or chemotherapy treatment. To study post-transcriptional regulation in G0 leukemic cells, we systematically analyzed their transcriptome, translatome, and proteome. We find that our resistant G0 cells recapitulate gene expression profiles of in vivo chemoresistant leukemic and G0 models. In G0 cells, canonical translation initiation is inhibited; yet we find that inflammatory genes are highly translated, indicating alternative post-transcriptional regulation. Importantly, AU-rich elements (AREs) are significantly enriched in the upregulated G0 translatome and transcriptome. Mechanistically, we find the stress-responsive p38 MAPK-MK2 signaling pathway stabilizes ARE mRNAs by phosphorylation and inactivation of mRNA decay factor, Tristetraprolin (TTP) in G0. This permits expression of ARE mRNAs that promote chemoresistance. Conversely, inhibition of TTP phosphorylation by p38 MAPK inhibitors and non-phosphorylatable TTP mutant decreases ARE-bearing TNFα and DUSP1 mRNAs and sensitizes leukemic cells to chemotherapy. Furthermore, co-inhibiting p38 MAPK and TNFα prior to or along with chemotherapy substantially reduces chemoresistance in primary leukemic cells ex vivo and in vivo.

Conclusions: These studies uncover post-transcriptional regulation underlying chemoresistance in leukemia. Our data reveal the p38 MAPK-MK2-TTP axis as a key regulator of expression of ARE-bearing mRNAs that promote chemoresistance. By disrupting this pathway, we develop an effective combination therapy against chemosurvival.
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http://dx.doi.org/10.1186/s13059-020-1936-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7011231PMC
February 2020

The repertoire of mutational signatures in human cancer.

Nature 2020 02 5;578(7793):94-101. Epub 2020 Feb 5.

Wellcome Sanger Institute, Hinxton, UK.

Somatic mutations in cancer genomes are caused by multiple mutational processes, each of which generates a characteristic mutational signature. Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), we characterized mutational signatures using 84,729,690 somatic mutations from 4,645 whole-genome and 19,184 exome sequences that encompass most types of cancer. We identified 49 single-base-substitution, 11 doublet-base-substitution, 4 clustered-base-substitution and 17 small insertion-and-deletion signatures. The substantial size of our dataset, compared with previous analyses, enabled the discovery of new signatures, the separation of overlapping signatures and the decomposition of signatures into components that may represent associated-but distinct-DNA damage, repair and/or replication mechanisms. By estimating the contribution of each signature to the mutational catalogues of individual cancer genomes, we revealed associations of signatures to exogenous or endogenous exposures, as well as to defective DNA-maintenance processes. However, many signatures are of unknown cause. This analysis provides a systematic perspective on the repertoire of mutational processes that contribute to the development of human cancer.
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http://dx.doi.org/10.1038/s41586-020-1943-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7054213PMC
February 2020

Analyses of non-coding somatic drivers in 2,658 cancer whole genomes.

Nature 2020 02 5;578(7793):102-111. Epub 2020 Feb 5.

Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.

The discovery of drivers of cancer has traditionally focused on protein-coding genes. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers, raise doubts about others and identify novel candidates, including point mutations in the 5' region of TP53, in the 3' untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.
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http://dx.doi.org/10.1038/s41586-020-1965-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7054214PMC
February 2020

Scaling computational genomics to millions of individuals with GPUs.

Genome Biol 2019 11 1;20(1):228. Epub 2019 Nov 1.

Broad Institute of MIT and Harvard, Cambridge, MA, USA.

Current genomics methods are designed to handle tens to thousands of samples but will need to scale to millions to match the pace of data and hypothesis generation in biomedical science. Here, we show that high efficiency at low cost can be achieved by leveraging general-purpose libraries for computing using graphics processing units (GPUs), such as PyTorch and TensorFlow. We demonstrate > 200-fold decreases in runtime and ~ 5-10-fold reductions in cost relative to CPUs. We anticipate that the accessibility of these libraries will lead to a widespread adoption of GPUs in computational genomics.
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http://dx.doi.org/10.1186/s13059-019-1836-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6823959PMC
November 2019

Passenger Hotspot Mutations in Cancer.

Cancer Cell 2019 09;36(3):288-301.e14

The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Center for Cancer Research, Massachusetts General Hospital, Boston, MA 02114, USA; Harvard Medical School, 250 Longwood Avenue, Boston, MA 02115, USA; Department of Pathology, Massachusetts General Hospital, Boston, MA 02114, USA. Electronic address:

Current statistical models for assessing hotspot significance do not properly account for variation in site-specific mutability, thereby yielding many false-positives. We thus (i) detail a Log-normal-Poisson (LNP) background model that accounts for this variability in a manner consistent with models of mutagenesis; (ii) use it to show that passenger hotspots arise from all common mutational processes; and (iii) apply it to a ∼10,000-patient cohort to nominate driver hotspots with far fewer false-positives compared with conventional methods. Overall, we show that many cancer hotspot mutations recurring at the same genomic site across multiple tumors are actually passenger events, recurring at inherently mutable genomic sites under no positive selection.
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http://dx.doi.org/10.1016/j.ccell.2019.08.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7371346PMC
September 2019

RNA sequence analysis reveals macroscopic somatic clonal expansion across normal tissues.

Science 2019 Jun;364(6444)

Broad Institute of MIT and Harvard, Cambridge, MA, USA.

How somatic mutations accumulate in normal cells is poorly understood. A comprehensive analysis of RNA sequencing data from ~6700 samples across 29 normal tissues revealed multiple somatic variants, demonstrating that macroscopic clones can be found in many normal tissues. We found that sun-exposed skin, esophagus, and lung have a higher mutation burden than other tested tissues, which suggests that environmental factors can promote somatic mosaicism. Mutation burden was associated with both age and tissue-specific cell proliferation rate, highlighting that mutations accumulate over both time and number of cell divisions. Finally, normal tissues were found to harbor mutations in known cancer genes and hotspots. This study provides a broad view of macroscopic clonal expansion in human tissues, thus serving as a foundation for associating clonal expansion with environmental factors, aging, and risk of disease.
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http://dx.doi.org/10.1126/science.aaw0726DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7350423PMC
June 2019

Analyzing Frequently Mutated Genes and the Association With Tumor Mutation Load.

JAMA Oncol 2019 04;5(4):577

Cancer Center, Massachusetts General Hospital, Boston.

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http://dx.doi.org/10.1001/jamaoncol.2019.0127DOI Listing
April 2019

Quantification of somatic mutation flow across individual cell division events by lineage sequencing.

Genome Res 2018 12 20;28(12):1901-1918. Epub 2018 Nov 20.

Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.

Mutation data reveal the dynamic equilibrium between DNA damage and repair processes in cells and are indispensable to the understanding of age-related diseases, tumor evolution, and the acquisition of drug resistance. However, available genome-wide methods have a limited ability to resolve rare somatic variants and the relationships between these variants. Here, we present lineage sequencing, a new genome sequencing approach that enables somatic event reconstruction by providing quality somatic mutation call sets with resolution as high as the single-cell level in subject lineages. Lineage sequencing entails sampling single cells from a population and sequencing subclonal sample sets derived from these cells such that knowledge of relationships among the cells can be used to jointly call variants across the sample set. This approach integrates data from multiple sequence libraries to support each variant and precisely assigns mutations to lineage segments. We applied lineage sequencing to a human colon cancer cell line with a DNA polymerase epsilon () proofreading deficiency (HT115) and a human retinal epithelial cell line immortalized by constitutive telomerase expression (RPE1). Cells were cultured under continuous observation to link observed single-cell phenotypes with single-cell mutation data. The high sensitivity, specificity, and resolution of the data provide a unique opportunity for quantitative analysis of variation in mutation rate, spectrum, and correlations among variants. Our data show that mutations arrive with nonuniform probability across sublineages and that DNA lesion dynamics may cause strong correlations between certain mutations.
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http://dx.doi.org/10.1101/gr.238543.118DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6280753PMC
December 2018

Structural Alterations Driving Castration-Resistant Prostate Cancer Revealed by Linked-Read Genome Sequencing.

Cell 2018 07 18;174(2):433-447.e19. Epub 2018 Jun 18.

Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.

Nearly all prostate cancer deaths are from metastatic castration-resistant prostate cancer (mCRPC), but there have been few whole-genome sequencing (WGS) studies of this disease state. We performed linked-read WGS on 23 mCRPC biopsy specimens and analyzed cell-free DNA sequencing data from 86 patients with mCRPC. In addition to frequent rearrangements affecting known prostate cancer genes, we observed complex rearrangements of the AR locus in most cases. Unexpectedly, these rearrangements include highly recurrent tandem duplications involving an upstream enhancer of AR in 70%-87% of cases compared with <2% of primary prostate cancers. A subset of cases displayed AR or MYC enhancer duplication in the context of a genome-wide tandem duplicator phenotype associated with CDK12 inactivation. Our findings highlight the complex genomic structure of mCRPC, nominate alterations that may inform prostate cancer treatment, and suggest that additional recurrent events in the non-coding mCRPC genome remain to be discovered.
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http://dx.doi.org/10.1016/j.cell.2018.05.036DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6046279PMC
July 2018

Analysis of somatic microsatellite indels identifies driver events in human tumors.

Nat Biotechnol 2017 Oct 11;35(10):951-959. Epub 2017 Sep 11.

Massachusetts General Hospital Center for Cancer Research, Charlestown, Massachusetts, USA.

Microsatellites (MSs) are tracts of variable-length repeats of short DNA motifs that exhibit high rates of mutation in the form of insertions or deletions (indels) of the repeated motif. Despite their prevalence, the contribution of somatic MS indels to cancer has been largely unexplored, owing to difficulties in detecting them in short-read sequencing data. Here we present two tools: MSMuTect, for accurate detection of somatic MS indels, and MSMutSig, for identification of genes containing MS indels at a higher frequency than expected by chance. Applying MSMuTect to whole-exome data from 6,747 human tumors representing 20 tumor types, we identified >1,000 previously undescribed MS indels in cancer genes. Additionally, we demonstrate that the number and pattern of MS indels can accurately distinguish microsatellite-stable tumors from tumors with microsatellite instability, thus potentially improving classification of clinically relevant subgroups. Finally, we identified seven MS indel driver hotspots: four in known cancer genes (ACVR2A, RNF43, JAK1, and MSH3) and three in genes not previously implicated as cancer drivers (ESRP1, PRDM2, and DOCK3).
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http://dx.doi.org/10.1038/nbt.3966DOI Listing
October 2017

Mutational Strand Asymmetries in Cancer Genomes Reveal Mechanisms of DNA Damage and Repair.

Cell 2016 Jan 21;164(3):538-49. Epub 2016 Jan 21.

Massachusetts General Hospital Cancer Center and Department of Pathology, 55 Fruit Street, Boston, MA 02114, USA; Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA. Electronic address:

Mutational processes constantly shape the somatic genome, leading to immunity, aging, cancer, and other diseases. When cancer is the outcome, we are afforded a glimpse into these processes by the clonal expansion of the malignant cell. Here, we characterize a less explored layer of the mutational landscape of cancer: mutational asymmetries between the two DNA strands. Analyzing whole-genome sequences of 590 tumors from 14 different cancer types, we reveal widespread asymmetries across mutagenic processes, with transcriptional ("T-class") asymmetry dominating UV-, smoking-, and liver-cancer-associated mutations and replicative ("R-class") asymmetry dominating POLE-, APOBEC-, and MSI-associated mutations. We report a striking phenomenon of transcription-coupled damage (TCD) on the non-transcribed DNA strand and provide evidence that APOBEC mutagenesis occurs on the lagging-strand template during DNA replication. As more genomes are sequenced, studying and classifying their asymmetries will illuminate the underlying biological mechanisms of DNA damage and repair.
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http://dx.doi.org/10.1016/j.cell.2015.12.050DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4753048PMC
January 2016