Andrew J. Blumberg

Clonal evolution of glioblastoma under therapy

Glioblastoma (GBM) is the most common and aggressive primary brain tumor. To better understand how GBM evolves, we analyzed longitudinal genomic and transcriptomic data from 114 patients. The analysis shows a highly branched evolutionary pattern in which 63% of patients experience expression-based subtype changes. The branching pattern, together with estimates of evolutionary rate, suggests that relapse-associated clones typically existed years before diagnosis. Fifteen percent of tumors present hypermutation at relapse in highly expressed genes, with a clear mutational signature. We find that 11% of recurrence tumors harbor mutations in LTBP4, which encodes a protein binding to TGF-β. Silencing LTBP4 in GBM cells leads to suppression of TGF-β activity and decreased cell proliferation. In recurrent GBM with wild-type IDH1, high LTBP4 expression is associated with worse prognosis, highlighting the TGF-β pathway as a potential therapeutic target in GBM.

A Hybrid Architecture for Interactive Verifiable Computation

We consider interactive, proof-based verifiable computation: how can a client machine specify a computation to a server, receive an answer, and then engage the server in an interactive protocol that convinces the client that the answer is correct, with less work for the client than executing the computation in the first place? Complexity theory and cryptography offer solutions in principle, but if implemented naively, they are ludicrously expensive. Recently, however, several strands of work have refined this theory and implemented the resulting protocols in actual systems. This work is promising but suffers from one of two problems: either it relies on expensive cryptography, or else it applies to a restricted class of computations. Worse, it is not always clear which protocol will perform better for a given problem.We describe a system that (a) extends optimized refinements of the non-cryptographic protocols to a much broader class of computations, (b) uses static analysis to fail over to the cryptographic ones when the non-cryptographic ones would be more expensive, and (c) incorporates this core into a built system that includes a compiler for a high-level language, a distributed server, and GPU acceleration. Experimental results indicate that our system performs better and applies more widely than the best in the literature.

Verifying computations with state

When a client outsources a job to a third party (e.g., the cloud), how can the client check the result, without re-executing the computation? Recent work in proof-based verifiable computation has made significant progress on this problem by incorporating deep results from complexity theory and cryptography into built systems. However, these systems work within a stateless model: they exclude computations that interact with RAM or a disk, or for which the client does not have the full input. This paper describes Pantry, a built system that overcomes these limitations. Pantry composes proof-based verifiable computation with untrusted storage: the client expresses its computation in terms of digests that attest to state, and verifiably outsources that computation. Using Pantry, we extend verifiability to MapReduce jobs, simple database queries, and interactions with private state. Thus, Pantry takes another step toward practical proof-based verifiable computation for realistic applications.

Localization theorems in topological Hochschild homology and topological cyclic homology

We construct localization cofibration sequences for the topological Hochschild homology (THH ) and topological cyclic homology (TC ) of small spectral categories. Using a global construction of the THH and TC of a scheme in terms of the perfect complexes in a spectrally enriched version of the category of unbounded complexes, the sequences specialize to localization cofibration sequences associated to the inclusion of an open subscheme. These are the targets of the cyclotomic trace from the localization sequence of Thomason‐Trobaugh in K ‐theory. We also deduce versions of Thomason’s blow-up formula and the projective bundle formula for THH and TC . 19D55; 14F43

Resolving the conflict between generality and plausibility in verified computation

The area of proof-based verified computation (outsourced computation built atop probabilistically checkable proofs and cryptographic machinery) has lately seen renewed interest. Although recent work has made great strides in reducing the overhead of naive applications of the theory, these schemes still cannot be considered practical. A core issue is that the work for the server is immense, in general; it is practical only for hand-compiled computations that can be expressed in special forms. This paper addresses that problem. Provided one is willing to batch verification, we develop a protocol that achieves the efficiency of the best manually constructed protocols in the literature yet applies to most computations. We show that Quadratic Arithmetic Programs, a new formalism for representing computations efficiently, can yield a particularly efficient PCP that integrates easily into the core protocols, resulting in a server whose work is roughly linear in the running time of the computation. We implement this protocol in the context of a system, called Zaatar, that includes a compiler and a GPU implementation. Zaatar is almost usable for real problems---without special-purpose tailoring. We argue that many (but not all) of the next research questions in verified computation are questions in secure systems.

Verifying computations without reexecuting them

From theoretical possibility to near practicality.

Privacy and accountability for location-based aggregate statistics

A significant and growing class of location-based mobile applications aggregate position data from individual devices at a server and compute aggregate statistics over these position streams. Because these devices can be linked to the movement of individuals, there is significant danger that the aggregate computation will violate the location privacy of individuals. This paper develops and evaluates PrivStats, a system for computing aggregate statistics over location data that simultaneously achieves two properties: first, provable guarantees on location privacy even in the face of any side information about users known to the server, and second, privacy-preserving accountability (i.e., protection against abusive clients uploading large amounts of spurious data). PrivStats achieves these properties using a new protocol for uploading and aggregating data anonymously as well as an efficient zero-knowledge proof of knowledge protocol we developed from scratch for accountability. We implemented our system on Nexus One smartphones and commodity servers. Our experimental results demonstrate that PrivStats is a practical system: computing a common aggregate (e.g., count) over the data of 10,000 clients takes less than 0.46 s at the server and the protocol has modest latency (0.6 s) to upload data from a Nexus phone. We also validated our protocols on real driver traces from the CarTel project.

Spatiotemporal Genomic Architecture Informs Precision Oncology in Glioblastoma

Precision medicine in cancer proposes that genomic characterization of tumors can inform personalized targeted therapies. However, this proposition is complicated by spatial and temporal heterogeneity. Here we study genomic and expression profiles across 127 multisector or longitudinal specimens from 52 individuals with glioblastoma (GBM). Using bulk and single-cell data, we find that samples from the same tumor mass share genomic and expression signatures, whereas geographically separated, multifocal tumors and/or long-term recurrent tumors are seeded from different clones. Chemical screening of patient-derived glioma cells (PDCs) shows that therapeutic response is associated with genetic similarity, and multifocal tumors that are enriched with PIK3CA mutations have a heterogeneous drug-response pattern. We show that targeting truncal events is more efficacious than targeting private events in reducing the tumor burden. In summary, this work demonstrates that evolutionary inference from integrated genomic analysis in multisector biopsies can inform targeted therapeutic interventions for patients with GBM.

Transcription restores DNA repair to heterochromatin, determining regional mutation rates in cancer genomes

Somatic mutations in cancer are more frequent in heterochromatic and late-replicating regions of the genome. We report that regional disparities in mutation density are virtually abolished within transcriptionally silent genomic regions of cutaneous squamous cell carcinomas (cSCCs) arising in an XPC(-/-) background. XPC(-/-) cells lack global genome nucleotide excision repair (GG-NER), thus establishing differential access of DNA repair machinery within chromatin-rich regions of the genome as the primary cause for the regional disparity. Strikingly, we find that increasing levels of transcription reduce mutation prevalence on both strands of gene bodies embedded within H3K9me3-dense regions, and only to those levels observed in H3K9me3-sparse regions, also in an XPC-dependent manner. Therefore, transcription appears to reduce mutation prevalence specifically by relieving the constraints imposed by chromatin structure on DNA repair. We model this relationship among transcription, chromatin state, and DNA repair, revealing a new, personalized determinant of cancer risk.

An ∞-categorical approach to R-line bundles, R-module Thom spectra, and twisted R-homology

We develop a generalization of the theory of Thom spectra using the language of infinity categories. This treatment exposes the conceptual underpinnings of the Thom spectrum functor: we use a new model of parametrized spectra, and our definition is motivated by the geometric definition of Thom spectra of May-Sigurdsson. For an associative ring spectrum