Mass General Cancer Center Announces First Recipients of Krantz Awards for Cancer Research
The inaugural class of awardees will receive more than $6 million in funding to accelerate groundbreaking cancer research.
Krantz Family Center for Cancer Research
Contact Information
Michael S. Lawrence, PhD
Assistant Professor of Pathology
Harvard Medical School
Assistant Geneticist
Mass General Cancer Center
Program Affiliations
Krantz Family Center for Cancer Research
Massachusetts General Hospital Pathology Service
2023 Quantum Award: Targeting transcription factors to open doors to new cancer therapies
Team: Liron Bar-Peled, PhD, Michael Lawrence, PhD and Chris Ott, PhD.
Learn more about the team's project and the Krantz Awards
Cancer results from alterations to DNA that lead to the activation of oncogenes or the inactivation of tumor suppressors. The Lawrence laboratory focuses on understanding the many ways this can happen, using computation as a powerful microscope to study the processes of DNA damage and repair, gene expression and genome replication, and cancer driver genes. Over our lifetimes, DNA slowly accumulates mutations due to environmental toxins and radiation, as well as from naturally occurring copying errors. The vast majority of mutations have little or no effect on a cell, but out of all possible mutations, a few may hit exactly the right place in the genome, where they can act as a “driver mutation,” pushing the cell toward aggressive growth and tumor formation. Sequencing the DNA in a tumor reveals not only its driver mutations, but also all the other “passenger mutations” that were present in the tumor-initiating cell. We seek insights about cancer from both driver and passenger mutations.
Cancers vary over many orders of magnitude in their total background mutation burden, ranging from very quiet tumor types such as leukemias and childhood tumors, which may have fewer than 10 somatic mutations in their exome, to carcinogen-associated tumor types such as lung cancer and melanoma, which may have over 1000. Mutations have many causes, and each mutagen can leave a telltale signature. For instance, spontaneous deamination of methylated CpG’s causes the transition mutations that dominate many tumor types. Mutagens in tobacco smoke cause G-to-T transversions. Ultraviolet radiation causes C-to-T mutations at dipyrimidines. Agitated APOBEC enzymes cause mutations at C’s preceded by T. Loss of mismatch repair causes microsatellite instability (MSI), marked by expansion and contraction of simple- sequence repeats, as well as characteristic types of singlebase changes. Tumors carrying mutations in the proofreading exonuclease domain of polymerase epsilon (POLE) tend to accrue C-to-A mutations at the trinucleotide TCT. Very rare “MSI+POLE” cancers show the highest yet known somatic mutation burdens, with upwards of 10,000 coding mutations per patient. Patients affected by MSI and/or POLE mutagenesis are known to experience better clinical outcomes, probably thanks to their high neoantigen loads which attract a powerful immune response. Our most recent research has focused on a less wellstudied signal in somatic mutation datasets, mutational asymmetries between the two DNA strands. These illuminate transcriptional or “T-class” mutational patterns, associated with exposure to tobacco smoke, UV radiation, and a yet-unknown agent in liver cancer, as well as replicative or “R-class” patterns, associated with MSI, APOBEC, POLE, and a yet-unknown agent in esophageal cancer.
Statistical approaches for distinguishing driver mutations from passenger mutations have relied on the gold standard of recurrence across patients. Seeing exactly the same DNA base-pair mutated recurrently across patients has been taken as proof that the mutation must be under functional selection for contributing to tumor fitness. The assumption is that mutational processes, being essentially random, are unlikely to hit the exact same base-pair over and over again. Our recent discoveries about APOBEC mutagenesis have cast doubt on this assumption. We have shown that APOBEC3A has a very strong preference for mutating cytosines presented in a short loop at the end of a strongly paired DNA hairpins. Our results indicate that there are multiple routes to cancer mutational hotspots. Driver mutation hotspots in oncogenes can rise to prominence through positive selection, and are not restricted to the “favorite” sites of any particular mutagen. In contrast, special DNA sites (like hairpins) that happen to be optimal substrates for a mutagen (like APOBEC) can give rise to “passenger hotspot mutations” that owe their prevalence to substrate optimality, not to any effects on tumor fitness. These findings apply not just to APOBEC but to all mutation signatures, and remind us of the need to be careful about assuming that all recurrent mutations are causative drivers of disease.
Figure: The mutational landscape of a cancer cell across size regimes. At the smallest scale, local DNA trinucleotide sequences (lower-left foreground) correlate with the "mutational signatures" induced by various mutagens. At the largest scale (background of image), chromatin is organized into multi-megabase domains comprising Compartment B (tightly packed, gene-poor DNA lining the nuclear periphery) and Compartment A (gene-rich open DNA in the nuclear interior). Mutations induced by APOBEC enzymes (yellow points) are distributed equally across the two compartments, but most other types of mutations (blue points) are concentrated in Compartment B. Between the large and small extremes lies the "mesoscale" regime, where genomic features like hairpin-forming ability are determined. DNA exposed in a hairpin loop is vulnerable to attack by the enzyme APOBEC3A (center), giving rise to highly recurrent passenger mutations in cancer.
Selected Publications
Isozaki H^, Sakhtemani R, Abbasi A, Nikpour N, Stanzione M, Oh S, Langenbucher A, Monroe S, Su W, Cabanos HF, Siddiqui FM, Phan N, Jalili P, Timonina D, Bilton S, Gomez- Caraballo M, Archibald HL, Nangia V, Dionne K, Riley A, Lawlor M, Banwait MK, Cobb RG, Zou L, Dyson NJ, Ott CJ, Benes C, Getz G, Chan CS, Shaw AT, Gainor JF, Lin JJ, Sequist LV, Piotrowska Z, Yeap BY, Engelman JA, Lee JJ, Maruvka YE, Buisson R, Lawrence MS*^, Hata AN*^. Therapy induced APOBEC3A drives evolution of persistent cancer cells. Nature. 2023 Aug;620(7973):393-401.
Langenbucher A, Bowen D, Sakhtemani R, Bournique E, Wise JF, Zou L*, Bhagwat AS*, Buisson R*, Lawrence MS*. An extended APOBEC3A mutation signature in cancer. Nat Commun. 2021 Mar 11;12(1):1602.
Jalili P, Bowen D, Langenbucher A, Park S, Aguirre K, Corcoran RB, Fleischman AG, Lawrence MS*, Zou L*, Buisson R*. Quantification of ongoing APOBEC3A activity in tumor cells by monitoring RNA editing at hotspots. Nat Commun. 2020 Jun 12;11(1):2971.
Buisson R, Langenbucher A, Bowen D, Kwan EE, Benes CH, Zou L*, Lawrence MS*. Passenger hotspot mutations in cancer driven by APOBEC3A and mesoscale features. Science. 2019 Jun 28; 364(6447):eaaw2872.
Buisson R, Lawrence MS, Benes C, Zou L. APOBEC3A and APOBEC3B activities render cancer cells susceptible to ATR inhibition. Cancer Res. 2017 Jul 11.
*Co-authors
^Co-corresponding authors
Data Analyst - Cancer Computational Biology
Emails:
erheinbay@mgh.harvard.edu
mslawrence@mgh.harvard.edu
Unique opportunity to join an interdisciplinary team bridging the Harvard Medical School, the Massachusetts General Hospital, and the Broad Institute of Harvard and MIT. The Rheinbay Lab and Lawrence Lab at the Massachusetts General Hospital Cancer Center seek well-qualified candidates to join a team of computational biologists working at the forefront of cancer research and treatment. We use computation as a powerful microscope to study both the fundamental biology of cancer initiation and progression, as well the diagnosis and treatment of cancer patients in the hospital setting.
Current research interests:
Principal Duties:
Required skills:
Postdoctoral Position at the Lawrence Laboratory
Unique opportunity to join an interdisciplinary team bridging the Harvard Medical School, the Massachusetts General Hospital, and the Broad Institute of Harvard and MIT. The Lawrence Lab at the Massachusetts General Hospital Cancer Center seeks well-?qualified candidates to join a team of computational biologists working at the forefront of cancer research and treatment.
For more information, please see this flyer.
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The inaugural class of awardees will receive more than $6 million in funding to accelerate groundbreaking cancer research.
Targeted therapies induced tumor expression of the APOBEC3A protein, which was shown to directly cause new mutations and accelerate the development of drug resistance.