Research Summary

Development of computational models for early detection of cancer lesions and progression to metastatic disease can help discriminate between high and low cancer risk profiles. Therefore, we seek to exploit diverse, high-throughput genomic and clinical data to understand the molecular networks underlying fundamental cellular processes that can eventually stratify patients by non-traditional underpinnings, including transcriptional regulation, epigenetic signaling, and chemosensitivity. Our algorithmic methods draw on machine learning, a computational field concerned with learning accurate, predictive models from noisy and high-dimensional data.

Another area of research includes developing standardized methods and measures to integrate drug toxicity, quality of life, and efficacy measures for breast cancer patients. We are building infrastructure and tools to support patient-reported outcomes collection and downstream analysis and visualization.

Research Funding

  • July 19, 2023 - July 19, 2028 - Analyzing Patient-level Data in a Breast Cancer Clinical Trial , Principal Investigator . Sponsor: NCI, Sponsor Award ID: 1R01CA283179-01
  • September 1, 2021 - September 17, 2026 - Developing a Toxicity Framework using Patient-Reported Outcome , Principal Investigator . Sponsor: The Burroughs Wellcome Fund, Sponsor Award ID:
  • September 15, 2021 - August 31, 2023 - Predicting the Likelihood of Immune-related Adverse Events in Breast Cancer Patients , Principal Investigator . Sponsor: NIH, Sponsor Award ID: R21CA258218
  • September 8, 2017 - August 31, 2022 - , Co-Investigator . Sponsor: NIH, Sponsor Award ID: P01CA210961


Postdoctoral Fellow, - Computational Chemical Biology, Broad Institute of Harvard and MIT
B.S., - Electrical Engineering, Cornell University
Ph.D., - Computational Biology, Rockefeller University, Tri-Institutional Computational Biology Program

Honors & Awards

  • Burroughs Wellcome Fund Innovation in Regulatory Science Award, 2021-2026
  • Interstellar Award (New York Academy of Sciences/Japan Center for Medical Research and Development), 2019-2020
  • White House Presidential Innovation Fellow, 2016-2017
  • Sage Bionetworks Young Investigator Award, 2013

Selected Publications

  1. Steenbruggen TG, Wolf DM, Campbell MJ, Sanders J, Cornelissen S, Thijssen B, Salgado RA, Yau C, O-Grady N, Basu A, Bhaskaran R, Mittempergher L, Hirst GL, Coppe JP, Kok M, Sonke GS, van 't Veer LJ, Horlings HM. B-cells and regulatory T-cells in the microenvironment of HER2+ breast cancer are associated with decreased survival: a real-world analysis of women with HER2+ metastatic breast cancer. Breast Cancer Res. 2023 Oct 04; 25(1):117.  View on PubMed
  2. Yu K, Basu A, Yau C, Wolf DM, Goodarzi H, Bandyopadhyay S, Korkola JE, Hirst GL, Asare S, DeMichele A, Hylton N, Yee D, Esserman L, van 't Veer L, Sirota M. Computational drug repositioning for the identification of new agents to sensitize drug-resistant breast tumors across treatments and receptor subtypes. Front Oncol. 2023; 13:1192208.  View on PubMed
  3. Magbanua MJM, van 't Veer L, Clark AS, Chien AJ, Boughey JC, Han HS, Wallace A, Beckwith H, Liu MC, Yau C, Wileyto EP, Ordonez A, Solanki TI, Hsiao F, Lee JC, Basu A, Brown Swigart L, Perlmutter J, Delson AL, Bayne L, Deluca S, Yee SS, Carpenter EL, Esserman LJ, Park JW, Chodosh LA, DeMichele A. Outcomes and clinicopathologic characteristics associated with disseminated tumor cells in bone marrow after neoadjuvant chemotherapy in high-risk early stage breast cancer: the I-SPY SURMOUNT study. Breast Cancer Res Treat. 2023 Apr; 198(2):383-390.  View on PubMed
  4. Glencer AC, Miller PN, Greenwood H, Maldonado Rodas CK, Freimanis R, Basu A, Mukhtar RA, Brabham C, Kim P, Hwang ES, Rosenbluth JM, Hirst GL, Campbell MJ, Borowsky AD, Esserman LJ. Identifying Good Candidates for Active Surveillance of Ductal Carcinoma In Situ: Insights from a Large Neoadjuvant Endocrine Therapy Cohort. Cancer Res Commun. 2022 12; 2(12):1579-1589.  View on PubMed
  5. Wolf DM, Yau C, Wulfkuhle J, Brown-Swigart L, Gallagher RI, Lee PRE, Zhu Z, Magbanua MJ, Sayaman R, O'Grady N, Basu A, Delson A, Coppé JP, Lu R, Braun J, I-SPY2 Investigators, Asare SM, Sit L, Matthews JB, Perlmutter J, Hylton N, Liu MC, Pohlmann P, Symmans WF, Rugo HS, Isaacs C, DeMichele AM, Yee D, Berry DA, Pusztai L, Petricoin EF, Hirst GL, Esserman LJ, van 't Veer LJ. Redefining breast cancer subtypes to guide treatment prioritization and maximize response: Predictive biomarkers across 10 cancer therapies. Cancer Cell. 2022 06 13; 40(6):609-623.e6.  View on PubMed
  6. Marczyk M, Mrukwa A, Yau C, Wolf D, Chen YY, Balassanian R, Nanda R, Parker BA, Krings G, Sattar H, Zeck JC, Albain KS, Boughey JC, Liu MC, Elias AD, Clark AS, Venters SJ, Shad S, Basu A, Asare SM, Buxton M, Asare AL, Rugo HS, Perlmutter J, DeMichele AM, Yee D, Berry DA, Veer LV, Symmans WF, Esserman L, Pusztai L, I-SPY Consortium. Treatment Efficacy Score-continuous residual cancer burden-based metric to compare neoadjuvant chemotherapy efficacy between randomized trial arms in breast cancer trials. Ann Oncol. 2022 08; 33(8):814-823.  View on PubMed
  7. Teng YC, Sundaresan A, O'Hara R, Gant VU, Li M, Martire S, Warshaw JN, Basu A, Banaszynski LA. ATRX promotes heterochromatin formation to protect cells from G-quadruplex DNA-mediated stress. Nat Commun. 2021 06 23; 12(1):3887.  View on PubMed
  8. O'Grady N, Gibbs DL, Abdilleh K, Asare A, Asare S, Venters S, Brown-Swigart L, Hirst GL, Wolf D, Yau C, van 't Veer LJ, Esserman L, Basu A. PRoBE the cloud toolkit: finding the best biomarkers of drug response within a breast cancer clinical trial. JAMIA Open. 2021 Apr; 4(2):ooab038.  View on PubMed
  9. Matthys MB, Dempsey AM, Melisko ME, Dreher N, Che ML, Van't Veer LJ, Esserman LJ, Basu A. Incorporation of Patient-Reported Outcomes Measurement Information System to assess quality of life among patients with breast cancer initiating care at an academic center. Cancer. 2021 07 01; 127(13):2342-2349.  View on PubMed
  10. Basu A, Philip EJ, Dewitt B, Hanmer J, Chattopadhyay A, Yau C, Melisko ME, Esserman LJ. The quality of life index: a pilot study integrating treatment efficacy and quality of life in oncology. NPJ Breast Cancer. 2020; 6:52.  View on PubMed
  11. Barnholtz-Sloan JS, Rollison DE, Basu A, Borowsky AD, Bui A, DiGiovanna J, Garcia-Closas M, Genkinger JM, Gerke T, Induni M, Lacey JV, Mirel L, Permuth JB, Saltz J, Shenkman EA, Ulrich CM, Zheng WJ, Nadaf S, Kibbe WA. Cancer Informatics for Cancer Centers (CI4CC): Building a Community Focused on Sharing Ideas and Best Practices to Improve Cancer Care and Patient Outcomes. JCO Clin Cancer Inform. 2020 02; 4:108-116.  View on PubMed
  12. Basu A, Warzel D, Eftekhari A, Kirby JS, Freymann J, Knable J, Sharma A, Jacobs P. Call for Data Standardization: Lessons Learned and Recommendations in an Imaging Study. JCO Clin Cancer Inform. 2019 11; 3:1-11.  View on PubMed
  13. Basu A, Mitra R, Liu H, Schreiber SL, Clemons PA. RWEN: response-weighted elastic net for prediction of chemosensitivity of cancer cell lines. Bioinformatics. 2018 10 01; 34(19):3332-3339.  View on PubMed
  14. Basu A, Bodycombe NE, Cheah JH, Price EV, Liu K, Schaefer GI, Ebright RY, Stewart ML, Ito D, Wang S, Bracha AL, Liefeld T, Wawer M, Gilbert JC, Wilson AJ, Stransky N, Kryukov GV, Dancik V, Barretina J, Garraway LA, Hon CS, Munoz B, Bittker JA, Stockwell BR, Khabele D, Stern AM, Clemons PA, Shamji AF, Schreiber SL. An interactive resource to identify cancer genetic and lineage dependencies targeted by small molecules. Cell. 2013 Aug 29; 154(5):1151-1161.  View on PubMed
  15. Mitchell L, Huard S, Cotrut M, Pourhanifeh-Lemeri R, Steunou AL, Hamza A, Lambert JP, Zhou H, Ning Z, Basu A, Côté J, Figeys DA, Baetz K. mChIP-KAT-MS, a method to map protein interactions and acetylation sites for lysine acetyltransferases. Proc Natl Acad Sci U S A. 2013 Apr 23; 110(17):E1641-50.  View on PubMed
  16. Basu A. Computational prediction of lysine acetylation proteome-wide. Methods Mol Biol. 2013; 981:127-36.  View on PubMed
  17. Basu A, Rose KL, Zhang J, Beavis RC, Ueberheide B, Garcia BA, Chait B, Zhao Y, Hunt DF, Segal E, Allis CD, Hake SB. Proteome-wide prediction of acetylation substrates. Proc Natl Acad Sci U S A. 2009 Aug 18; 106(33):13785-90.  View on PubMed
  18. Whitcomb SJ, Basu A, Allis CD, Bernstein E. Polycomb Group proteins: an evolutionary perspective. Trends Genet. 2007 Oct; 23(10):494-502.  View on PubMed

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