Resume-aware faculty matching

Find professors who actually fit you

Upload your resume. Four AI agents analyze your background, rank the faculty who fit, inspect their recent research, and help you draft outreach — grounded in their actual work, not templates.

Free to startNo credit cardCancel anytime
Top matches Balanced preset
Dr. Sarah Chen
Stanford · Interpretability · NLP
91
Dr. Marcus Holloway
MIT · Robotics · RL
84
Dr. Aisha Okonkwo
CMU · Fairness · HCI
82
Nova · Professor Researcher · re-ranking top 20…

Amanda Phipps

Verified

University of Washington · Epidemiology

Active 2005–2026

h-index67
Citations15.8k
Papers510264 last 5y
Funding$27.7M3 active
See your match with Amanda Phipps — sign in to PhdFit.Sign in

About

Amanda Phipps is an Associate Professor and Associate Chair in the Department of Epidemiology at the University of Washington's School of Public Health. She holds a PhD in Epidemiology from the University of Washington, an MPH in Epidemiology from the University of California, Berkeley, and a BA in Biological Sciences from Northwestern University. Her research interests encompass cancer epidemiology, molecular epidemiology, and clinical epidemiology. Her current projects focus on the relationship between modifiable lifestyle factors such as smoking and obesity and survival in individuals with biologically-distinct subtypes of colorectal cancer. She also investigates the impact of sleep and sleep disorders on cancer incidence and survival, as well as molecular subtypes of breast cancer, particularly the risk factors for the poor-prognosis triple-negative subtype of breast cancer.

Research signals

Five dimensions sourced from public faculty / publication signals. Sign in to compare against your own profile and see your match score.

Research topics

  • Genetics
  • Biology
  • Medicine
  • Computational biology
  • Endocrinology
  • Internal medicine
  • Bioinformatics
  • Oncology
  • Cancer research

Selected publications

  • Abstract 2867: Interaction between T-cell inflamed gene expression profile score and tumor-associated microbiome on colorectal cancer mortality in a heterogeneous patient population

    Cancer Research · 2026-04-03

    article

    Abstract Background: The microbiome and tumor immune response are important and inter-related components that are implicated in colorectal cancer (CRC) prognosis. However, associations between these components and potential joint effects on CRC mortality remain unclear. Methods: We included 366 participants with CRC (106 African American, 161 Alaska Native, 91 Hispanic, 8 non-Hispanic White) from the Translational Research Program in Cancer Differences across Populations (TRPCDP). 241 participants who did not die of CRC were matched to 125 participants who died of CRC during follow-up by age, sex, tumor site, tumor stage, year of diagnosis, and population group. We sequenced microbial DNA from the V4 region of the 16S rRNA bacterial gene and sequenced RNA using the Illumina TruSeq RNA Exome kit from formalin-fixed paraffin embedded (FFPE) tumor tissue. We calculated the T-cell inflamed gene expression profile (GEP) score as a weighted sum of log2-transformed transcripts per million of 18 genes: CCL5, CD27, CD274 (PD-L1), CD276 (B7-H3), CD8A, CMKLR1, CXCL9, CXCR6, HLA-DQA1, HLA-DRB1, HLA-E, IDO1, LAG3, NKG7, PDCD1LG2 (PDL2), PSMB10, STAT1, and TIGIT. We dichotomized the T-cell inflamed GEP score into high and low groups using the top tertile as a threshold. Using logistic regression, we estimated odds ratios (OR) and 95% confidence intervals (CI) for associations between bacterial presence and dichotomized T-cell inflamed GEP score, as well as interaction effects of bacteria and dichotomized T-cell inflamed GEP score on CRC-specific mortality, adjusting for matching factors. Results: Among 48 genera tested, Anaerococcus was associated with lower odds of high T-cell inflamed GEP score (OR=0.34, 95% CI 0.20-0.58) and Leptotrichia was associated with higher odds of high T-cell inflamed GEP score (OR=2.93, 95% CI 1.66-5.22). When combined, the joint effect of tumors being Leptotrichia positive and low T-cell inflamed GEP score was associated with over four times the odds of CRC mortality (OR=4.41, 95% CI 1.86-10.83) compared to tumors that were Leptotrichia negative and high T-cell inflamed GEP score. Conclusions: The joint effect of Leptotrichia presence and low T-cell inflamed GEP score resulted in markedly higher odds of CRC death. Understanding the influence of this immune-microbiota interaction may improve CRC prognostic stratification and enable the discovery of new treatment targets to improve CRC prognosis. Citation Format: Claire Elizabeth Thomas, Hang Yin, Jeroen Huyghe, Nicole Catalina Lorona, Scott D. Labrie, Keith R. Curtis, Orsalem Kahsai, Sosun Nayemi, Ningxin Ma, Timothy Randolph, Conghui Qu, Sushma Thomas, Li Hsu, Amanda L. Koehne, Heather Green-Mantrana, Marc Matrana, James J. Tiesinga, William M. Grady, Diana Redwood, Christopher I. Li, Li Li, Riki (Ulrike) Peters, Jane C. Figueiredo, Timothy K. Thomas, Amanda I. Phipps, Meredith A. Hullar. Interaction between T-cell inflamed gene expression profile score and tumor-associated microbiome on colorectal cancer mortality in a heterogeneous patient population [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2867.

  • Supplementary Figure S9 from T-cell Subset Features and Distributions Evolve across the Colorectal Precancer–Cancer Spectrum

    2026-01-08

    articleOpen access

    <p>Supplementary Figure S9. The combined T-cell status of precursor and carcinoma tissue categories in relation to anatomic location. (A-B) CD3+CD4+ and CD3+CD8+ T-cell densities in overall tissue regions stratified by anatomic location. (C-D) CD3+CD4+FOXP3+ and CD3+CD8+FOXP3+ T-cell densities in overall tissue regions stratified by anatomic location. P values were calculated with the Mann-Whitney U test (Wilcoxon rank-sum test) as compared to colorectal normal mucosa near precursor lesions (Normal mucosa) and carcinoma with proficient mismatch repair (pMMR). ***: P <0.0005, **: P <0.005, *: P <0.05. Abbreviations: CA, colorectal invasive carcinoma; dMMR, deficient mismatch repair; Non-serrated, non-serrated adenomas, Normal, colorectal normal mucosa near the precursor lesions; pMMR, proficient mismatch repair; Serrated without SSL, serrated lesions including hyperplastic polyp and traditional serrated adenoma; SSL, sessile serrated lesions.</p>

  • Supplementary Figure S5 from T-cell Subset Features and Distributions Evolve across the Colorectal Precancer–Cancer Spectrum

    2026-01-08

    articleOpen access

    <p>Supplementary Figure S5. Intraepithelial and lamina propria/stromal CD3+CD4+ and CD3+CD8+ T-cell densities were stratified by specimen types, which include colorectal normal mucosa, non-serrated adenomas, serrated lesions, invasive carcinoma, and normal mucosa near invasive carcinoma. CD3+CD4+ T-cell and CD3+CD8+ T-cell densities were stratified by T-cell differentiation status [CD45RA+CD45RO- (naive) and CD45RA-CD45RO+ (memory)], and functional status [FOXP3+ (regulatory), consisting of FOXP3+Low and FOXP3+High] in the intraepithelial (A-J) and lamina propria/stromal (K-T) tissue regions. P values were calculated with the Mann-Whitney U test (Wilcoxon rank-sum test) as compared to normal mucosa near precursor lesions (normal) and carcinoma. ***: P <0.0005, **: P <0.005, *: P <0.05. Abbreviations: Carcinoma, colorectal invasive carcinoma; N near CA, colorectal normal mucosa near carcinoma; Non-serrated, non-serrated adenomas, Normal, colorectal normal mucosa near precursor lesions; Serrated, serrated lesions.</p>

  • Supplementary Figure S3 from T-cell Subset Features and Distributions Evolve across the Colorectal Precancer–Cancer Spectrum

    2026-01-08

    articleOpen access

    <p>Supplementary Figure S3. Identification of distinct T-cell subsets via the combinational expression of T-cell markers (membrane CD3, membrane CD4, membrane CD8, membrane CD45RA, membrane CD45RO, nucleus FOXP3), cell cycle marker (nucleus MKI67), epithelial marker (cytoplasm KRT), and DNA marker (nucleus DAPI) at single-cell resolution. Scale bar: 2.5 (μm).</p>

  • Supplementary Figure S4 from T-cell Subset Features and Distributions Evolve across the Colorectal Precancer–Cancer Spectrum

    2026-01-08

    articleOpen access

    <p>Supplementary Figure S4. T-cell densities (/mm2) in the overall region (intraepithelial + lamina propria/stromal regions) based on the subcellular-localized CD3+ (total T-cell marker) fluorescence signals across 15 precursor and 10 carcinoma tissue microarray slides from the Health Professionals Follow-up Study, Nurses’ Health Study, and Nurses’ Health Study II.</p>

  • Associations of genetically predicted interleukin-6 and tumor necrosis factor signaling pathways with mortality among persons with colorectal cancer: a two-sample Mendelian randomization

    BMC Medicine · 2026-03-06

    articleOpen access

    BACKGROUND: Despite significant progress in identifying risk factors for colorectal cancer (CRC), factors influencing survival in people with CRC remain less understood. Pro-inflammatory cytokines like interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α) have been implicated in cancer progression and may influence CRC outcomes. We investigated associations between genetically predicted levels of IL-6 and TNF-α signaling pathways and mortality in people with CRC. METHODS: We conducted a two-sample Mendelian randomization (MR) analysis using cis-acting single nucleotide polymorphisms (SNPs) associated with soluble IL-6 receptor alpha (sIL6-RA) and IL-6 signal transducer gp130 (IL6ST), representing IL-6 signaling, and with TNF-α, and its soluble receptors (sTNF-R1, sTNF-R2). SNPs were obtained separately from two large genome-wide association studies (GWAS): deCODE and UK Biobank (UKB). The outcome was CRC-specific mortality among 16,964 CRC cases (4010 deaths) in the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). Analyses were stratified by tumor site and stage. The inverse variance weighted (IVW) method, incorporating a correlation matrix for dependent SNPs, was used for primary analyses. Because literature links TNF-α to CRC incidence, we additionally performed a simulation study to evaluate the potential impact of collider bias resulting from restricting analyses to CRC cases. RESULTS: Genetically predicted sIL6-RA was weakly positively associated with CRC-specific mortality (deCODE-SNPs (n = 13) HR per 1 SD increase: 1.06; 95% CI: 1.00-1.12; UKB-SNPs (n = 11) HR: 1.09; 95% CI: 1.02-1.17). Genetically proxied IL6ST levels showed no association with CRC-specific mortality in the overall sample (deCODE-SNPs (n = 19) HR: 1.04; 95% CI: 0.90-1.21; UKB-SNPs (n = 9) HR: 1.11; 95% CI: 0.87-2.42), while higher IL6ST levels were associated with increased mortality among patients with stage 2/3 disease (deCODE-SNPs (n = 19) HR: 1.45; 95% CI: 1.10-1.91; UKB-SNPs (n = 9) HR: 1.87; 95% CI: 1.22-2.89). No associations were observed for TNF-α, sTNF-R1, or sTNF-R2. Findings for all exposures were consistent across both GWAS datasets. Simulation analyses for TNF-α indicated collider bias was present but limited in magnitude. CONCLUSIONS: Our findings suggest that IL-6 signaling may play a role in CRC progression although of limited magnitude, whereas TNF-related pathways appear less relevant for prognosis.

  • P-2151. Incidence of Breakthrough HSV in Adult Allogeneic Hematopoietic Cell Transplant Recipients on Standardized Antiviral Prophylaxis

    Open Forum Infectious Diseases · 2026-01-01

    articleOpen access

    Abstract Background Reactivations of herpes simplex viruses (HSV) can occur in the early post-allogeneic hematopoietic cell transplant (aHCT) period despite universal antiviral prophylaxis. Few studies have assessed HSV recurrence in the era of standardized antiviral prophylaxis, in which val/acyclovir is recommended for up to 1 year post aHCT. We evaluated the incidence and management of HSV during the first 100 days post-HCT over two decades.Figure 1:Time from transplant to first positive HSV test and development of symptoms Methods All first aHCT recipients at Fred Hutchinson Cancer Center between 2002-2022 were reviewed to determine the incidence of HSV within the first 100 days on prophylaxis (acyclovir 800 mg or valacyclovir 500 mg twice daily). HSV cases were identified via viral culture, polymerase chain reaction, and/or direct fluorescent antibody testing, and clinical records were reviewed for symptoms, clinical outcomes, use of prophylaxis, and treatment regimens. Resistance was categorized as clinical (presumptive) or virologically-confirmed by the University of Washington Virology laboratory. Results We reviewed data from 4,358 aHCT recipients aged ≥18 years, among whom 3,749 (86%) were HSV seropositive and 30 developed HSV recurrence (cumulative incidence = 0.8%). Most (n = 22) reactivations were HSV-1 and 8 were HSV-2; 2 were unspecified. The median time from transplant to first positive test was 35 days (IQR: 20-65 days) (Figure 1). HSV was detected at multiple anatomic sites; oral recurrences were most common. In total, 14/30 (46.7%) patients developed acyclovir-resistant HSV (8 virologically-confirmed, 6 clinical). Treatment duration was significantly longer for patients with resistant (median 38 days [IQR: 26-41]) compared to susceptible infections (20 days [IQR: 16-27]; p = 0.03). Few patients (n = 4) had events attributed to non-adherence/malabsorption. Conclusion Clinical HSV disease is rare among aHCT patients on prophylaxis in the first 100 days. Development of acyclovir resistance is uncommon but represented almost half of breakthrough cases. Our findings highlight the importance and effectiveness of universal val/acyclovir prophylaxis in the early post-transplant period. Disclosures Christine Johnston, MD, MPH, AiCuris: Advisor/Consultant|Assembly Biosciences: Advisor/Consultant|GlaxoSmithKline: Advisor/Consultant|GlaxoSmithKline: Grant/Research Support|Moderna: Grant/Research Support|Pfizer: Advisor/Consultant Michael J. Boeckh, MD PhD, Allovir: Advisor/Consultant|Ansun Biopharma: Grant/Research Support|AstraZeneka: Advisor/Consultant|AstraZeneka: Grant/Research Support|GSK: Grant/Research Support|Merck: Advisor/Consultant|Merck: Grant/Research Support|Moderna: Advisor/Consultant|Moderna: Grant/Research Support|Symbio: Advisor/Consultant|Vir Biotechnology: Grant/Research Support Denise McCulloch, MD, MPH, Pfizer: Grant/Research Support Steven A. Pergam, MD, MPH, F2G: Site PI for clinical trial|Global Life Technologies, Inc.: Grant/Research Support|Mundipharma: Site PI for clinical trial|Symbio: Site PI for clinical trial

  • Supplementary Figure S2 from T-cell Subset Features and Distributions Evolve across the Colorectal Precancer–Cancer Spectrum

    2026-01-08

    articleOpen access

    <p>Supplementary Figure S2. Protocol for multiplex immunofluorescence staining for T cells and epithelial cells. Steps 1-4 were manually conducted. Steps 5-9 were performed with a Leica Bond RX Research Stainer (Leica Biosystems, Buffalo, Illinois, U.S.), regarding the condition of primary antibodies and fluorescence dyes (see the Supplementary Table S2). A. Deparaffinization in xylene (Fisher Chemical, Hampton, New Hampshire, U.S.) and rehydration through a graded dehydrated ethyl alcohol series (100% x3 + 95% x1 + 80% x1 + diluted water x5). B. Antigen retrieval with 2100-Retriever (62700-10, Electron Microscopy Science, Hatfield, Pennsylvania, U.S.) in ethylenediaminetetraacetic acid (EDTA) buffer pH 9.0 (S2367, Dako, Copenhagen, Denmark). C. Opal Antibody Diluent/Block (ARD1001EA, Akoya Biosciences, Marlborough, Massachusetts, U.S.). D. Opal polymer HRP Mouse + Rabbit (ARH1001EA, Akoya Biosciences). E. BOND epitope retrieval solution 1&2 (Leica Biosystems). F. Spectral DAPI (FP1490, Akoya Biosciences, Marlborough, Massachusetts, U.S.). G. Cover slips 24x50 mm No.1 thickness (12450S, Epredia, Portsmouth, New Hampshire, U.S.), prolong gold antifade reagent (P36930, Life Technologies Corporation, Eugene, Oregon, U.S.). Research Resource Identifiers (RRIDs) for primary antibodies were listed at Supplementary Table S2, but RRIDs for Opal dyes, staining solutions, and Akoya Biosciences instrumentation had not been assigned.</p>

  • Supplementary Figure S8 from T-cell Subset Features and Distributions Evolve across the Colorectal Precancer–Cancer Spectrum

    2026-01-08

    articleOpen access

    <p>Supplementary Figure S8. The combined T-cell status of precursor tissue categories in relation to lesion size, age of resection, and anatomic location. (A-D) CD3+CD4+ and CD3+CD8+ T-cells’ densities stratified by precursor lesions’ size, which includes small (lesion size: <5 mm), medium (5-9 mm), and large (≥10 mm) in non-serrated and serrated lesions. (E-H) CD3+CD4+ and CD3+CD8+ T-cells’ densities stratified by age of resection, which includes early-onset (age <50 years), intermediate-onset (age 50-54 years), and later-onset (age 55-69 and ≥70 years). P values were calculated with the Mann-Whitney U test (Wilcoxon rank-sum test) as compared to each adenoma category in (A-D) and colorectal normal mucosa near precursor lesions (Normal mucosa) in (E-H). ***: P <0.0005, **: P <0.005, *: P <0.05. Abbreviations: Non-serrated, non-serrated adenomas, Normal, colorectal normal mucosa near precursor lesions; Serrated, serrated lesions.</p>

  • Data from T-cell Subset Features and Distributions Evolve across the Colorectal Precancer–Cancer Spectrum

    2026-01-08

    articleOpen access

    <div>Abstract<p>The immune microenvironment is a crucial component of colorectal carcinoma that has been well characterized, but much less is known about the immune microenvironment of colorectal carcinoma precursors. We hypothesized that T-cell infiltrates might differ across the colorectal neoplastic spectrum. We leveraged the prospective cohort incident-tumor biobank method, which provided formalin-fixed, paraffin-embedded tumor tissue specimens (<i>N</i> = 1,825) from 790 colorectal carcinoma precursors (including hyperplastic polyps, sessile serrated adenomas, traditional serrated adenomas, tubular adenomas, tubulovillous adenomas, and villous adenomas) and 1,035 colorectal carcinomas. We performed an <i>in situ</i> multispectral immunofluorescence assay for CD3, CD4, CD8, FOXP3 (negative, low, or high expression), PTPRC (CD45RO and CD45RA), MKI67 (Ki-67), and KRT (keratin) combined with supervised machine learning. CD3<sup>+</sup>CD4<sup>+</sup> cells were more abundant than CD3<sup>+</sup>CD8<sup>+</sup> cells in most precursors. In conventional adenomas, greater villous component correlated with fewer intraepithelial CD3<sup>+</sup>CD8<sup>+</sup> cells. Serrated lesions, including hyperplastic polyps and sessile serrated lesions, exhibited higher densities of intraepithelial CD3<sup>+</sup>CD8<sup>+</sup> cells compared with other precursors and carcinomas. Age strata of patients with precursors (including early-onset precursors) were not associated with differential T-cell infiltration patterns. Compared with invasive colorectal carcinoma, precursors generally showed higher densities of CD3<sup>+</sup>CD4<sup>+</sup> cells and CD3<sup>+</sup>CD8<sup>+</sup> cells with phenotypes of naive (CD45RA<sup>+</sup>CD45RO<sup>−</sup>), memory (CD45RA<sup>−</sup>CD45RO<sup>+</sup>), and regulatory (FOXP3<sup>+Low</sup> and FOXP3<sup>+High</sup>) in intraepithelial and lamina propria/stromal regions. In conclusion, T-cell infiltration patterns vary across different histopathologic types of the colorectal neoplastic spectrum from precursors to invasive carcinomas. Our findings shed light on how the tumor-immune microenvironment evolves during precursor development and progression to colorectal carcinoma.</p></div>

Recent grants

Frequent coauthors

  • Polly A. Newcomb

    Fred Hutch Cancer Center

    484 shared
  • Ulrike Peters

    351 shared
  • Andrew T. Chan

    Brigham and Women's Hospital

    344 shared
  • Daniel D. Buchanan

    337 shared
  • Thomas E. Rohan

    Thomas Jefferson University

    328 shared
  • Jean Wactawski‐Wende

    279 shared
  • Dorothy S. Lane

    Stony Brook School

    263 shared
  • Ross L. Prentice

    263 shared
  • Resume-aware match score
  • Save to shortlist
  • AI-drafted outreach

See your match with Amanda Phipps

PhdFit ranks faculty by your research interests, methods, and publications — grounded in their actual work, not templates.

  • Free to start
  • No credit card
  • 30-second signup