Aditi Hazra

Dr. Aditi Hazra

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Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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22 February 2019 in Breast Cancer Research
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KKKevin H. Kensler
Kevin H. Kensler
MRMeredith M. Regan
Meredith M. Regan
YHYujing J. Heng
Yujing J. Heng
GBGabrielle M. Baker
Gabrielle M. Baker
MPMichael E. Pyle
Michael E. Pyle
RTRulla M. Tamimi
Rulla M. Tamimi
The androgen receptor (AR) is an emerging prognostic marker and therapeutic target in breast cancer. AR is expressed in 60–80% of breast cancers, with higher prevalence among estrogen receptor-positive (ER+) tumors. Androgen treatment inhibits ER signaling in ER+/AR+ breast cancer cell lines, and AR expression is associated with improved survival for this subtype in epidemiologic studies. However, whether AR expression modifies the efficacy of selective ER modulators or aromatase inhibitors for ER+ cancers remains unclear. We evaluated the prognostic and predictive value of AR expression among 3021 postmenopausal ER+ breast cancer patients in the Breast International Group (BIG) trial 1–98. The BIG 1–98 study was a four-armed, double-blind, phase III randomized clinical trial that compared 5 years of tamoxifen or letrozole monotherapy, or sequences of 2 years and 3 years treatment with one drug and then the other. AR expression was measured by immunohistochemistry and the percentage of AR-positive nuclei was quantified. The association between AR expression and prognosis was evaluated using Cox proportional hazards models. Continuous AR-by-treatment interactions were assessed using Subpopulation Treatment Effect Pattern Plots (STEPP). Eighty-two percent of patients had AR+ (≥ 1%) tumors. Patients with AR+ cancers were more likely to have smaller, lower-grade tumors, with higher expression of ER and PR. AR expression was not associated with breast cancer-free interval (BCFI) (415 events) over a median 8.0 years of follow-up (p = 0.12, log-rank test). In multivariable-adjusted models, AR expression was not associated with BCFI (HR = 1.07, 95% CI 0.83–1.36, p = 0.60). The letrozole versus tamoxifen monotherapy treatment effect did not significantly differ for AR+ tumors (HR = 0.63, 95% CI 0.44–0.75, p = 0.003) and AR− tumors (HR = 0.39, 95% CI 0.21–0.72, p = 0.002) (p-heterogeneity = 0.16). STEPP analysis also suggested no heterogeneity of the treatment effect across the continuum of AR expression. AR expression was not associated with prognosis, nor was there heterogeneity of the letrozole versus tamoxifen treatment effect by AR expression. These findings suggest that AR expression may not be an informative biomarker for the selection of adjuvant endocrine therapy for postmenopausal women with ER+ breast cancers. ClinicalTrials.gov , NCT00004205, Registered 27 January 2003—Retrospectively registered, https://clinicaltrials.gov/ct2/show/study/NCT00004205 .

8 August 2017 in Breast Cancer Research and Treatment
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MHMegan Healey
Megan Healey
Kelly A. HirkoKelly A. Hirko
Kelly A. Hirko
ABAndrew H. Beck
Andrew H. Beck
LCLaura C. Collins
Laura C. Collins
SSStuart J. Schnitt
Stuart J. Schnitt
AHAditi Hazra
Aditi Hazra

12 September 2017 in Breast Cancer Research
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Journal Article
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JWJun Wang
Jun Wang
YHYujing J. Heng
Yujing J. Heng
HEHeather Eliassen
Heather Eliassen
RTRulla M. Tamimi
Rulla M. Tamimi
AHAditi Hazra
Aditi Hazra
SHSusan E. Hankinson
Susan E. Hankinson
Alcohol consumption is an established risk factor for breast cancer and the association generally appears stronger among estrogen receptor (ER)-positive tumors. However, the biological mechanisms underlying this association are not completely understood. We analyzed messenger RNA (mRNA) microarray data from both invasive breast tumors (N = 602) and tumor-adjacent normal tissues (N = 508) from participants diagnosed with breast cancer in the Nurses’ Health Study (NHS) and NHSII. Multivariable linear regression, controlling for other known breast cancer risk factors, was used to identify differentially expressed genes by pre-diagnostic alcohol intake. For pathway analysis, we performed gene set enrichment analysis (GSEA). Differentially expressed genes or enriched pathway-defined gene sets with false discovery rate (FDR) <0.1 identified in tumors were validated in RNA sequencing data of invasive breast tumors (N = 166) from The Cancer Genome Atlas. No individual genes were significantly differentially expressed by alcohol consumption in the NHS/NHSII. However, GSEA identified 33 and 68 pathway-defined gene sets at FDR <0.1 among 471 ER+ and 127 ER- tumors, respectively, all of which were validated. Among ER+ tumors, consuming 10+ grams of alcohol per day (vs. 0) was associated with upregulation in RNA metabolism and transport, cell cycle regulation, and DNA repair, and downregulation in lipid metabolism. Among ER- tumors, in addition to upregulation in RNA processing and cell cycle, alcohol intake was linked to overexpression of genes involved in cytokine signaling, including interferon and transforming growth factor (TGF)-β signaling pathways, and translation and post-translational modifications. Lower lipid metabolism was observed in both ER+ tumors and ER+ tumor-adjacent normal samples. Most of the significantly enriched gene sets identified in ER- tumors showed a similar enrichment pattern among ER- tumor-adjacent normal tissues. Our data suggest that moderate alcohol consumption (i.e. 10+ grams/day, equivalent to one or more drinks/day) is associated with several specific and reproducible biological processes and pathways, which adds potential new insight into alcohol-related breast carcinogenesis.

31 May 2017 in Cancer Epidemiology, Biomarkers & Prevention
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RTReka Toth
Reka Toth
Dominique SchererDominique Scherer
Dominique Scherer
LKLinda E. Kelemen
Linda E. Kelemen
ARAngela Risch
Angela Risch
AHAditi Hazra
Aditi Hazra
CUCornelia Ulrich
Cornelia Ulrich
Background: Epigenetic disturbances are crucial in cancer initiation, potentially with pleiotropic effects, and may be influenced by the genetic background. Methods: In a subsets (ASSET) meta-analytic approach, we investigated associations of genetic variants related to epigenetic mechanisms with risks of breast, lung, colorectal, ovarian and prostate carcinomas using 51,724 cases and 52,001 controls. False discovery rate–corrected P values (q values < 0.05) were considered statistically significant. Results: Among 162,887 imputed or genotyped variants in 555 candidate genes, SNPs in eight genes were associated with risk of more than one cancer type. For example, variants in BABAM1 were confirmed as a susceptibility locus for squamous cell lung, overall breast, estrogen receptor (ER)–negative breast, and overall prostate, and overall serous ovarian cancer; the most significant variant was rs4808076 [OR = 1.14; 95% confidence interval (CI) = 1.10–1.19; q = 6.87 × 10−5]. DPF1 rs12611084 was inversely associated with ER-negative breast, endometrioid ovarian, and overall and aggressive prostate cancer risk (OR = 0.93; 95% CI = 0.91–0.96; q = 0.005). Variants in L3MBTL3 were associated with colorectal, overall breast, ER-negative breast, clear cell ovarian, and overall and aggressive prostate cancer risk (e.g., rs9388766: OR = 1.06; 95% CI = 1.03–1.08; q = 0.02). Variants in TET2 were significantly associated with overall breast, overall prostate, overall ovarian, and endometrioid ovarian cancer risk, with rs62331150 showing bidirectional effects. Analyses of subpathways did not reveal gene subsets that contributed disproportionately to susceptibility. Conclusions: Functional and correlative studies are now needed to elucidate the potential links between germline genotype, epigenetic function, and cancer etiology. Impact: This approach provides novel insight into possible pleiotropic effects of genes involved in epigenetic processes. Cancer Epidemiol Biomarkers Prev; 26(6); 816–25. ©2017 AACR.

2 February 2017 in PLOS ONE
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AQAlejandro Quiroz-Zárate
Alejandro Quiroz-Zárate
BHBenjamin J. Harshfield
Benjamin J. Harshfield
RHRong Hu
Rong Hu
NKNick Knoblauch
Nick Knoblauch
ABAndrew H. Beck
Andrew H. Beck
AHAditi Hazra
Aditi Hazra
We investigate 71 single nucleotide polymorphisms (SNPs) identified in meta-analytic studies of genome-wide association studies (GWAS) of breast cancer, the majority of which are located in intergenic or intronic regions. To explore regulatory impacts of these variants we conducted expression quantitative loci (eQTL) analyses on tissue samples from 376 invasive postmenopausal breast cancer cases in the Nurses’ Health Study (NHS) diagnosed from 1990–2004. Expression analysis was conducted on all formalin-fixed paraffin-embedded (FFPE) tissue samples (and on 264 adjacent normal samples) using the Affymetrix Human Transcriptome Array. Significance and ranking of associations between tumor receptor status and expression variation was preserved between NHS FFPE and TCGA fresh-frozen sample sets (Spearman r = 0.85, p<10^-10 for 17 of the 21 Oncotype DX recurrence signature genes). At an FDR threshold of 10%, we identified 27 trans-eQTLs associated with expression variation in 217 distinct genes. SNP-gene associations can be explored using an open-source interactive browser distributed in a Bioconductor package. Using a new a procedure for testing hypotheses relating SNP content to expression patterns in gene sets, defined as molecular function pathways, we find that loci on 6q14 and 6q25 affect various gene sets and molecular pathways (FDR < 10%). Although the ultimate biological interpretation of the GWAS-identified variants remains to be uncovered, this study validates the utility of expression analysis of this FFPE expression set for more detailed integrative analyses.

4 April 2023 in Cells
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AHAditi Hazra
Aditi Hazra
AOAndrea O’hara
Andrea O’hara
KPKornelia Polyak
Kornelia Polyak
FNFaina Nakhlis
Faina Nakhlis
BHBeth T. Harrison
Beth T. Harrison
FLFilipa Lynce
Filipa Lynce
Identification of a unique genomic biomarker in de novo inflammatory breast cancer (IBC) may provide an insight into the biology of this aggressive disease. The goal of our study was to elucidate biomarkers associated with IBC. We examined breast biopsies collected from Dana–Farber Cancer Institute patients with IBC prior to initiating preoperative systemic treatment (30 samples were examined, of which 14 were eligible). Patients without available biopsies (n = 1), with insufficient tumor epithelial cells (n = 10), or insufficient DNA yield (n = 5) were excluded from the analysis. Molecular subtype and tumor grade were abstracted from a medical records’ review. Ten IBC tumors were estrogen-receptor-positive (ER+) and human epidermal growth factor receptor 2 (HER2)-negative (n = 10 out of 14). Sufficient RNA and DNA were simultaneously extracted from 14 biopsy specimens using the Qiagen AllPrep Kit. RNA was amplified using the Sensation kit and profiled using the Affymetrix Human Transcriptome Array 2.0. DNA was profiled for genome-wide copy number variation (CNV) using the Affymetrix OncoScan Array and analyzed using the Nexus Chromosome Analysis Suite. Among the 14 eligible samples, we first confirmed biological concordance and quality control metrics using replicates and gene expression data. Second, we examined CNVs and gene expression change by IBC subtype. We identified significant CNVs in IBC patients after adjusting for multiple comparisons. Next, to assess whether the CNVs were unique to IBC, we compared the IBC CNV data to fresh-frozen non-IBC CNV data from The Cancer Genome Atlas (n = 388). On chromosome 7p11.2, we identified significant CN gain located at position 58,019,983-58,025,423 in 8 ER+ IBC samples compared to 338 non-IBC ER+ samples (region length: 5440 bp gain and 69,039 bp, False Discovery Rate (FDR) p-value = 3.12 × 10−10) and at position 57,950,944–58,025,423 in 3 TN-IBC samples compared to 50 non-IBC TN samples (74,479 base pair, gain, FDR p-value = 4.27 × 10−5; near the EGFR gene). We also observed significant CN loss on chromosome 21, located at position 9,648,315–9,764,385 (p-value = 4.27 × 10−5). Secondarily, differential gene expression in IBC patients with 7p11.2 CN gain compared to SUM149 were explored after FDR correction for multiple testing (p-value = 0.0016), but the results should be interpreted with caution due to the small sample size. Finally, the data presented are hypothesis-generating. Validation of CNVs that contribute to the unique presentation and biological features associated with IBC in larger datasets may lead to the optimization of treatment strategies.