ORCID Profile
0000-0002-2104-5457
Current Organisations
Dana Farber Cancer Institute
,
Brigham and Women's Hospital
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22512700
Abstract: CRISPR-Cas9 screen data
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22512712
Abstract: ORF overexpression screen enrichment analysis
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22512715
Abstract: ORF overexpression screen data
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22512691.V1
Abstract: Supplementary detailed methods
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.C.6540319
Abstract: Abstract High-grade serous ovarian cancer (HGSOC) is often sensitive to initial treatment with platinum and taxane combination chemotherapy, but most patients relapse with chemotherapy-resistant disease. To systematically identify genes modulating chemotherapy response, we performed pooled functional genomic screens in HGSOC cell lines treated with cisplatin, paclitaxel, or cisplatin plus paclitaxel. Genes in the intrinsic pathway of apoptosis were among the top candidate resistance genes in both gain-of-function and loss-of-function screens. In an open reading frame overexpression screen, followed by a mini-pool secondary screen, anti-apoptotic genes including i BCL2L1 /i (BCL-XL) and i BCL2L2 /i (BCL-W) were associated with chemotherapy resistance. In a CRISPR-Cas9 knockout screen, loss of i BCL2L1 /i decreased cell survival whereas loss of proapoptotic genes promoted resistance. To dissect the role of in idual anti-apoptotic proteins in HGSOC chemotherapy response, we evaluated overexpression or inhibition of BCL-2, BCL-XL, BCL-W, and MCL1 in HGSOC cell lines. Overexpression of anti-apoptotic proteins decreased apoptosis and modestly increased cell viability upon cisplatin or paclitaxel treatment. Conversely, specific inhibitors of BCL-XL, MCL1, or BCL-XL/BCL-2, but not BCL-2 alone, enhanced cell death when combined with cisplatin or paclitaxel. Anti-apoptotic protein inhibitors also sensitized HGSOC cells to the poly (ADP-ribose) polymerase inhibitor olaparib. These unbiased screens highlight anti-apoptotic proteins as mediators of chemotherapy resistance in HGSOC, and support inhibition of BCL-XL and MCL1, alone or combined with chemotherapy or targeted agents, in treatment of primary and recurrent HGSOC. Implications: Anti-apoptotic proteins modulate drug resistance in ovarian cancer, and inhibitors of BCL-XL or MCL1 promote cell death in combination with chemotherapy. /
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22512709
Abstract: ORF constructs in secondary mini-pool overexpression screen
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22512706
Abstract: Secondary mini-pool overexpression screen data
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22512700.V1
Abstract: CRISPR-Cas9 screen data
Publisher: American Association for Cancer Research (AACR)
Date: 2021
DOI: 10.1158/2326-6066.CIR-20-0527
Abstract: Macrophages are among the most common cells in the colorectal cancer microenvironment, but their prognostic significance is incompletely understood. Using multiplexed immunofluorescence for CD68, CD86, IRF5, MAF, MRC1 (CD206), and KRT (cytokeratins) combined with digital image analysis and machine learning, we assessed the polarization spectrum of tumor-associated macrophages in 931 colorectal carcinomas. We then applied Cox proportional hazards regression to assess prognostic survival associations of intraepithelial and stromal densities of M1-like and M2-like macrophages while controlling for potential confounders, including stage and microsatellite instability status. We found that high tumor stromal density of M2-like macrophages was associated with worse cancer-specific survival, whereas tumor stromal density of M1-like macrophages was not significantly associated with better cancer-specific survival. High M1:M2 density ratio in tumor stroma was associated with better cancer-specific survival. Overall macrophage densities in tumor intraepithelial or stromal regions were not prognostic. These findings suggested that macrophage polarization state, rather than their overall density, was associated with cancer-specific survival, with M1- and M2-like macrophage phenotypes exhibiting distinct prognostic roles. These results highlight the utility of a multimarker strategy to assess the macrophage polarization at single-cell resolution within the tumor microenvironment.
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22512706.V1
Abstract: Secondary mini-pool overexpression screen data
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22512709.V1
Abstract: ORF constructs in secondary mini-pool overexpression screen
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22512697.V1
Abstract: CRISPR-Cas9 screen enrichment analysis
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22512694.V1
Abstract: Figure S1A. Cisplatin and paclitaxel sensitivity in ovarian cancer cell lines Figure S1B. Cell line growth curves in ORF screen Figure S1C. Candidate resistance genes scoring in {greater than or equal to}2 conditions in primary ORF screen Figure S2A. Expression of MDR1, encoded by ABCB1 Figure S2B. Overexpression of ABCB1 and paclitaxel response Figure S2C. Overexpression of ABCB1 and paclitaxel response in HGSOC cell lines Figure S2D. Effect of ABCB1 overexpression on cell growth with paclitaxel treatment Figure S2E. Effect of MDR1/P-glycoprotein inhibitor elacridar on paclitaxel response Figure S2F. Overexpression of ABCB1 and colony formation with paclitaxel treatment and effect of elacridar on colony formation Figure S3A. Cell line growth curves in mini-pool overexpression secondary screen Figure S3B. Mini-pool overexpression secondary screen Figure S3C. Top-ranked genes by LFC in mini-pool overexpression secondary screen Figure S4A. Cell line growth curves in CRISPR-Cas9 screen Figure S4B. CRISPR-Cas9 screen data from cisplatin+paclitaxel "low-dose" combination Figure S5A. Expression of BCL-XL and BCL-W Figure S5B. Overexpression of BCL2L1 (BCL-XL) or BCL2L2 (BCL-W) and paclitaxel response in HGSOC cell lines Figure S5C. Effect of overexpressing anti-apoptotic proteins on apoptotic priming Figure S5D. Expression of BCL-2 and MCL1 Figure S5E. Overexpression of BCL2 or MCL1 and apoptosis induction Figure S5F. Overexpression of BCL2 or MCL1 and paclitaxel or cisplatin response Figure S6. Cell cycle analysis of HGSOC cells overexpressing anti-apoptotic proteins Figure S7A. Genomic alterations in anti-apoptotic genes in primary ovarian cancer Figure S7B. Copy-number alterations of anti-apoptotic genes in primary HGSOC Figure S7C. Copy-number alterations of pro-apoptotic genes in primary HGSOC Figure S7D. Copy number and expression of anti-apoptotic genes in primary HGSOC Figure S7E. MCL1 and BCL2L1 are focally lified in HGSOC Figure S7F. Progression-free interval of patients with primary HGSOC with focal lifications of BCL2L1 or MCL1 Figure S8A. Copy number alterations of anti-apoptotic genes in ovarian cancer cell lines Figure S8B. Expression of anti-apoptotic genes in ovarian cancer cell lines Figure S9A. Expression of anti-apoptotic genes in platinum-sensitive and -resistant HGSOC Figure S9B. Expression of anti-apoptotic genes in paired platinum-sensitive and- resistant HGSOC Figure S10A. Effects of single-agent anti-apoptotic protein inhibitors on ovarian cancer cell lines Figure S10B. BH3 profiling of HGSOC cell lines with a panel of pro-apoptotic peptides
Publisher: American Association for Cancer Research (AACR)
Date: 11-2019
DOI: 10.1158/1541-7786.MCR-18-1243
Abstract: Anti-apoptotic proteins modulate drug resistance in ovarian cancer, and inhibitors of BCL-XL or MCL1 promote cell death in combination with chemotherapy.
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.C.6540319.V1
Abstract: Abstract High-grade serous ovarian cancer (HGSOC) is often sensitive to initial treatment with platinum and taxane combination chemotherapy, but most patients relapse with chemotherapy-resistant disease. To systematically identify genes modulating chemotherapy response, we performed pooled functional genomic screens in HGSOC cell lines treated with cisplatin, paclitaxel, or cisplatin plus paclitaxel. Genes in the intrinsic pathway of apoptosis were among the top candidate resistance genes in both gain-of-function and loss-of-function screens. In an open reading frame overexpression screen, followed by a mini-pool secondary screen, anti-apoptotic genes including i BCL2L1 /i (BCL-XL) and i BCL2L2 /i (BCL-W) were associated with chemotherapy resistance. In a CRISPR-Cas9 knockout screen, loss of i BCL2L1 /i decreased cell survival whereas loss of proapoptotic genes promoted resistance. To dissect the role of in idual anti-apoptotic proteins in HGSOC chemotherapy response, we evaluated overexpression or inhibition of BCL-2, BCL-XL, BCL-W, and MCL1 in HGSOC cell lines. Overexpression of anti-apoptotic proteins decreased apoptosis and modestly increased cell viability upon cisplatin or paclitaxel treatment. Conversely, specific inhibitors of BCL-XL, MCL1, or BCL-XL/BCL-2, but not BCL-2 alone, enhanced cell death when combined with cisplatin or paclitaxel. Anti-apoptotic protein inhibitors also sensitized HGSOC cells to the poly (ADP-ribose) polymerase inhibitor olaparib. These unbiased screens highlight anti-apoptotic proteins as mediators of chemotherapy resistance in HGSOC, and support inhibition of BCL-XL and MCL1, alone or combined with chemotherapy or targeted agents, in treatment of primary and recurrent HGSOC. Implications: Anti-apoptotic proteins modulate drug resistance in ovarian cancer, and inhibitors of BCL-XL or MCL1 promote cell death in combination with chemotherapy. /
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22512691
Abstract: Supplementary detailed methods
Publisher: MDPI AG
Date: 04-09-2021
Abstract: Breast cancer is a heterogenous disease with variability in tumor cells and in the surrounding tumor microenvironment (TME). Understanding the molecular ersity in breast cancer is critical for improving prediction of therapeutic response and prognostication. High-plex spatial profiling of tumors enables characterization of heterogeneity in the breast TME, which can holistically illuminate the biology of tumor growth, dissemination and, ultimately, response to therapy. The GeoMx Digital Spatial Profiler (DSP) enables researchers to spatially resolve and quantify proteins and RNA transcripts from tissue sections. The platform is compatible with both formalin-fixed paraffin-embedded and frozen tissues. RNA profiling was developed at the whole transcriptome level for human and mouse s les and protein profiling of 100-plex for human s les. Tissue can be optically segmented for analysis of regions of interest or cell populations to study biology-directed tissue characterization. The GeoMx Breast Cancer Consortium (GBCC) is composed of breast cancer researchers who are developing innovative approaches for spatial profiling to accelerate biomarker discovery. Here, the GBCC presents best practices for GeoMx profiling to promote the collection of high-quality data, optimization of data analysis and integration of datasets to advance collaboration and meta-analyses. Although the capabilities of the platform are presented in the context of breast cancer research, they can be generalized to a variety of other tumor types that are characterized by high heterogeneity.
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22512712.V1
Abstract: ORF overexpression screen enrichment analysis
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22512697
Abstract: CRISPR-Cas9 screen enrichment analysis
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22512694
Abstract: Figure S1A. Cisplatin and paclitaxel sensitivity in ovarian cancer cell lines Figure S1B. Cell line growth curves in ORF screen Figure S1C. Candidate resistance genes scoring in {greater than or equal to}2 conditions in primary ORF screen Figure S2A. Expression of MDR1, encoded by ABCB1 Figure S2B. Overexpression of ABCB1 and paclitaxel response Figure S2C. Overexpression of ABCB1 and paclitaxel response in HGSOC cell lines Figure S2D. Effect of ABCB1 overexpression on cell growth with paclitaxel treatment Figure S2E. Effect of MDR1/P-glycoprotein inhibitor elacridar on paclitaxel response Figure S2F. Overexpression of ABCB1 and colony formation with paclitaxel treatment and effect of elacridar on colony formation Figure S3A. Cell line growth curves in mini-pool overexpression secondary screen Figure S3B. Mini-pool overexpression secondary screen Figure S3C. Top-ranked genes by LFC in mini-pool overexpression secondary screen Figure S4A. Cell line growth curves in CRISPR-Cas9 screen Figure S4B. CRISPR-Cas9 screen data from cisplatin+paclitaxel "low-dose" combination Figure S5A. Expression of BCL-XL and BCL-W Figure S5B. Overexpression of BCL2L1 (BCL-XL) or BCL2L2 (BCL-W) and paclitaxel response in HGSOC cell lines Figure S5C. Effect of overexpressing anti-apoptotic proteins on apoptotic priming Figure S5D. Expression of BCL-2 and MCL1 Figure S5E. Overexpression of BCL2 or MCL1 and apoptosis induction Figure S5F. Overexpression of BCL2 or MCL1 and paclitaxel or cisplatin response Figure S6. Cell cycle analysis of HGSOC cells overexpressing anti-apoptotic proteins Figure S7A. Genomic alterations in anti-apoptotic genes in primary ovarian cancer Figure S7B. Copy-number alterations of anti-apoptotic genes in primary HGSOC Figure S7C. Copy-number alterations of pro-apoptotic genes in primary HGSOC Figure S7D. Copy number and expression of anti-apoptotic genes in primary HGSOC Figure S7E. MCL1 and BCL2L1 are focally lified in HGSOC Figure S7F. Progression-free interval of patients with primary HGSOC with focal lifications of BCL2L1 or MCL1 Figure S8A. Copy number alterations of anti-apoptotic genes in ovarian cancer cell lines Figure S8B. Expression of anti-apoptotic genes in ovarian cancer cell lines Figure S9A. Expression of anti-apoptotic genes in platinum-sensitive and -resistant HGSOC Figure S9B. Expression of anti-apoptotic genes in paired platinum-sensitive and- resistant HGSOC Figure S10A. Effects of single-agent anti-apoptotic protein inhibitors on ovarian cancer cell lines Figure S10B. BH3 profiling of HGSOC cell lines with a panel of pro-apoptotic peptides
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22512715.V1
Abstract: ORF overexpression screen data
No related grants have been discovered for Jennifer Guerrierro.