Benefits of Adding Paclitaxel to Adjuvant Doxorubicin/Cyclophosphamide Depending on HER2 & ER Status: Analysis of Tumor Tissue Microarrays and Immunohistochemistry in CALGB 9344 (Intergroup 0148).

2009 ◽  
Author(s):  
D. Berry ◽  
D. Berry ◽  
A. Thor ◽  
S. Jewell ◽  
G. Broadwater ◽  
...  
Keyword(s):  
Tumor Tissue ◽  
Tissue Microarrays ◽  
Status Analysis ◽  
Er Status

scholarly journals High Prevalence of 5T4/Trophoblast Glycoprotein in Soft Tissue Sarcomas

Cancers ◽  
2021 ◽  
Vol 13 (19) ◽  
pp. 4841
Author(s):  
Patrick Groothuis ◽  
Nicola Penel ◽  
Antoine Italiano ◽  
Nuria Kotecki ◽  
Fred Dijcks ◽  
...  
Keyword(s):  
Soft Tissue ◽  
Tumor Tissue ◽  
Staining Method ◽  
Soft Tissue Sarcomas ◽  
Tissue Microarrays ◽  
Histological Subtypes ◽  
Scoring Method ◽  
Drug Conjugates ◽  
High Prevalence ◽  
Quantitative Scoring

The expression of 5T4/trophoblast glycoprotein was evaluated in several histological subtypes of soft tissue sarcoma (STS) to determine whether the prevalence and level of expression of this membrane-associated glycoprotein is sufficient for use in targeted therapies. Tumor tissue microarrays containing cores from different histological subtypes of STS were stained using a standardized immunohistochemical staining method to detect 5T4; the level of staining was assessed using a semi-quantitative scoring method. No 5T4 staining was seen in the angiosarcomas and liposarcomas investigated in this study. 5T4 staining in the other STS subtypes was seen in more than 50% of cases, warranting further investigation into whether this antigen could evoke an anti-tumor immune response or can be used as target for the delivery of more potent toxins through antibody drug conjugates.

Active c-Src has prognostic and therapeutic value in ER-negative breast cancer

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 10063-10063
Author(s):  
A. Arnaout ◽  
L. Yang ◽  
C. Holloway ◽  
N. Steven ◽  
P. Sun ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prognostic Significance ◽  
Immunohistochemical Analysis ◽  
Tissue Microarrays ◽  
Distant Recurrence ◽  
Breast Cancers ◽  
Nonreceptor Tyrosine Kinase ◽  
Human Breast Carcinomas ◽  
Er Positive ◽  
Er Status

10063 Background: Approximately 33% of newly diagnosed breast cancers lack ER and these tend to have a worse prognosis as compared to ER-positive breast cancers. Therapeutic options are limited as they are not responsive to antihormonal therapy and often develop resistance to chemotherapies. We have recently shown that activation of the nonreceptor tyrosine kinase protein c-Src leads to the accelerated ER degradation in ER-negative breast cancers. This study performs an immunohistochemical analysis of activated c-Src in a large cohort of primary human breast carcinomas to a) assess its prognostic significance and b) correlate its relationship to the ER status of breast cancers. Methods: A total of 916 patients with breast cancer diagnosed between 1987 and 1997 had clinicopathological data and paraffin-embedded tumor tissues for the study. Tissue microarrays were constructed. A four point scoring system based on immunostaining intensity was used to grade the levels of active phosphorylated c-Src. Grading was done by one pathologist. Statistical analysis was used to assess the prognostic significance of activated c-Src and its relationship to other prognostic variables. Results: Median follow-up was 7.31 years. Active c-Src grade was inversely correlated with ER status (p=0.004) and predicted for treatment with chemotherapy (p=0.002) and lack of treatment with Tamoxifen (p=0.007). Patients with greater levels of c-Src tended to be younger (p=0.004) and had higher Bloom Richardson scores for their tumors (p=0.004). Higher levels of c-Src also predicted for for shorter timing to distant recurrence (p=0.01) and shorter timing to death (p=0.04). There was a trend towards a shorter timing to regional recurrence with higher levels of c-Src but the relationship was not statistically significant (p=0.08). Conclusion: This study supports the hypothesis that the presence of active, phosphorylated c-Src contributes to the development of ER-negative status in breast cancers. The presence of c-Src also is associated with other poor prognostic factors and contributes to a worse prognostic outcome. This study suggests that c-Src inhibitors may be a novel therapeutic strategy for the treatment of ER-negative breast cancers. No significant financial relationships to disclose.

scholarly journals Machine learning-enabled cancer diagnostics with widefield polarimetric second-harmonic generation microscopy

2021 ◽  
Author(s):  
Kamdin Mirsanaye ◽  
Leonardo Uribe Castaño ◽  
Yasmeen Kamaliddin ◽  
Ahmad Golaraei ◽  
Renaldas Augulis ◽  
...  
Keyword(s):  
Second Harmonic Generation ◽  
Harmonic Generation ◽  
Tumor Tissue ◽  
Second Harmonic ◽  
Tissue Microarrays ◽  
Cancer Diagnostics ◽  
Label Free ◽  
Second Harmonic Generation Microscopy ◽  
Trained Classifier ◽  
Omission Rate

The extracellular matrix (ECM) collagen undergoes major remodeling during tumorigenesis. However, alterations to the ECM are not widely considered in cancer diagnostics, due to mostly uniform appearance of collagen fibers in white light images of hematoxylin and eosin-stained tissue sections. Polarimetric second-harmonic generation (P-SHG) microscopy enables label-free visualization and ultrastructural investigation of non-centrosymmetric molecules, which, when combined with texture analysis, provides multiparameter characterization of tissue collagen. This paper demonstrates whole slide imaging of breast tissue microarrays using high-throughput widefield P-SHG microscopy. The resulting P-SHG parameters are used in classification to differentiate tumor tissue from normal with 94.2% accuracy and F1-score, and 6.3% false discovery rate. Subsequently, the trained classifier is employed to predict tumor tissue with 91.3% accuracy, 90.7% F1-score, and 13.8% false omission rate. As such, we show that widefield P-SHG microscopy reveals collagen ultrastructure over large tissue regions and can be utilized as a sensitive biomarker for cancer diagnostics and prognostics studies.

scholarly journals Performance of Different Diagnostic PD-L1 Clones in Head and Neck Squamous Cell Carcinoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Julika Ribbat-Idel ◽  
Franz F. Dressler ◽  
Rosemarie Krupar ◽  
Christian Watermann ◽  
Finn-Ole Paulsen ◽  
...  
Keyword(s):  
Head And Neck ◽  
Tumor Cells ◽  
Squamous Cell ◽  
Tumor Tissue ◽  
Checkpoint Inhibitors ◽  
Principal Component ◽  
Tissue Microarrays ◽  
Daily Routine ◽  
Therapeutic Decision Making ◽  
Reported Data

Background: The approval of immune checkpoint inhibitors in combination with specific diagnostic biomarkers presents new challenges to pathologists as tumor tissue needs to be tested for expression of programmed death-ligand 1 (PD-L1) for a variety of indications. As there is currently no requirement to use companion diagnostic assays for PD-L1 testing in Germany different clones are used in daily routine. While the correlation of staining results has been tested in various entities, there is no data for head and neck squamous cell carcinomas (HNSCC) so far.Methods: We tested five different PD-L1 clones (SP263, SP142, E1L3N, 22-8, 22C3) on primary HNSCC tumor tissue of 75 patients in the form of tissue microarrays. Stainings of both immune and tumor cells were then assessed and quantified by pathologists to simulate real-world routine diagnostics. The results were analyzed descriptively and the resulting staining pattern across patients was further investigated by principal component analysis and non-negative matrix factorization clustering.Results: Percentages of positive immune and tumor cells varied greatly. Both the resulting combined positive score as well as the eligibility for certain checkpoint inhibitor regimens was therefore strongly dependent on the choice of the antibody. No relevant co-clustering and low similarity of relative staining patterns across patients was found for the different antibodies.Conclusions: Performance of different diagnostic anti PD-L1 antibody clones in HNSCC is less robust and interchangeable compared to reported data from other tumor entities. Determination of PD-L1 expression is critical for therapeutic decision making and may be aided by back-to-back testing of different PD-L1 clones.

Measuring phospho-MET by multiplex immunofluorescence to aid in selection of patients with MET activation in tumors.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 3131-3131
Author(s):  
Tony Navas ◽  
Apurva K. Srivastava ◽  
Jeevan P Govindharajulu ◽  
Yvonne A. Evrard ◽  
Susanne Borgel ◽  
...  
Keyword(s):  
Plasma Membrane ◽  
Patient Selection ◽  
Tumor Tissue ◽  
Tissue Microarrays ◽  
Immunofluorescence Assay ◽  
Preclinical Trials ◽  
Xenograft Models ◽  
Patient Selection Criteria ◽  
Development And Validation ◽  
Pdx Models

3131 Background: Currently, patient selection criteria for clinical testing of MET inhibitors are limited. Robust studies selecting patients based on MET protein expression, MET gene amplification, or mutations have not met their efficacy goals. Development of microscopy-based assays to quantify levels of phospho-MET (pMET) in tumors has been hampered by poor antibody specificity. Here, we present the development and validation of a robust, highly specific multiplex immunofluorescence assay (IFA) that measures pY1235-MET and total MET in tumor tissue. Methods: This assay utilizes antibodies to pY1235-MET (NCI-23111), total MET (D1C2), and plasma membrane (PM) marker Na+/K+-ATPase, each conjugated to a different Alexa Fluor dye. We used tumor tissue from crizotinib-treated SNU5 xenograft models to demonstrate pY1235-MET assay fitness-for-purpose and cross-platform assay concordance with our validated pMET ELISA. In addition, this IFA was validated by phospho-peptide competition using custom tissue microarrays (TMA) derived from patients with colorectal carcinoma (CRC). Finally, we developed quantitative algorithms to assess pY1235 MET levels in the plasma membrane and nucleus using PM and DAPI masks, respectively. Patient-derived xenograft models (PDX) were obtained from NCI’s Patient-Derived Models Repository (www.pdmr.cancer.gov). Results: The prevalence of high pY1235-MET expression in CRC patient specimens was greater than expected; of the 64 TMA cores evaluated, 29 (45%) and 19 (29%) had high pY1235-MET and total MET levels, respectively, as defined by mean marker area of ≥ 30 μm2/cell. To address the potential utility of pY1235-MET as a diagnostic biomarker, we examined 15 CRC PDX models by pMET ELISA and IFA. Two CRC tumor models were positive for pY1235-MET expression in both assays. The pY1235-MET IFA results and gene expression data were used to select PDX models for ongoing preclinical trials of potent MET inhibitors. Conclusions: This novel pY1235-MET IFA will enable clinicians to address the utility of activated MET as a biomarker for patient selection and/or prediction of response in clinical trials of MET inhibitors. Funded by NCI Contract No. HHSN261200800001E.

scholarly journals Canopy Homolog 2 Expression Predicts Poor Prognosis in Hepatocellular Carcinoma with Tumor Hemorrhage

2018 ◽  
Vol 50 (6) ◽  
pp. 2017-2028 ◽  
Author(s):  
Dong Wang ◽  
Zhi-Ming Wang ◽  
Sai Zhang ◽  
Hai-Jun Wu ◽  
Yi-Ming Tao
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Proliferation ◽  
Tumor Microenvironment ◽  
Tumor Tissue ◽  
Cox Regression ◽  
Positive Impact ◽  
Critical Role ◽  
Tissue Microarrays ◽  
Cox Proportional Hazards ◽  
Qrt Pcr

Background/Aims: Canopy homolog 2 (CNPY2) is a signature gene highly associated with tumor progression, including hepatocellular carcinoma (HCC). The presence of tumor hemorrhage (TH) implies a fast-growing and worse tumor microenvironment. We examined a possible association between CNPY2 levels and TH and evaluated their prognostic values in patients with HCC. Methods: CNPY2 mRNA and protein levels were respectively determined in two independent cohorts of HCC specimens using quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry of tissue microarrays. Kaplan-Meier survival and Cox regression analyses were executed to evaluate the prognosis of HCC. CNPY2 knockout HCC cell lines were established by the CRISPR/Cas9 gene editing system, and the functional role of CNPY2 in HCC cell proliferation and growth was examined in vitro and in vivo. Results: qRT-PCR showed that CNPY2 expression was significantly higher in HCC tumor tissue than in adjacent non-tumor tissue. Immunohistochemistry of HCC tissue microarrays demonstrated that CNPY2 expression was significantly correlated with TH and clinicopathological features indicating worse HCC progression. The prognostic value of CNPY2 expression and TH was validated by Cox proportional hazards analyses. Furthermore, CNPY2 knockout resulted in the significant suppression of MHCC97H cell proliferation, tumor growth, and hemorrhage. Bioinformatics analysis revealed that CNPY2 was closely associated with the expression levels of 6 positive impact genes in HCC, namely, ROMO1, BOLA2, HSF1, ATG4B, ATF4, and DENR, which are implicated in the regulation of the tumor microenvironment. Conclusion: CNPY2 is an oncogene that plays a critical role in the progression of HCC with TH. CNPY2 could be exploited as a novel prognostic marker and potential target for therapeutic intervention in HCC.

Abstract 5300: A survey of EphA2 expression by immunohistochemistry (IHC) in tumor tissue microarrays (TMAs) to support BT5528 indication selection

2020 ◽  
Author(s):  
Carly T. Campbell ◽  
Robert Smale ◽  
James Lee ◽  
Josette William Ragheb ◽  
Michael Rigby ◽  
...  
Keyword(s):  
Tumor Tissue ◽  
Tissue Microarrays

scholarly journals Extent, impact, and mitigation of batch effects in tumor biomarker studies using tissue microarrays

2021 ◽  
Author(s):  
Konrad H. Stopsack ◽  
Svitlana Tyekucheva ◽  
Molin Wang ◽  
Travis A. Gerke ◽  
J. Bailey Vaselkiv ◽  
...  
Keyword(s):  
Measurement Error ◽  
Tumor Tissue ◽  
Tissue Microarrays ◽  
R Package ◽  
Tumor Biomarker ◽  
Batch Effects ◽  
Protein Biomarkers ◽  
Individual Study ◽  
Inherent Feature ◽  
Prostate Cancers

Tissue microarrays (TMAs) have been used in thousands of cancer biomarker studies. To what extent batch effects, measurement error in biomarker levels between slides, affects TMA-based studies has not been assessed systematically. We evaluated 20 protein biomarkers on 14 TMAs with prospectively collected tumor tissue from 1,448 primary prostate cancers. In half of the biomarkers, more than 10% of biomarker variance was attributable to between-TMA differences (range, 1–48%). We implemented different methods to mitigate batch effects (R package batchtma), tested in plasmode simulation. Biomarker levels were more similar between mitigation approaches compared to uncorrected values. For some biomarkers, associations with clinical features changed substantially after addressing batch effects. Batch effects and resulting bias are not an error of an individual study but an inherent feature of TMA-based protein biomarker studies. They always need to be considered during study design and addressed analytically in studies using more than one TMA.

scholarly journals Extent, impact, and mitigation of batch effects in tumor biomarker studies using tissue microarrays

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Konrad H Stopsack ◽  
Svitlana Tyekucheva ◽  
Molin Wang ◽  
Travis A Gerke ◽  
J Bailey Vaselkiv ◽  
...  
Keyword(s):  
Measurement Error ◽  
Tumor Tissue ◽  
Tissue Microarrays ◽  
R Package ◽  
Tumor Biomarker ◽  
Batch Effects ◽  
Protein Biomarkers ◽  
Individual Study ◽  
Inherent Feature ◽  
Prostate Cancers

Tissue microarrays (TMAs) have been used in thousands of cancer biomarker studies. To what extent batch effects, measurement error in biomarker levels between slides, affects TMA-based studies has not been assessed systematically. We evaluated 20 protein biomarkers on 14 TMAs with prospectively collected tumor tissue from 1,448 primary prostate cancers. In half of the biomarkers, more than 10% of biomarker variance was attributable to between-TMA differences (range, 1-48%). We implemented different methods to mitigate batch effects (R package batchtma), tested in plasmode simulation. Biomarker levels were more similar between mitigation approaches compared to uncorrected values. For some biomarkers, associations with clinical features changed substantially after addressing batch effects. Batch effects and resulting bias are not an error of an individual study but an inherent feature of TMA-based protein biomarker studies. They always need to be considered during study design and addressed analytically in studies using more than one TMA.

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