Validation of absolutely quantitated Ki67 and cyclinD1 protein levels for prognosis of Luminal-like breast cancer patients.

AIMS: To translate a clinical research finding into daily clinical practice requires well-controlled clinical trials. We have demonstrated the usage of absolute quantitation of Ki67 and cyclinD1 protein levels to improve prognosis of Luminal-like patients based on overall survival (OS) analysis of a cohort of 155 breast cancer specimens (cohort 1). However, this finding is considered the D level of evidence (LOE) to require subsequent validation before it may be used in daily clinical practice. To set the stage for future clinical trials, our findings were validated through OS analysis of an independent cohort (cohort 2) of 173 Luminal-like patients. METHODS: Both Ki67 and cyclinD1 levels were measured absolutely and quantitatively using the Quantitative Dot Blot (QDB) method in cohort 2. The proposed cutoffs for both biomarkers from cohort 1 were re-evaluated in cohort 2 and in the merged cohort of 1 and 2, respectively, through univariate, multivariate and Kaplan-Meier survival analysis. RESULTS: The proposed cutoffs of 2.31 nmol/g for Ki67 and 0.44 µmol/g for cyclinD1 were validated as effective cutoffs in cohort 2 and the merged cohort through OS analysis. The combined use of both biomarkers allowed us to identify patients with both biomarker levels below the cutoffs (59.3%) with10-year survival probability (SP) of 89%, in comparison to those above the cutoffs (8.3%) with 8 year SP of 28% through OS analysis in the merged cohort. CONCLUSIONS: This study validated our findings that absolute quantitation of Ki67 and cyclinD1 allows effective subtyping of luminal-like patients. It sets the stage for prospective or prospective-retrospective clinical studies.

Quantitative Dot Blot (QDB) as a universal platform for absolute quantification of tissue biomarkers.

To circumvent the limitations associated with sandwich ELISA for tissue biomarker quantitation, Quantitative Dot Blot method (QDB) was proposed using antibodies clinically validated for immunohistochemistry (IHC), as this method requires only one primary antibody in the analysis. The protein levels of four breast cancer tissue biomarkers, including Estrogen Receptor (ER), Progesterone Receptor (PR), Ki67 and Her2, were absolutely quantitated successfully in 190 frozen breast tissue biopsies, and the results were further verified with provided IHC results. We propose QDB method as an alternative platform to Sandwich ELISA for absolute quantitation of tissue biomarkers with significantly reduced developing effort and time.

ELISA-like QDB method to meet the emerging need of Her2 assessment for breast cancer patients.

Inherent issues of subjectivity and inconsistency have long plagued immunohistochemistry (IHC)-based Her2 assessment, leading to the repeated issuance of guidelines by the American Society of Clinical Oncology/College of American Pathologists (ASCO/CAP) for its standardization for breast cancer patients. Yet, all these efforts may prove insufficient with the advent of Trastuzumab deruxtecan (T-Dxd), a drug with the promise to expand to tumors traditionally defined as Her2 negative (Her2-). In this study, we attempted to address these issues by exploring an ELISA-like quantitative dot blot (QDB) method as an alternative to IHC. The QDB method has been used to measure multiple protein biomarkers including ER, PR, Ki67, and cyclin D1 in breast cancer specimens. Using an independent cohort (cohort 2) of breast cancer formalin-fixed paraffin-embedded (FFPE) specimens, we validated cutoffs developed in cohort 1 (Yu et al., Scientific Reports 2020 10:10502) with overall 100% specificity (95% CI: 100-100) and 97.56% sensitivity (95% CI: 92.68-100) in cohort 2 against standard practice with the dichotomized absolutely quantitated values. Using the limit of detection (LOD) of the QDB method as the putative cutoff point, tumors with no Her2 expression were identified with the number comparable to those of IHC 0. Our results support further evaluation of the QDB method as an alternative to IHC to meet the emerging need of identifying tumors with low Her2 expression (Her2-low) in daily clinical practice.

Objective Quantitation of EGFR Protein Levels using Quantitative Dot Blot Method for the Prognosis of Gastric Cancer Patients.

PURPOSE: An underlying factor for the failure of several clinical trials of anti-epidermal growth factor receptor (EGFR) therapies is the lack of an effective method to identify patients who overexpress EGFR protein. The quantitative dot blot method (QDB) was used to measure EGFR protein levels objectively, absolutely, and quantitatively. Its feasibility was evaluated for the prognosis of overall survival (OS) of patients with gastric cancer. MATERIALS AND METHODS: Slices of 2×5 µm from formalin-fixed paraffin-embedded gastric cancer specimens were used to extract total tissue lysates for QDB measurement. Absolutely quantitated EGFR protein levels were used for the Kaplan-Meier OS analysis. RESULTS: EGFR protein levels ranged from 0 to 772.6 pmol/g (n=246) for all gastric cancer patients. A poor correlation was observed between quantitated EGFR levels and immunohistochemistry scores with ρ=0.024 and P=0.717 in Spearman's correlation analysis. EGFR was identified as an independent negative prognostic biomarker for gastric cancer patients only through absolute quantitation, with a hazard ratio of 1.92 (95% confidence interval, 1.05-3.53; P=0.034) in multivariate Cox regression OS analysis. A cutoff of 208 pmol/g was proposed to stratify patients with a 3-year survival probability of 44% for patients with EGFR levels above the cutoff versus 68% for those below the cutoff based on Kaplan-Meier OS analysis (log rank test, P=0.002). CONCLUSIONS: A QDB-based assay was developed for gastric cancer specimens to measure EGFR protein levels absolutely, quantitatively, and objectively. This assay should facilitate clinical trials aimed at evaluation of anti-EGFR therapies retrospectively and prospectively for gastric cancer.

3D Visualization of the Dynamic Bidirectional Talk Between ER/PR and Her2 Pathways.

Background: Extensive amounts of archived formalin fixed paraffin embedded (FFPE) human tumor tissues are the ultimate resource to investigate signaling network underlying tumorigenesis in human. Yet, their usage is severely limited for lacking of suitable protein techniques. In this study, a quantitative, objective, absolute, and high throughput immunoblot method, quantitative dot blot (QDB), was explored to address this issue by investigating the putative relationship between estrogen receptor (ER)/progesterone receptor (PR) and human epidermal growth factor receptor 2 (Her2) pathways in breast cancer tumorigenesis. Methods: In this descriptive observational retrospective study, ER, PR, Her2, and Ki67 protein levels were measured absolutely and quantitatively in 852 FFPE breast cancer tissues using the QDB method. ER, PR, and Her2 levels were charted on the X, Y, and Z-axes to observe samples distribution in a 3D scatterplot. Results: A "seesaw" relationship between ER/PR and Her2 pathways was observed in ER-PR-Her2 space, characterized by the expression levels of these 3 proteins. Specimens with strong expressions of ER/PR proteins were found spreading along the ER/PR floor while those with strong Her2 expression were found wrapping around the Her2 axis. Those lacking strong expressions of all 3 proteins were found accumulating at the intersection of the ER, PR, and Her2 axes. Few specimens floated in the ER-PR-Her2 space to suggest the lack of co-expression of all 3 proteins simultaneously. Ki67 levels were found to be significantly reduced in specimens spreading in the ER-PR space. Conclusions: The unique distribution of specimens in ER-PR-Her2 space prior to any clinical intervention provided visual support of bidirectional talk between ER/PR and Her2 pathways in breast cancer specimens. Clinical interventions to suppress these 2 pathways alternatively warrant further exploration for breast cancer patients accordingly. Our study also demonstrated that the QDB method is an effective tool to analyze archived FFPE cancer specimens in biomedical research.

Combined Use of cyclinD1 and Ki67 for Prognosis of Luminal-Like Breast Cancer Patients.

BACKGROUND: Ki67 is a biomarker of proliferation to be used in immunohistochemistry (IHC)-based surrogate assay to determine the necessity of cytotoxic therapy for Luminal-like breast cancer patients. cyclinD1 is another frequently used biomarker of proliferation. A retrospective study was performed here to investigate if these two biomarkers may be combined to improve the prognosis of Luminal-like patients. METHODS: Both Ki67 and cyclinD1 protein levels were measured absolutely and quantitatively using Quantitative Dot Blot method in 143 Luminal-like specimens. Optimized cutoffs for these two biomarkers were developed to evaluate their prognostic roles using Kaplan-Meier overall survival (OS) analysis. RESULTS: cyclinD1 was found as an independent prognostic factor from Ki67 in univariate and multivariate OS analyses. At optimized cutoffs (cyclinD1 at 0.44 µmol/g and Ki67 at 2.31 nmol/g), the subgroup with both biomarkers below the cutoffs (n = 65) had 10-year survival probability at 90% in comparison to those with both biomarkers above the cutoffs (n = 18) with 8-year survival probability at 26% (log-rank test, p <0.0001). This finding was used to modify the surrogate assay using IHC-based cyclinD1 scores, with p-value decreased from 0.031 to 0.00061 or from 0.1 to 0.02, when the Ki67 score of 14 or 20% was used as cutoff, respectively, in the surrogate assay. CONCLUSION: The current study supports the prospective investigation of cyclinD1 relevance in the clinic.

Improving Prognosis of Surrogate Assay for Breast Cancer Patients by Absolute Quantitation of Ki67 Protein Levels Using Quantitative Dot Blot (QDB) Method.

BACKGROUND: Immunohistochemistry (IHC)-based surrogate assay is the prevailing method in daily clinical practice to determine the necessity of chemotherapy for Luminal-like breast cancer patients worldwide. It relies on Ki67 scores to separate Luminal A-like from Luminal B-like breast cancer subtypes. Yet, IHC-based Ki67 assessment is known to be plagued with subjectivity and inconsistency to undermine the performance of the surrogate assay. A novel method needs to be explored to improve the clinical utility of Ki67 in daily clinical practice. MATERIALS AND METHODS: The Ki67 protein levels in a cohort of 253 specimens were assessed with IHC and quantitative dot blot (QDB) methods, respectively, and used to assign these specimens into Luminal A-like and Luminal B-like subtypes accordingly. Their performances were compared with the Kaplan-Meier, univariate, and multivariate survival analyses of the overall survival (OS) of Luminal-like patients. RESULTS: The surrogate assay based on absolutely quantitated Ki67 levels (cutoff at 2.31 nmol/g) subtyped the Luminal-like patients more effectively than that based on Ki67 scores (cutoff at 14%) (Log rank test, p = 0.00052 vs. p = 0.031). It is also correlated better with OS in multivariate survival analysis [hazard ratio (HR) at 6.89 (95% CI: 2.66-17.84, p = 0.0001) vs. 2.14 (95% CI: 0.89-5.11, p = 0.087)]. CONCLUSIONS: Our study showed that the performance of the surrogate assay may be improved significantly by measuring Ki67 levels absolutely, quantitatively, and objectively using the QDB method.

Developing a routine lab test for absolute quantification of HER2 in FFPE breast cancer tissues using Quantitative Dot Blot (QDB) method.

Developing immunoassay for absolute quantitation of protein biomarkers in Formalin Fixed Paraffin Embedded (FFPE) samples promises improved objectivity, consistency and accuracy in daily clinical practice. The feasibility of Quantitative Dot Blot (QDB) method for this purpose was explored in this study. We were able to measure HER2 protein levels using 0.5 µg/sample total protein lysate extracted from 2 × 5 µm FFPE slices absolutely and quantitatively using QDB method in 332 breast cancer FFPE samples. HER2 levels measured using two clinically validated antibodies for immunohistochemistry respectively were highly correlated (r = 0.963). We also achieved area under the curve (AUC) at 0.9998 ± 0.0002 (p < 0.0001, n = 224) with IHC analysis, and 0.9942 ± 0.0031 (p < 0.0001, n = 319) with combined results from IHC and Fluorescence in situ hybridization (FISH) analyses when analyzed with Receiver Operative Characteristics analysis (ROC) respectively. When the results were converted dichotomously with optimized cutoffs from ROC analyses, we achieved 99.5% concordance with IHC; and 96.9% with combined results from both IHC and FISH analyses. Therefore, we were able to demonstrate QDB method as the first immunoassay platform for absolute quantitation of protein biomarkers in FFPE samples to meet the need of daily clinical practice, especially for local laboratories or laboratories in developing countries.

Quantitative dot blot analysis (QDB), a versatile high throughput immunoblot method.

Lacking access to an affordable method of high throughput immunoblot analysis for daily use remains a big challenge for scientists worldwide. We proposed here Quantitative Dot Blot analysis (QDB) to meet this demand. With the defined linear range, QDB analysis fundamentally transforms traditional immunoblot method into a true quantitative assay. Its convenience in analyzing large number of samples also enables bench scientists to examine protein expression levels from multiple parameters. In addition, the small amount of sample lysates needed for analysis means significant saving in research sources and efforts. This method was evaluated at both cellular and tissue levels with unexpected observations otherwise would be hard to achieve using conventional immunoblot methods like Western blot analysis. Using QDB technique, we were able to observed an age-dependent significant alteration of CAPG protein expression level in TRAMP mice. We believe that the adoption of QDB analysis would have immediate impact on biological and biomedical research to provide much needed high-throughput information at protein level in this "Big Data" era.