Multigene classifiers, prognostic factors, and predictors of breast cancer clinical outcome

Integrating Genomic Information with Tumor-Immune Microenvironment in Triple-Negative Breast Cancer

BACKGROUND

the development and progression of triple-negative breast cancer (TNBC) is driven by somatic driver mutations and the tumor-immune microenvironment. To date, data on somatic mutations has not been leveraged and integrated with information on the immune microenvironment to elucidate the possible oncogenic interactions and their potential effects on clinical outcomes. Here, we investigated possible oncogenic interactions between somatic mutations and the tumor-immune microenvironment, and their correlation with patient survival in TNBC.

METHODS

We performed analysis combining data on 7,875 somatic mutated genes with information on 1,751 immune-modulated genes, using gene-expression data as the intermediate phenotype, and correlated the resulting information with survival. We conducted functional analysis to identify immune-modulated molecular networks and signaling pathways enriched for somatic mutations likely to drive clinical outcomes.

RESULTS

We discovered differences in somatic mutation profiles between patients who died and those who survived, and a signature of somatic mutated immune-modulated genes transcriptionally associated with TNBC, predictive of survival. In addition, we discovered immune-modulated molecular networks and signaling pathways enriched for somatic mutations.

CONCLUSIONS

The investigation revealed possible oncogenic interactions between somatic mutations and the tumor-immune microenvironment in TNBC, likely to affect clinical outcomes.

Identification of a survival-related signature for sarcoma patients through integrated transcriptomic and proteomic profiling analyses

Sarcoma (SARC) represents a group of highly histological and molecular heterogeneous rare malignant tumors with poor prognosis. There are few proposed classifiers for predicting patient's outcome. The Cancer Proteome Atlas (TPCA) and The Cancer Genome Atlas (TCGA) databases provide multi-omics datasets that enable a comprehensive investigation for this disease. The proteomic expression profile of SARC patients along with the clinical information was downloaded. 55 proteins were found to be associated with overall survival (OS) of patients using univariate Cox regression analysis. We developed a prognostic risk signature that comprises seven proteins (AMPKALPHA, CHK1, S6, ARID1A, RBM15, ACETYLATUBULINLYS40, and MSH6) with robust predictive performance using multivariate Cox stepwise regression analysis. Additionally, the signature could be an independent prognostic predictor after adjusting for clinicopathological parameters. Patients in high-risk group also have worse progression free intervals (PFI) than that of patients in low-risk group, but not for disease free intervals (DFI). The signature was validated using transcriptomic profile of SARC patients from TCGA. Potential mechanisms between high- and low-risk groups were identified using differentially expressed genes (DEGs) analysis. These DEGs were primarily enriched in RAS and MPAK signaling pathways. The signature protein molecules are candidate biomarkers for SARC, and the analysis of computational biology in tumor infiltrating lymphocytes and immune checkpoint molecules revealed distinctly immune landscapes of high- and low-risk patients. Together, we constructed a prognostic signature for predicting outcomes for SARC integrating proteomic and transcriptomic profiles, this might have value in guiding clinical practice.

Genome Instability Profiles Predict Disease Outcome in a Cohort of 4,003 Patients with Breast Cancer

PURPOSE

The choice of therapy for patients with breast cancer is often based on clinicopathologic parameters, hormone receptor status, and HER2 amplification. To improve individual prognostication and tailored treatment decisions, we combined clinicopathologic prognostic data with genome instabilty profiles established by quantitative measurements of the DNA content.

EXPERIMENTAL DESIGN

We retrospectively assessed clinical data of 4,003 patients with breast cancer with a minimum postoperative follow-up period of 10 years. For the entire cohort, we established genome instability profiles. We applied statistical methods, including correlation matrices, Kaplan-Meier curves, and multivariable Cox proportional hazard models, to ascertain the potential of standard clinicopathologic data and genome instability profiles as independent predictors of disease-specific survival in distinct subgroups, defined clinically or with respect to treatment.

RESULTS

In Cox regression analyses, two parameters of the genome instability profiles, the S-phase fraction and the stemline scatter index, emerged as independent predictors in premenopausal women, outperforming all clinicopathologic parameters. In postmenopausal women, age and hormone receptor status were the predominant prognostic factors. However, by including S-phase fraction and 2.5c exceeding rate, we could improve disease outcome prediction in pT1 tumors irrespective of the lymph node status. In pT3-pT4 tumors, a higher S-phase fraction led to poorer prognosis. In patients who received adjuvant endocrine therapy, chemotherapy or radiotherapy, or a combination, the ploidy profiles improved prognostication.

CONCLUSIONS

Genome instability profiles predict disease outcome in patients with breast cancer independent of clinicopathologic parameters. This applies especially to premenopausal patients. In patients receiving adjuvant therapy, the profiles improve identification of high-risk patients.

The hopeful anticancer role of oleuropein in breast cancer through histone deacetylase modulation

Breast cancer (BC) is one of the most common cancers among women worldwide. Genetic, epigenetic, and environmental factors play a crucial role in BC development. Because epigenetic imbalance occurs earlier than expression in carcinogenesis and is reversible, epigenetic reprogramming strategies could be more useful for cancer prevention and therapy. There is evidence indicating that the use of herbal compounds with low toxicity can offer a real benefit in the prevention or treatment of cancer. Oleuropein (OLE), as a natural polyphenol, has shown the anticancer property in cancers. In this study, we investigated for the first time the link between histone deacetylase (HDAC) and OLE to have an anticancer effect in BC. The potential apoptotic and anti-invasive effects of OLE were tested using MCF-7 cells. Transcript expression of HDAC1 and HDAC4 genes after treatment was determined using quantitative reverse transcription polymerase chain reaction. OLE obviously reduced invasiveness and cell viability and simultaneously induced cell apoptosis in MCF-7 cancer cells. Dose-dependent reduction of HDAC4 was observed, whereas apparent changes could not be observed in HDAC1 expression. The current research indicated that OLE can inhibit proliferation and invasion of cells by inducing apoptosis likely through modulation of an important epigenetic factor, HDAC4, in MCF-7 cells. OLE has the potential to be a therapeutic drug for BC prevention and treatment.

Gene expression assay and Watson for Oncology for optimization of treatment in ER-positive, HER2-negative breast cancer

BACKGROUND

Personalized treatment for cancer patients is a hot topic of debate, particularly the decision to initiate chemotherapy in patients with Estrogen receptor (ER)-positive, HER2-negative tumors in the early stages of breast cancer (BC). Owing to significant advancements in information technology (IT) and genomics, clinicians are increasingly attaining therapeutic goals rapidly and safely by effectively differentiating patient subsets that require chemotherapy. IBM Watson for Oncology (WFO) is a cognitive computing system employed by clinicians to provide evidence-based treatment options for cancer. WFO aids in clinical diagnosis, with claims that it may be superior in performance to human clinicians. The current study was based on the hypothesis that WFO alone cannot effectively determine whether or not chemotherapy is essential for the subset of ER-positive, HER2-negative BC patients.

PATIENTS AND METHODS

From December 2015 to July 2017, 95 patients with ER-positive, HER2- negative BC subjected to treatment were retrospectively examined using WFO, and outputs compared to real clinical practice. Treatment options were suggested by WFO, and WFO recommendations calculated both with and without data from the gene expression assay (GEA).

RESULTS

WFO without GEA was unable to determine the groups of patients that did not require chemotherapy. Concordant therapeutic recommendations between real clinical practice and WFO without GEA were obtained for 23.2% of the patient group. On the other hand, the results of WFO with GEA showed good clinical applicability. Sensitivity, specificity, positive predictive and negative predictive values of WFO with GEA were 100%, 80%, 61% and 100%, respectively.

CONCLUSIONS

Our collective findings indicate that WFO without the gene expression assay has limited clinical utility.

Pregnancy and Breast Cancer

Breast cancer is the most commonly diagnosed type of cancer among women worldwide. The majority of breast cancers are sporadic and the etiology is not well understood. Several factors have been attributed to altering the risk of breast cancer. A full-term pregnancy is a crucial factor in altering the risk. Early full-term pregnancy has been shown to reduce the lifetime risk of breast cancer, while a later first full-term pregnancy increases breast cancer risk. Epidemiological and experimental data demonstrate that spontaneous or induced abortions do not significantly alter the risk of breast cancer. In this study, we briefly discuss the different types and stages of breast cancer, various risk factors, and potential mechanisms involved in early full-term pregnancy-induced protection against breast cancer. Understanding how early full-term pregnancy induces protection against breast cancer will help design innovative preventive and therapeutic strategies. This understanding can also help in the development of molecular biomarkers that can be of tremendous help in predicting the risk of breast cancer in the general population.

[Validation and clinical application of MammaPrint® in patients with breast cancer]

BACKGROUND

In recent years, advances in molecular biology have resulted in innovations in breast cancer diagnostics and therapeutics. The development of genomics has revolutionized our understanding of this disease. MammaPrint^® was developed as a diagnostic tool to predict risk of breast cancer recurrence using the expression of 70 genes altering the clinicopathologic paradigm of selection of patients for adjuvant cytotoxic chemotherapy.

MATERIALS AND METHODS

A study of stage i-ii breast cancer patients on whom the MammaPrint^® genomic assay was performed.

RESULTS

The use of the MammaPrint^® assay was a decisive factor for the recommendation of adjuvant treatment with chemotherapy and/or hormone therapy in patients with high risk for relapse. In our group, the patients with low-risk have not presented local or systemic recurrences DISCUSSION: The determination of the genetic characteristics and its alterations in breast cancer, is fundamentally important for a better identification of risk, as well as a better selection of cancer therapy.

CONCLUSION

MammaPrint^® is an effective study to determine risk of recurrence of in early stage breast cancer.

Basic Histopathological Methods and Breast Lesion Types for Research

The in situ observation on the tissues, such as histopathology, immunohistochemistry (IHC), immunofluorescence (IF), and in situ hybridization (ISH), is one of the most important methods in the biomedical scientific research. In this chapter we introduce the most often used methods-hematoxylin and eosin (H&E) and double IF staining. H&E staining is used for general morphology by which the different pathological types of breast lesions are identified. The double IF staining is often used to study the protein-protein interaction on tissues for signaling mechanisms. This chapter also includes the histopathology of primary or simplified breast lesion types that is essential for applying the above methods and the reclassification of breast cancers by molecular markers.

Identifying clinically relevant prognostic subgroups of postmenopausal women with node-positive hormone receptor-positive early-stage breast cancer treated with endocrine therapy: a combined analysis of ABCSG-8 and ATAC using the PAM50 risk of recurrence score and intrinsic subtype

BACKGROUND

In the adjuvant treatment of hormone receptor-positive (HR+) breast cancer, variables like tumour size, grade and nodal status have great impact on therapy decisions. As most node-positive patients with HR+ breast cancer currently receive adjuvant chemotherapy improved methods for characterization of individuals' metastasis risk are needed to reduce overtreatment.

PATIENTS AND METHODS

Tissue specimens from node-positive patients of the ABCSG-8 and ATAC trials who received adjuvant tamoxifen and/or anastrozole were included in this study. Analysing RNA from paraffin blocks using the PAM50 test, the primary objective was to evaluate the prognostic information of the risk of recurrence (ROR) score added to combined clinical standard variables in patients with one positive node (1N+) and in patients with two or three positive nodes (2-3N+), using log-likelihood ratio tests.

RESULTS

At a median follow-up of 9.6 years, distant metastases occurred in 97 (18%) of 543 node-positive patients. In a multivariate analysis, the PAM50-derived ROR score provided reliable prognostic information in addition to and beyond established clinical factors for 1N+ (P < 0.0001) and 2-3N+ patients (P = 0.0002). Ten-year distant recurrence risk was significantly increased in the high-risk compared with the low-risk group derived from ROR score for 1N+ [25.5%, 95% confidence interval (CI) 17.5% to 36.1%versus 6.6%, 95% CI 3.3% to 12.8%] and compared with the combined low/intermediate risk group for 2-3N+ patients (33.7%, 95% CI 25.5% to 43.8% versus 12.5%, 95% CI 6.6% to 22.8%). Additionally, the luminal A intrinsic subtype (IS) exhibited significantly lower risk of distant recurrence compared with the luminal B subtype in 1N+ and 2-3N+ patients.

CONCLUSION

PAM50 ROR score and IS can identify node-positive patient subgroups with limited risk of metastasis after endocrine therapy, for whom adjuvant chemotherapy can be spared. The PAM50 test is a valuable tool in determining treatment of node-positive early-stage breast cancer patients.

The classification of invasive carcinoma of the breast

The classification of invasive breast carcinoma assists diagnosis, allows for comparison of different patient groups in clinical trials and facilitates epidemiological analysis. For the individual patient, accurate tumor classification informs clinical decision-making with emphasis on assessment of prognosis and treatment formulation. Tumor grade is an independent prognostic indicator and is calculated by assessing specific tumor characteristics microscopically. The Tumor Node Metastasis staging system, produced by the American Joint Committee on Cancer Union for International Cancer Control, combines information about the primary tumor size, the status of the regional lymph nodes and the presence or absence of distant metastases at diagnosis to classify disease. In recent years, the use of gene expression profiling technology has led to the development of the molecular classification of breast cancer and has highlighted the importance of hormone receptor and HER2 oncogenic pathways, with particular reference to targeted chemotherapy. Tumor typing involves the identification of 'no special type' carcinoma with variable clinical, histological and molecular characteristics and 'special type' carcinomas that are usually associated with a particular set of prognostic and predictive indices. Some special type carcinomas have unique biological features that influence diagnostic investigation and clinical management.

Relapsed classic E-cadherin (CDH1)-mutated invasive lobular breast cancer shows a high frequency of HER2 (ERBB2) gene mutations

PURPOSE

We queried whether comprehensive genomic profiling using a next-generation sequencing-based assay could identify novel and unanticipated targets of therapy for patients with relapsed invasive lobular carcinoma (ILC).

EXPERIMENTAL DESIGN

DNA sequencing (Illumina HiSeq 2000) was conducted for 3,320 exons of 182 cancer-related genes and 37 introns of 14 genes frequently rearranged in cancer on indexed, adaptor-ligated, hybridization-captured libraries using DNA isolated from formalin-fixed paraffin-embedded sections from 22 histologically verified ILC.

RESULTS

A total of 75 genomic alterations were identified with an average of 3.4 alterations per tumor (range, 1-6), of which 35 were actionable for an average of 1.59 actionable alterations per patient (range, 0-3). Nineteen of 22 (86%) of the ILC samples harbored at least one actionable alteration. Six (27%) cases featured alterations in ERRB2 including 4 (18%) with ERBB2 mutation, 1 (5%) with an ERBB2 gene fusion, and 1 (5%) with an ERBB2 copy number gain (amplification). The enrichment of ERBB2 mutations/fusion in CDH1-mutated ILC (5 of 22, 23%) compared with the 5 ERBB2 mutations in a series of 286 non-CDH1-mutated breast cancers from which the ILC cases were obtained (5 of 286, 2%) was significant (P = 0.0006).

CONCLUSIONS

Comprehensive genomic profiling of relapsed CDH1-mutated ILC revealed actionable genomic alterations in 86% of cases, featured a high incidence of ERBB2 alterations, and can reveal actionable alterations that can inform treatment decisions for patients with ILC.

Comparison of EndoPredict and Oncotype DX test results in hormone receptor positive invasive breast cancer

Aim

Several multigene expression-based tests offering prognostic and predictive information in hormone-receptor positive early breast cancer were established during the last years. These tests provide prognostic information on distant recurrences and can serve as an aid in therapy decisions. We analyzed the recently validated reverse-transcription-quantitative-real-time PCR-based multigene-expression Endopredict (EP)-test on 34 hormone-receptor positive breast-cancer cases and compared the EP scores with the Oncotype DX Recurrence-scores (RS) obtained from the same cancer samples.

Methods

Formalin-fixed, paraffin-embedded invasive breast-cancer tissues from 34 patients were analyzed by the EP-test. Representative tumor blocks were analyzed with Oncotype DX prior to this study. Tumor tissue was removed from unstained slides, total-RNA was isolated and EP-analysis was performed blinded to Oncotype DX results.

Results

Extraction of sufficient amounts of RNA and generation of valid EP-scores were possible for all 34 samples. EP classified 11 patients as low-risk and 23 patients as high-risk. RS Score defined 15 patients as low-risk, 10 patients as intermediate-risk in and 9 patients as high-risk. Major-discrepancy occurred in 6 of 34 cases (18%): Low-risk RS was classified as high-risk by EP in 6 cases. Combining the RS intermediate-risk and high-risk groups to a common group, the concordance between both tests was 76%. Correlation between continuous EP and RS-scores was moderate (Pearson-coefficient: 0.65 (p<0.01).

Conclusion

We observed a significant but moderate concordance (76%) and moderate correlation (0.65) between RS and EP Score. Differences in results can be explained by different weighting of biological motives covered by the two tests. Further studies are needed to explore the clinical relevance of discrepant test results with respect of outcome.

MammaPrint Feasibility in a Large Tertiary Urban Medical Center: An Initial Experience

Background. The MammaPrint (MP) diagnostic assay stratifies breast cancer patients into high- and low-risk groups using mRNA analysis of a 70-gene profile. The assay is validated for assessment of patients with estrogen receptor positive or negative tumors less than 5 cm with 3 or fewer malignant lymph nodes. TargetPrint (TP) is an assay for assessing estrogen, progesterone, and HER2-neu receptor status based on mRNA expression. A potential limitation of these assays is that they require an evaluation of fresh tissue samples. There is limited published experience describing MP or TP implementation. Methods. Over 10 months, 4 breast surgeons obtained samples from 54 patients for MP/TP analysis. The samples were analyzed by Agendia Labs. The tumors were independently evaluated for receptor status using immunohistochemistry (IHC). Retrospectively, we identified patients who were assessed by MP/TP during this period. Patients who underwent OncotypeDx evaluation were also identified. Results. Of the 54 patients receiving MP, 4 were found ineligible for MP risk assessment because >3 lymph nodes were found to be malignant. Out of all eligible patients, 14/50 (28%) had samples whose quantity of tumor was not sufficient for analysis (QNS). Out of eligible patients with tumors <1 cm, 7/8 (88%) had QNS samples. 7/42 with tumors ≥1 cm (17%) had QNS samples. Nine patients had discordant receptor results when evaluated by IHC versus. TP. Of patients who also underwent OncotypeDx testing, 6/14 (43%) had discordant results with MP. Conclusions. This study indicates that using MP/TP assay is feasible in a tertiary care center but there may be utility in limiting MP testing to patients with tumors between 1 and 5 cm due to high likelihood of uninformative results in subcentimeter tumors. Further study is needed to explore the discordance between oncotype and MP results.

A pathway-based classification of breast cancer integrating data on differentially expressed genes, copy number variations and microRNA target genes

Breast cancer is a clinically heterogeneous disease characterized by distinct molecular aberrations. Understanding the heterogeneity and identifying subgroups of breast cancer are essential to improving diagnoses and predicting therapeutic responses. In this paper, we propose a classification scheme for breast cancer which integrates data on differentially expressed genes (DEGs), copy number variations (CNVs) and microRNAs (miRNAs)-regulated mRNAs. Pathway information based on the estimation of molecular pathway activity is also applied as a postprocessor to optimize the classifier. A total of 250 malignant breast tumors were analyzed by k-means clustering based on the patterns of the expression profiles of 215 intrinsic genes, and the classification performances were compared with existing breast cancer classifiers including the BluePrint and the 625-gene classifier. We show that a classification scheme which incorporates pathway information with various genetic variations achieves better performance than classifiers based on the expression levels of individual genes, and propose that the identified signature serves as a basic tool for identifying rational therapeutic opportunities for breast cancer patients.

The management of preinvasive breast cancer

SUMMARY Ductal carcinoma in situ (DCIS) is a preinvasive breast cancer in which the proliferations of malignant ductal epithelial cells have not breached the ductal basement membrane. Currently there is controversy over the optimum management of DCIS, with suggestions that there may be an element of ‘overdiagnosis’ of some low-risk cases that may never progress to invasive cancer within a patient’s lifetime. This review discusses the biology and natural history of DCIS and current management strategies, addresses the risk factors for recurrence and how these can be minimized, highlights areas of controversy and suggest the possible direction of future research.

From discovery to the clinic: the novel DNA methylation biomarker (m)SEPT9 for the detection of colorectal cancer in blood

Detection of colorectal cancer at an early stage has been shown to significantly decrease mortality from the disease, while the advent of effective therapies for late-stage colorectal cancer make the detection of colorectal cancer at any stage a critical step in further reducing colorectal cancer mortality. Availability of a blood-based test for colorectal cancer is expected to improve screening compliance in the general population. Through DNA methylation-sensitive, restriction enzyme-based biomarker discovery, we identified a region of the Septin 9 gene that is methylated in over 90% of colorectal cancer tissues with little or no methylation seen in normal colon tissue and other controls. Specific detection of colorectal cancer DNA using the Septin 9 methylation biomarker ((m)SEPT9) was demonstrated in multiple studies of plasma from colorectal cancer patients and colonoscopy-verified negative controls. A prospective, population-based trial to determine the clinical performance of (m)SEPT9 in colorectal cancer screening guideline-eligible individuals has recently been completed, with the results to be published in the near future. The potential pitfalls and lessons learned in the multiyear process of developing the (m)SEPT9 biomarker from initial discovery to commercialization are described in this article.

From morphologic to molecular: established and emerging molecular diagnostics for breast carcinoma

Diagnostics in the field of breast carcinoma are constantly evolving. The recent wave of molecular methodologies, both microscope and non-microscope based, have opened new ways to gain insight into this disease process and have moved clinical diagnostics closer to a 'personalized medicine' approach. In this review we highlight some of the advancements that laboratory medicine technology is making toward guiding the diagnosis, prognosis, and therapy selection for patients affected by breast carcinoma. The content of the article is largely structured by methodology, with a distinct emphasis on both microscope based and non-microscope based diagnostic formats. Where possible, we have attempted to emphasize the potential benefits as well as limitations to each of these technologies. Successful molecular diagnostics, applied in concert within the morphologic context of a patient's tumor, are what will lay the foundation for personalized therapy and allow a more sophisticated approach to clinical trial stratification. The future of breast cancer diagnostics looks challenging, but it is also a field of great opportunity. Never before have there been such a plethora of new tools available for disease investigation or candidate therapy selection.

Integrating contextual miRNA and protein signatures for diagnostic and treatment decisions in cancer

The promise of personalized medicine is highly dependent on the identification of biomarkers that inform diagnostic decisions and treatment options, as well as on the accurate, rapid and cost-effective detection and interpretation of these biomarkers. miRNAs, which are short noncoding regulatory RNAs, are rapidly emerging as a novel class of biomarkers with a unique set of biological and chemical properties that makes them very appealing candidates for theranostic applications in cancer. Since the utility of some protein-encoding gene biomarkers is already exploited in routine clinical practice, it will be important to identify areas in which miRNAs provide complementary or superior information to these existing (and other translational) biomarkers to enhance the diagnostic, prognostic and predictive power of molecular characterization of tumors. In this article, the challenges and opportunities for integration of miRNA-based assays in the clinical toolkit to improve care and management of patients afflicted with solid tumors will be discussed.

Prognostic classification of pediatric medulloblastoma based on chromosome 17p loss, expression of MYCC and MYCN, and Wnt pathway activation

Pediatric medulloblastoma is considered a highly heterogeneous disease and a new strategy of risk stratification to optimize therapeutic outcomes is required. We aimed to investigate a new risk-stratification approach based on expression profiles of medulloblastoma cohorts. We analyzed gene expression profiles of 30 primary medulloblastomas and detected strong evidence that poor survival outcome was significantly associated with mRNA expression profiles of 17p loss. However, it was not supported in independent cohorts from previously published data (n = 100). We speculated that this discrepancy might come from complex conditions of two important prognostic determinants: loss of tumor suppressors (chromosome 17p) and high expression of oncogenes c-myc (MYCC) or N-myc (MYCN). When patients were stratified into 5 or 7 subgroups based on simultaneous consideration of these 2 factors while defining the Wnt group as independent, obviously different survival expectancies were detected between the subgroups. For instance, predicted 5-year survival probabilities ranged from 19% to 81% in the 5 subgroups. We also found that age became a significant prognostic marker after adjusting for 17p, MYCC, and MYCN status. Diminished survival in age <3 years was more substantial in subgroups with high expression of MYCC, MYCN, or 17p loss but not in other subgroups, indicating that poor survival outcome might be synergistically affected by these 3 factors. Here we suggest a more tailored subgrouping system based on expression profiles of chromosome 17p, MYCC, and MYCN, which could provide the basis for a novel risk-stratification strategy in pediatric medulloblastoma.

Novel staging system for predicting disease-specific survival in patients with breast cancer treated with surgery as the first intervention: time to modify the current American Joint Committee on Cancer staging system

PURPOSE

American Joint Committee on Cancer (AJCC) staging is used to determine breast cancer prognosis, yet patient survival within each stage shows wide variation. We hypothesized that differences in biology influence this variation and that addition of biologic markers to AJCC staging improves determination of prognosis.

PATIENTS AND METHODS

We identified a cohort of 3,728 patients who underwent surgery as the first intervention between 1997 and 2006. A Cox proportional hazards model, with backward stepwise exclusion of factors and stratification on pathologic stage (PS), was used to test the significance of adding grade (G), lymphovascular invasion (L), estrogen receptor (ER) status (E), progesterone receptor (PR) status, combined ER and PR status (EP), or combined ER, PR, and human epidermal growth factor receptor 2 status (M). We assigned values of 0 to 2 to these disease-specific survival (DSS) -associated factors and assessed six different staging systems: PS, PS + G, PS + G L, PS + G E, PS + G EP, and PS + G M. We compared 5-year DSS rates, Akaike's information criterion (AIC), and Harrell's concordance index (C-index) between systems. Surveillance, Epidemiology, and End Results data were used as the external validation cohort (n = 26,711).

RESULTS

Median follow-up was 6.5 years, and 5-year DSS rate was 97.4%. The PS + G E status staging system was most precise, with a low AIC (1,931.9) and the highest C-index (0.80). PS + G E status was confirmed to stratify outcomes in internal bootstrapping samples and the external validation cohort.

CONCLUSION

Our results validate an improved breast cancer staging system that incorporates grade and ER status. We recommend that biologic markers be incorporated into revised versions of the AJCC staging system.

Predictive and prognostic molecular markers for cancer medicine

Over the last 10 years there has been an explosion of information about the molecular biology of cancer. A challenge in oncology is to translate this information into advances in patient care. While there are well-formed routes for translating new molecular information into drug therapy, the routes for translating new information into sensitive and specific diagnostic, prognostic and predictive tests are still being developed. Similarly, the science of using tumor molecular profiles to select clinical trial participants or to optimize therapy for individual patients is still in its infancy. This review will summarize the current technologies for predicting treatment response and prognosis in cancer medicine, and outline what the future may hold. It will also highlight the potential importance of methods that can integrate molecular, histopathological and clinical information into a synergistic understanding of tumor progression. While these possibilities are without doubt exciting, significant challenges remain if we are to implement them with a strong evidence base in a widely available and cost-effective manner.

Clinical implication of p53 overexpression in breast cancer patients younger than 50 years with a triple-negative subtype who undergo a modified radical mastectomy

OBJECTIVE

The purpose of this study was to identify the clinicopathological characteristics and prognostic value of p53 overexpression in breast cancer patients treated with a modified radical mastectomy.

METHODS

The medical records of 197 patients who had undergone modified radical mastectomy between January 1991 and December 2008 were reviewed retrospectively. Breast cancer subtype and p53 overexpression were investigated using immunohistochemistry and/or fluorescent in situ hybridization analysis of surgical specimens.

RESULTS

The median follow-up after the modified radical mastectomy was 56.1 months (range, 14.7-232.7). The median age was 47 years (range, 31-72). p53 overexpression was noted in 73 patients (37.1%). Breast cancer-specific death rate (P = 0.011), cancer progression (P = 0.024), distant metastasis (P = 0.015), hormone receptor negativity (P < 0.001) and human epidermal growth factor receptor 2 positivity (P = 0.017) were detected more frequently in patients with p53 overexpression. The overall survival rates were significantly lower in the p53-overexpression group than in the non-p53-overexpression group (P = 0.021, log-rank test). In the multivariate analysis, p53 overexpression showed the strongest prognostic significance in patients aged <50 years (P = 0.039) and with the triple-negative subtype (P = 0.023).

CONCLUSIONS

p53 overexpression correlated with breast cancer-specific death rates and adverse prognostic factors in patients treated with modified radical mastectomy. p53 overexpression might be a more reliable prognosticator in patients aged <50 years and with the triple-negative subtype. More effective systemic treatments might be warranted for these patients exhibiting p53 overexpression. Further validation is required to make more definite conclusions.

Molecular pathology of breast cancer: the journey from traditional practice toward embracing the complexity of a molecular classification

CONTEXT

Adenocarcinoma of the breast is the most frequent cancer affecting women in both developed and developing regions of the world. From the moment of clinical presentation until the time of pathologic diagnosis, patients affected by this disease will face daunting questions related to prognosis and treatment options. While improvements in targeted therapies have led to increased patient survival, these same advances have created the imperative to accurately stratify patients to achieve maximum therapeutic efficacy while minimizing side effects. In this evolving era of personalized medicine, there is an ever-increasing need to overcome the limitations of traditional diagnostic practice.

OBJECTIVE

To summarize the molecular diagnostics traditionally used to guide prognostication and treatment of breast carcinomas, to highlight published data on the molecular classification of these tumors, and to showcase molecular assays that will supplement traditional methods of categorizing the disease.

DATA SOURCES

A review of the literature covering the molecular diagnostics of breast carcinomas with a focus on the gene expression and array studies used to characterize the molecular signatures of the disease. Special emphasis is placed on summarizing evolving technologies useful in the diagnosis and characterization of breast carcinoma.

CONCLUSIONS

Available and emerging molecular resources will allow pathologists to provide superior diagnostic, prognostic, and predictive information about individual breast carcinomas. These advances should translate into earlier identification and tailored therapy and should ultimately improve outcome for patients affected by this disease.

Molecular clustering based on ERα and EIG121 predicts survival in high-grade serous carcinoma of the ovary/peritoneum

Assessment of estrogen receptor (ER) expression by immunohistochemistry has yielded inconsistent results as a prognostic indicator in ovarian carcinoma. In breast and endometrial carcinomas, panels of estrogen-induced genes have shown improved prognostic capability over the use of ER immunohistochemistry alone. For both breast and endometrial cancers, overexpression of estrogen-induced genes is associated with better prognosis. We hypothesized that analysis of a panel of estrogen-induced genes can predict the outcome in ovarian carcinoma and potentially differentiate between tumors of varying hormonal responsiveness. From a cohort of 219 women undergoing ovarian cancer surgery from 2004 to 2007, 83 patients were selected for inclusion. All patients had advanced stage ovarian/primary peritoneal high-grade serous carcinoma and underwent primary surgical debulking, followed by adjuvant treatment with platinum and taxane agents. The expression of ERα and six genes known to be induced by estrogen in the female reproductive tract (namely EIG121, sFRP1, sFRP4, RALDH2, PR, and IGF-1) was measured using quantitative RT-PCR. Unsupervised cluster analyses were used to categorize patients as high or low gene expressors. Gene expression results were then compared with those for ER immunohistochemistry. Clusters were compared using χ(2) analyses, and Cox proportional hazards models were used to evaluate survival outcomes. The median follow-up time was 38.7 months (range: 1-68). A cluster defined by EIG121 and ERα segregated tumors into distinct groups of high and low gene expressors. Shorter overall survival (OS) was associated with high gene expression (HR 2.84 (1.11-7.30), P=0.03), even after adjustment for other covariates. No difference in ER immunohistochemistry expression was noted between gene clusters. In contrast to other hormonally driven cancers, high expression of ERα and the estrogen-induced gene EIG121 predicts shorter OS in patients with high-grade serous ovarian carcinoma. Such a biomarker panel may potentially be used to guide management with estrogen antagonists in this patient population.

Applicability of RNA standards for evaluating RT-qPCR assays and platforms

The availability of diverse RT-qPCR assay formats and technologies hinder comparability of data between platforms. Reference standards to facilitate platform evaluation and comparability are needed. We have explored using universal RNA standards for comparing the performance of a novel qPCR platform (Fluidigm® BioMark™) against the widely used ABI 7900HT system. Our results show that such standards may form part of a toolkit to evaluate the key performance characteristics of platforms.

Molecular markers for the diagnosis and management of ductal carcinoma in situ

Ductal carcinoma in situ (DCIS) is a heterogeneous group of lesions reflecting the proliferation of malignant cells within the ducts of the breast without invasion through the basement membrane. Numerous studies analyzing the molecular profiles of DCIS using genome-wide unbiased and candidate gene approaches have been conducted with the aim of identifying clinically useful markers that would predict the risk of progression to invasion. Results of these investigations defined the heterogeneity of DCIS at the molecular level, but a gene signature predictive of invasive progression has not been identified. Major diagnostic criteria that differentiate DCIS from invasive cancer are the presence of intact basement membrane and myoepithelial cell layer. Based on this, perturbation of normal myoepithelial cell differentiation has been proposed to explain progression to invasion. Comprehensive molecular studies analyzing large cohorts of DCIS with long-term clinical follow-up are necessary to resolve the many remaining questions.

Genome-wide gene expression profiling of formalin-fixed paraffin-embedded breast cancer core biopsies using microarrays

The routine workflow for invasive cancer diagnostics includes biopsy processing by formalin fixation and paraffin embedding. It has been shown only recently that this kind of sample can be used for gene expression analysis with microarrays. To support this view, the authors conducted a microarray study using formalin-fixed paraffin-embedded (FFPE) core needle biopsies from breast cancers. Typically, for the 3'-biased chip type that was used, the probe sets interrogate sequences near the poly-A-tail of the transcripts, and this kind of probe turned out to be suitable to measure RNA levels in FFPE biopsies. For ER and HER2, the authors observed strong correlations between RNA levels and protein expression (p = 0.000003 and p = 0.0022). ER and HER2 classification of the biopsies by the RNA levels was feasible with high sensitivity and specificity (AUROC = 0.93 and AUROC = 0.96). Furthermore, a signature of 346 genes was identified that correlated with ER and a signature of 528 genes that correlated with HER2 protein status. Many of these genes (ER: 63%) could be confirmed by analysis of gene expression data from frozen tissues. The findings support the notion that clinically relevant information can be gained from microarray analyses of FFPE cancer biopsies. This opens new opportunities for biomarker detection studies and the integration of microarrays into the workflow of cancer diagnostics.

Bayesian ensemble methods for survival prediction in gene expression data

MOTIVATION

We propose a Bayesian ensemble method for survival prediction in high-dimensional gene expression data. We specify a fully Bayesian hierarchical approach based on an ensemble 'sum-of-trees' model and illustrate our method using three popular survival models. Our non-parametric method incorporates both additive and interaction effects between genes, which results in high predictive accuracy compared with other methods. In addition, our method provides model-free variable selection of important prognostic markers based on controlling the false discovery rates; thus providing a unified procedure to select relevant genes and predict survivor functions.

RESULTS

We assess the performance of our method several simulated and real microarray datasets. We show that our method selects genes potentially related to the development of the disease as well as yields predictive performance that is very competitive to many other existing methods.

AVAILABILITY

http://works.bepress.com/veera/1/.

A comparison of PAM50 intrinsic subtyping with immunohistochemistry and clinical prognostic factors in tamoxifen-treated estrogen receptor-positive breast cancer

PURPOSE

To compare clinical, immunohistochemical (IHC), and gene expression models of prognosis applicable to formalin-fixed, paraffin-embedded blocks in a large series of estrogen receptor (ER)-positive breast cancers from patients uniformly treated with adjuvant tamoxifen.

EXPERIMENTAL DESIGN

Quantitative real-time reverse transcription-PCR (qRT-PCR) assays for 50 genes identifying intrinsic breast cancer subtypes were completed on 786 specimens linked to clinical (median follow-up, 11.7 years) and IHC [ER, progesterone receptor (PR), HER2, and Ki67] data. Performance of predefined intrinsic subtype and risk-of-relapse scores was assessed using multivariable Cox models and Kaplan-Meier analysis. Harrell's C-index was used to compare fixed models trained in independent data sets, including proliferation signatures.

RESULTS

Despite clinical ER positivity, 10% of cases were assigned to nonluminal subtypes. qRT-PCR signatures for proliferation genes gave more prognostic information than clinical assays for hormone receptors or Ki67. In Cox models incorporating standard prognostic variables, hazard ratios for breast cancer disease-specific survival over the first 5 years of follow-up, relative to the most common luminal A subtype, are 1.99 [95% confidence interval (CI), 1.09-3.64] for luminal B, 3.65 (95% CI, 1.64-8.16) for HER2-enriched subtype, and 17.71 (95% CI, 1.71-183.33) for the basal-like subtype. For node-negative disease, PAM50 qRT-PCR-based risk assignment weighted for tumor size and proliferation identifies a group with >95% 10-year survival without chemotherapy. In node-positive disease, PAM50-based prognostic models were also superior.

CONCLUSION

The PAM50 gene expression test for intrinsic biological subtype can be applied to large series of formalin-fixed, paraffin-embedded breast cancers, and gives more prognostic information than clinical factors and IHC using standard cut points.

Diagnosis of metastatic neoplasms: molecular approaches for identification of tissue of origin

CONTEXT

Tumors of uncertain or unknown origin are estimated to constitute 3% to 5% of all metastatic cancer cases. Patients with these types of tumors show worse outcomes when compared to patients in which a primary tumor is identified. New molecular tests that identify molecular signatures of a tissue of origin have become available.

OBJECTIVE

To review the literature on existing molecular approaches to the diagnosis of metastatic tumors of uncertain origin and discuss the current status and future developments in this area.

DATA SOURCES

Published peer-reviewed literature, available information from medical organizations (National Comprehensive Cancer Network), and other publicly available information from tissue-of-origin test providers and/or manufacturers.

CONCLUSIONS

Molecular tests for tissue-of-origin determination in metastatic tumors are available and have the potential to significantly impact patient management. However, available validation data indicate that not all tests have shown adequate performance characteristics for clinical use. Pathologists and oncologists should carefully evaluate claims for accuracy and clinical utility for tissue-of-origin tests before using test results in patient management. The personalized medicine revolution includes the use of molecular tools for identification/confirmation of the site of origin for metastatic tumors, and in the future, this strategy might also be used to determine specific therapeutic approaches.

Primary breast carcinoma: association of mammographic calcifications with osteopontin expression

PURPOSE

To evaluate the osteopontin (OPN) protein expression levels in breast carcinomas to determine if they correlate with mammographic appearances such as calcifications.

MATERIALS AND METHODS

This retrospective study was institutional review board approved. Informed consent was obtained from patients. Clinical history, histopathologic findings, mammographic features, and OPN expression as determined with immunohistochemistry results were evaluated in 141 women with breast cancer. The median age of patients was 53 years (range, 29-82 years). Mammographic features and clinicopathologic characteristics were correlated with tumor OPN expression. chi(2) And Fisher exact tests were used to evaluate the association of OPN expression with mammographic and clinicopathologic features.

RESULTS

Calcifications on mammograms (P = .012), spiculated margins of mass on mammograms (P = .02), "triple-negative" (ie, cancer that is estrogen receptor, progesterone receptor, and human epidermal growth factor receptor negative) phenotype (P = .02), and lymph node metastasis (P < .0001) were significantly associated with OPN status. In contrast to OPN-negative tumors, OPN-positive tumors were more likely to have spiculated margins (57.6% vs 9.2%), to be associated with calcifications (54.3% vs 30.6%), to be a triple-negative phenotype (26% vs 8.1%), and to have axillary lymph node metastasis (81.5% vs 38.8%). Most calcifications were of pleomorphic morphology (60.4% vs 11.8%, P = .046).

CONCLUSION

OPN could play a role in the formation of calcifications that often are associated with breast cancer.

GeneSigDB--a curated database of gene expression signatures

The primary objective of most gene expression studies is the identification of one or more gene signatures; lists of genes whose transcriptional levels are uniquely associated with a specific biological phenotype. Whilst thousands of experimentally derived gene signatures are published, their potential value to the community is limited by their computational inaccessibility. Gene signatures are embedded in published article figures, tables or in supplementary materials, and are frequently presented using non-standard gene or probeset nomenclature. We present GeneSigDB (http://compbio.dfci.harvard.edu/genesigdb) a manually curated database of gene expression signatures. GeneSigDB release 1.0 focuses on cancer and stem cells gene signatures and was constructed from more than 850 publications from which we manually transcribed 575 gene signatures. Most gene signatures (n = 560) were successfully mapped to the genome to extract standardized lists of EnsEMBL gene identifiers. GeneSigDB provides the original gene signature, the standardized gene list and a fully traceable gene mapping history for each gene from the original transcribed data table through to the standardized list of genes. The GeneSigDB web portal is easy to search, allows users to compare their own gene list to those in the database, and download gene signatures in most common gene identifier formats.