The MINDACT trial: the first prospective clinical validation of a genomic tool

Enhancing clinical decision support with genomic tools in breast cancer: A Scottish perspective

INTRODUCTION

The Oncotype DX Breast RS test has been adopted in Scotland and has been the subject of a large population-based study by a Scottish Consensus Group to assess the uptake of the recurrence score (RS), evaluate co-variates associated with the RS and to analyse the effect it may have had on clinical practice.

MATERIALS & METHODS

Pan-Scotland study between August 2018-August 2021 evaluating 833 patients who had a RS test performed as part of their diagnostic pathway. Data was extracted retrospectively from electronic records and analysis conducted to describe change in chemotherapy administration (by direct comparison with conventional risk assessment tools), and univariate/multivariate analysis to assess relationship between covariates and the RS.

RESULTS

Chemotherapy treatment was strongly influenced by the RS (p < 0.001). Only 30 % of patients received chemotherapy treatment in the intermediate and high risk PREDICT groups, where chemotherapy is considered. Additionally, 55.5 % of patients with a high risk PREDICT had a low RS and did not receive chemotherapy. There were 17 % of patients with a low risk PREDICT but high RS who received chemotherapy. Multivariate regression analysis showed the progesterone receptor Allred score (PR score) to be a strong independent predictor of the RS, with a negative PR score being associated with high RS (OR 4.49, p < 0.001). Increasing grade was also associated with high RS (OR 3.81, p < 0.001). Classic lobular pathology was associated with a low RS in comparison to other tumour pathology (p < 0.01). Nodal disease was associated with a lower RS (p = 0.012) on univariate analysis, with menopausal status (p = 0.43) not influencing the RS on univariate or multivariate analysis.

CONCLUSIONS

Genomic assays offer the potential for risk-stratified decision making regarding the use of chemotherapy. They can help reduce unnecessary chemotherapy treatment and identify a subgroup of patients with more adverse genomic tumour biology. A recent publication by Health Improvement Scotland (HIS) has updated guidance on use of the RS test for NHS Scotland. It suggests to limit its use to the intermediate risk PREDICT group. Our study shows the impact of the RS test in the low and high risk PREDICT groups. The implementation across Scotland has resulted in a notable shift in practice, leading to a significant reduction in chemotherapy administration in the setting of high risk PREDICT scores returning low risk RS. There has also been utility for the test in the low risk PREDICT group to detect a small subgroup with a high RS. We have found the PR score to have a strong independent association with high risk RS. This finding was not evaluated by the key RS test papers, and the potential prognostic information provided by the PR score as a surrogate biomarker is an outstanding question that requires more research to validate.

Using MammaPrint on core needle biopsy to guide the need for axillary staging during breast surgery

BACKGROUND

At present, the only opportunity to omit axillary staging is with Choosing Wisely criteria for women ages >70 y with cT1 2N0 estrogen receptor-positive/human epidermal growth factor receptor 2-negative breast cancer. However, many women are diagnosed when pathologic node status-negative, raising the question of additional opportunities to omit sentinel lymph node biopsy. We sought to investigate the association between MammaPrint, a genomic test that estimates estrogen receptor-positive breast cancer recurrence risk, and pathologic node status, with the aim that low-risk MammaPrint could be considered for omission of sentinel lymph node biopsy if associated with pathologic node status-negative.

METHODS

A single-institution database was queried for all women with cT1 2N0 estrogen receptor-positive/human epidermal growth factor receptor 2-negative invasive breast cancer with breast surgery as their first treatment and MammaPrint performed from 2020 to 2021. Patient and tumor factors, including MammaPrint score, were compared with axillary node status for correlation.

RESULTS

A total of 668 women met inclusion criteria, with a median age of 66 y. MammaPrint was low-risk luminal A in 481 (72%) and high-risk luminal B in 187 (28%). At the time of breast surgery, 588 (88%) had sentinel lymph node biopsy, 27 (4%) had axillary lymph node dissection, and 53 (7.9%) had no axillary staging. Most women in both the pathologic node status-negative and pathologic node status-positive cohorts had low-risk MammaPrint (355 [73.3%] pathologic node status-negative vs 91 [69.5%] pathologic node status-positive), and women with low-risk MammaPrint did not have a significantly lower risk of pathologic node status-positive (P = .377).

CONCLUSION

Low-risk MammaPrint does not predict lower risk of pathologic node status-positive breast cancer. Based on our results, genomic testing does not appear to provide additional personalization for the ability to omit sentinel lymph node biopsy for patients outside of the Choosing Wisely guidelines.

NCAPH drives breast cancer progression and identifies a gene signature that predicts luminal a tumour recurrence

BACKGROUND

Luminal A tumours generally have a favourable prognosis but possess the highest 10-year recurrence risk among breast cancers. Additionally, a quarter of the recurrence cases occur within 5 years post-diagnosis. Identifying such patients is crucial as long-term relapsers could benefit from extended hormone therapy, while early relapsers might require more aggressive treatment.

METHODS

We conducted a study to explore non-structural chromosome maintenance condensin I complex subunit H's (NCAPH) role in luminal A breast cancer pathogenesis, both in vitro and in vivo, aiming to identify an intratumoural gene expression signature, with a focus on elevated NCAPH levels, as a potential marker for unfavourable progression. Our analysis included transgenic mouse models overexpressing NCAPH and a genetically diverse mouse cohort generated by backcrossing. A least absolute shrinkage and selection operator (LASSO) multivariate regression analysis was performed on transcripts associated with elevated intratumoural NCAPH levels.

RESULTS

We found that NCAPH contributes to adverse luminal A breast cancer progression. The intratumoural gene expression signature associated with elevated NCAPH levels emerged as a potential risk identifier. Transgenic mice overexpressing NCAPH developed breast tumours with extended latency, and in Mouse Mammary Tumor Virus (MMTV)-NCAPHErbB2 double-transgenic mice, luminal tumours showed increased aggressiveness. High intratumoural Ncaph levels correlated with worse breast cancer outcome and subpar chemotherapy response. A 10-gene risk score, termed Gene Signature for Luminal A 10 (GSLA10), was derived from the LASSO analysis, correlating with adverse luminal A breast cancer progression.

CONCLUSIONS

The GSLA10 signature outperformed the Oncotype DX signature in discerning tumours with unfavourable outcomes, previously categorised as luminal A by Prediction Analysis of Microarray 50 (PAM50) across three independent human cohorts. This new signature holds promise for identifying luminal A tumour patients with adverse prognosis, aiding in the development of personalised treatment strategies to significantly improve patient outcomes.

Gene expression profiles in clinically T1-2N0 ER+HER2- breast cancer patients treated with breast-conserving therapy: their added value in case sentinel lymph node biopsy is not performed

PURPOSE

Omitting sentinel lymph node biopsy (SLNB) in breast cancer treatment results in patients with unknown positive nodal status and potential risk for systemic undertreatment. This study aimed to investigate whether gene expression profiles (GEPs) can lower this risk in cT1-2N0 ER+ HER2- breast cancer patients treated with BCT.

METHODS

Patients were included if diagnosed between 2011 and 2017 with cT1-2N0 ER+ HER2- breast cancer, treated with BCT and SLNB, and in whom GEP was applied. Adjuvant chemotherapy recommendations based on clinical risk status (Dutch breast cancer guideline of 2020 versus PREDICT v2.1) with and without knowledge on SLNB outcome were compared to GEP outcome. We examined missing adjuvant chemotherapy indications, and the number of GEPs needed to identify one patient at risk for systemic undertreatment.

RESULTS

Of 3585 patients, 2863 (79.9%) had pN0 and 722 (20.1%) pN + disease. Chemotherapy was recommended in 1354 (37.8% guideline-2020) and 1888 patients (52.7% PREDICT). Eliminating SLNB outcome (n = 722) resulted in omission of chemotherapy recommendation in 475 (35.1% guideline-2020) and 412 patients (21.8% PREDICT). GEP revealed genomic high risk in 126 (26.5% guideline-2020) and 82 patients (19.9% PREDICT) in case of omitted chemotherapy recommendation in the absence of SLNB. Extrapolated to the whole group, this concerns 3.5% and 2.3%, respectively, resulting in the need for 28-44 GEPs to identify one patient at risk for systemic undertreatment.

CONCLUSION

If no SLNB is performed, clinical risk status according to the guideline of 2020 and PREDICT predicts a very low risk for systemic undertreatment. The number of GEPs needed to identify one patient at risk for undertreatment does not justify its standard use.

The variability of aggressiveness of grade 1 breast cancer

BACKGROUND

Grade 1 breast cancer represents the lowest grade of invasive breast cancer and is associated with a low risk of recurrence and distant metastasis. However, when grade 1 breast cancer is associated with lymph node involvement, the prognosis may be worse than that of grade 1 breast cancer without lymph node involvement.

METHOD

The study population included all patients who were managed in our institution between January 1, 2007 and December 31, 2013 for grade 1 breast cancer . We compared patients who had lymph node involvement to those who had no lymph node involvement.

RESULTS

During the study period 291 grade 1 carcinomas were included of which 23% had associated positive lymph node involvement. Overall survival did not differ significantly between patients without lymph node involvement and those with lymph node involvement, nor was there a significant difference in the risk of local recurrence free survival. However, a significant difference was found in survival without distant metastasis with a significant level of a p at 0.029.

CONCLUSION

Our findings confirm that tumor size and LVSI are strong predictors of axillary lymph node involvement, which is a key determinant of distant metastasis-free survival.

NCAPH Drives Breast Cancer Progression and Identifies a Gene Signature that Predicts Luminal A Tumor Recurrence

Despite their generally favorable prognosis, luminal A tumors paradoxically pose the highest ten-year recurrence risk among breast cancers. From those that relapse, a quarter of them do it within five years after diagnosis. Identifying such patients is crucial, as long-term relapsers could benefit from extended hormone therapy, whereas early relapsers may require aggressive treatment. In this study, we demonstrate that NCAPH plays a role in the pathogenesis of luminal A breast cancer, contributing to its adverse progression in vitro and in vivo. Furthermore, we reveal that a signature of intratumoral gene expression, associated with elevated levels of NCAPH, serves as a potential marker to identify patients facing unfavorable progression of luminal A breast cancer. Indeed, transgenic mice overexpressing NCAPH generated breast tumors with long latency, and in MMTV-NCAPH/ErbB2+ double-transgenic mice, the luminal tumors formed were more aggressive. In addition, high intratumoral levels of Ncaph were associated with worse breast cancer evolution and poor response to chemotherapy in a cohort of genetically heterogeneous transgenic mice generated by backcrossing. In this cohort of mice, we identified a series of transcripts associated with elevated intratumoral levels of NCAPH, which were linked to adverse progression of breast cancer in both mice and humans. Utilizing the Least Absolute Shrinkage and Selection Operator (LASSO) multivariate regression analysis on this series of transcripts, we derived a ten-gene risk score. This score is defined by a gene signature (termed Gene Signature for Luminal A 10 or GSLA10) that correlates with unfavorable progression of luminal A breast cancer. The GSLA10 signature surpassed the Oncotype DX signature in discerning tumors with unfavorable outcomes (previously categorized as Luminal A by PAM50) across three independent human cohorts. This GSLA10 signature aids in identifying patients with Luminal A tumors displaying adverse prognosis, who could potentially benefit from personalized treatment strategies.

Deciphering Phenotypes from Protein Biomarkers for Translational Research with PIPER

Liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM) has widespread clinical use for detection of inborn errors of metabolism, therapeutic drug monitoring, and numerous other applications. This technique detects proteolytic peptides as surrogates for protein biomarker expression, mutation, and post-translational modification in individual clinical assays and in cancer research with highly multiplexed quantitation across biological pathways. LC-MRM for protein biomarkers must be translated from multiplexed research-grade panels to clinical use. LC-MRM panels provide the capability to quantify clinical biomarkers and emerging protein markers to establish the context of tumor phenotypes that provide highly relevant supporting information. An application to visualize and communicate targeted proteomics data will empower translational researchers to move protein biomarker panels from discovery to clinical use. Therefore, we have developed a web-based tool for targeted proteomics that provides pathway-level evaluations of key biological drivers (e.g., EGFR signaling), signature scores (representing phenotypes) (e.g., EMT), and the ability to quantify specific drug targets across a sample cohort. This tool represents a framework for integrating summary information, decision algorithms, and risk scores to support Physician-Interpretable Phenotypic Evaluation in R (PIPER) that can be reused or repurposed by other labs to communicate and interpret their own biomarker panels.

Blood-Based mRNA Tests as Emerging Diagnostic Tools for Personalised Medicine in Breast Cancer

Molecular diagnostic tests help clinicians understand the underlying biological mechanisms of their patients' breast cancer (BC) and facilitate clinical management. Several tissue-based mRNA tests are used routinely in clinical practice, particularly for assessing the BC recurrence risk, which can guide treatment decisions. However, blood-based mRNA assays have only recently started to emerge. This review explores the commercially available blood mRNA diagnostic assays for BC. These tests enable differentiation of BC from non-BC subjects (Syantra DX, BCtect), detection of small tumours <10 mm (early BC detection) (Syantra DX), detection of different cancers (including BC) from a single blood sample (multi-cancer blood test Aristotle), detection of BC in premenopausal and postmenopausal women and those with high breast density (Syantra DX), and improvement of diagnostic outcomes of DNA testing (variant interpretation) (+RNAinsight). The review also evaluates ongoing transcriptomic research on exciting possibilities for future assays, including blood transcriptome analyses aimed at differentiating lymph node positive and negative BC, distinguishing BC and benign breast disease, detecting ductal carcinoma in situ, and improving early detection further (expression changes can be detected in blood up to eight years before diagnosing BC using conventional approaches, while future metastatic and non-metastatic BC can be distinguished two years before BC diagnosis).

Construction of a lncRNA-mediated ceRNA network and a genomic-clinicopathologic nomogram to predict survival for breast cancer patients

Breast cancer (BC) is the most common cancer among women and a leading cause of cancer-related deaths worldwide. The diagnosis of early patients and the prognosis of advanced patients have not improved over the past several decades. The purpose of the present study was to identify the lncRNA-related genes based on ceRNA network and construct a credible model for prognosis in BC. Based on The Cancer Genome Atlas (TCGA) database, prognosis-related differently expressed genes (DEGs) and a lncRNA-associated ceRNA regulatory network were obtained in BC. The patients were randomly divided into a training group and a testing group. A ceRNA-related prognostic model as well as a nomogram was constructed for further study. A total of 844 DElncRNAs, 206 DEmiRNAs and 3295 DEmRNAs were extracted in BC, and 12 RNAs (HOTAIR, AC055854.1, ST8SIA6-AS1, AC105999.2, hsa-miR-1258, hsa-miR-7705, hsa-miR-3662, hsa-miR-4501, CCNB1, UHRF1, SPC24 and SHCBP1) among them were recognized for the construction of a prognostic risk model. Patients were then assigned to high-risk and low-risk groups according to the risk score. The Kaplan-Meier (K-M) analysis demonstrated that the high-risk group was closely associated with poor prognosis. The predictive nomogram combined with clinical features showed performance in clinical practice. In a nutshell, our ceRNA-related gene model and the nomogram graph are accurate and reliable tools for predicting prognostic outcomes of BC patients, and may make great contributions to modern precise medicine.

Anesthetics and Long Term Cancer Outcomes: May Epigenetics Be the Key for Pancreatic Cancer?

Knowledge shows a divergence of results between preclinical and clinical studies regarding anesthesia and postoperative progression of cancer. While laboratory and animal data from then 2000s onwards raised much enthusiasm in this field of research leading to several clinical investigations worldwide, data from randomized trials seem to have killed off hope for many scientists. However several aspects of the actual knowledge should be reevaluated and there is space for new strategies of investigation. In this paper, we perform a critical review of actual knowledge and propose new research strategies with a special focus on anesthetic management and repurposed anesthetic adjuvants for pancreatic cancer.

Prediction of Breast Cancer Recurrence Using a Deep Convolutional Neural Network Without Region-of-Interest Labeling

Purpose

The present study aimed to assign a risk score for breast cancer recurrence based on pathological whole slide images (WSIs) using a deep learning model.

Methods

A total of 233 WSIs from 138 breast cancer patients were assigned either a low-risk or a high-risk score based on a 70-gene signature. These images were processed into patches of 512x512 pixels by the PyHIST tool and underwent color normalization using the Macenko method. Afterward, out of focus and pixelated patches were removed using the Laplacian algorithm. Finally, the remaining patches (n=294,562) were split into 3 parts for model training (50%), validation (7%) and testing (43%). We used 6 pretrained models for transfer learning and evaluated their performance using accuracy, precision, recall, F1 score, confusion matrix, and AUC. Additionally, to demonstrate the robustness of the final model and its generalization capacity, the testing set was used for model evaluation. Finally, the GRAD-CAM algorithm was used for model visualization.

Results

Six models, namely VGG16, ResNet50, ResNet101, Inception_ResNet, EfficientB5, and Xception, achieved high performance in the validation set with an overall accuracy of 0.84, 0.85, 0.83, 0.84, 0.87, and 0.91, respectively. We selected Xception for assessment of the testing set, and this model achieved an overall accuracy of 0.87 with a patch-wise approach and 0.90 and 1.00 with a patient-wise approach for high-risk and low-risk groups, respectively.

Conclusions

Our study demonstrated the feasibility and high performance of artificial intelligence models trained without region-of-interest labeling for predicting cancer recurrence based on a 70-gene signature risk score.

A Novel Three-Gene Score as a Predictive Biomarker for Pathologically Complete Response after Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer

Although triple-negative breast cancer (TNBC) typically responds better to neoadjuvant chemotherapy (NAC) compared to the other subtypes, a pathological complete response (pCR) is achieved in less than half of the cases. We established a novel three-gene score using genes based on the E2F target gene set that identified pCR after NAC, which showed robust performance in both training and validation cohorts (total of n = 3862 breast cancer patients). We found that the three-gene score was elevated in TNBC compared to the other subtypes. A high score was associated with Nottingham histological grade 3 in TNBC. Across multiple cohorts, high-score TNBC enriched not only E2F targets but also G2M checkpoint and mitotic spindle, which are all cell proliferation-related gene sets. High-score TNBC was associated with homologous recombination deficiency, high mutation load, and high infiltration of Th1, Th2, and gamma-delta T cells. However, the score did not correlate with drug sensitivity for paclitaxel, 5-fluorouracil, cyclophosphamide, and doxorubicin in TNBC human cell lines. High-score TNBC was significantly associated with a high rate of pCR not only in the training cohort but also in the validation cohorts. High-score TNBC was significantly associated with better survival in patients who received chemotherapy but not in patients who did not receive chemotherapy. The three-gene score is associated with a high mutation rate, immune cell infiltration, and predicts response to NAC in TNBC.

Validation of the revised 8th AJCC breast cancer clinical prognostic staging system: analysis of 5321 cases from a single institution

The anatomic stage groups (ASG) have been arguably the most powerful in predicting breast cancer (BC) outcomes. Recognizing the prognostic influence of histologic grade and receptor status, the 8th AJCC mandates their incorporation into the newly established prognostic stage groups (PSG). This staging scheme was subsequently revised to provide pathological and clinical prognostic stage tables (PPSG/CPSG) due to its incapability to categorize a significant subset of BCs, with the former only used for patients having surgical resection as the initial treatment, and the latter for all patients. Given the increasingly used neoadjuvant therapy, PPSG cannot be assigned in a significant proportion of higher staged BCs. In this study, we validated the CPSG in a cohort of 5321 BCs. Compared to ASG, the application of CPSG resulted in assigning 16.1% and 27.2% of cases to a higher or a lower stage group in non-stage IV BCs, respectively. The changes were seen mostly frequently in ASG IB, followed by IIIC, IIB, IIA, IIIA, IIIB, and IA. In 7.9% of cases, the assigned CPSG changed more than one stage group from the ASG. CPSG provided an improved overall discriminating power in predicting BC-specific survival when compared to ASG. Pairwise comparison using the Cox proportional hazard model demonstrated further advantages for CPSG as the latter showed a significant difference in all categories when compared to their proximate groups, except IIA vs. IB and IIIA vs. IIIB. In contrast, a significantly different hazard was only seen when comparing IIB vs. IIA, IIIA vs. IIB, and IV vs. IIIC for ASG. Thus, the revised 8th AJCC CPSG provided a superior overall staging scheme for predicting prognostic outcomes in BC patients receiving standard of care treatment. Further validation using the available data with larger populations and longer follow-up may be needed to refine and improve this table.

Current Achievements and Applications of Transcriptomics in Personalized Cancer Medicine

Over the last decades, transcriptome profiling emerged as one of the most powerful approaches in oncology, providing prognostic and predictive utility for cancer management. The development of novel technologies, such as revolutionary next-generation sequencing, enables the identification of cancer biomarkers, gene signatures, and their aberrant expression affecting oncogenesis, as well as the discovery of molecular targets for anticancer therapies. Transcriptomics contribute to a change in the holistic understanding of cancer, from histopathological and organic to molecular classifications, opening a more personalized perspective for tumor diagnostics and therapy. The further advancement on transcriptome profiling may allow standardization and cost reduction of its analysis, which will be the next step for transcriptomics to become a canon of contemporary cancer medicine.

The Potential Use of Tumour-Based Prognostic and Predictive Tools in Older Women with Primary Breast Cancer: A Narrative Review

A move is under way towards personalised cancer treatment, where tumour biology of an individual patient is examined to give unique predictive and prognostic information. This is extremely important in the setting of older women, who have treatment-specific goals which may differ from their younger counterparts, and may include conservation of quality of life rather than curative intent of treatment. One method employed to assist with this is the use of tumour-based prognostic and predictive tools. This article explores six of the most common tumour-based tools currently available on the market: MammaPrint, Oncotype DX, Mammostrat, Prosigna, EndoPredict, IHC4. The article discusses the creation and validation of these tools, their use and validation in older women, and future directions in the field. With the exception of Oncotype Dx, which has also been licensed for prediction of response from adjuvant chemotherapy, these tools have been licensed for use as prognostic tools only, mainly in the setting of adjuvant therapy following surgery. The evidence base for use in older women is strongest for Mammostrat and PAM50, although overall the evidence is much weaker than that in younger women. Where older women have been included in validation studies, this is often in small numbers, or the exact proportion of older women is unknown. In practice, all six of the tools are recommended to be utilised on surgical excision specimens, as well as in core needle biopsy (CNB) specimens in all of the tools except Mammostrat. This is extremely important in the setting of older women, of whom a large proportion do not undergo surgery. The suggested nature of the sample is formalin-fixed paraffin-embedded in all the tools except MammaPrint, which can also be performed on fresh-frozen samples. Future development of prognostic tools in older women with breast cancer should focus on treatment dilemmas specific to this population. This includes the decision of primary treatment between surgery or endocrine therapy and decisions regarding adjuvant therapy, in particular, chemotherapy.

Research-based PAM50 signature and long-term breast cancer survival

Purpose

Multi-gene signatures provide biological insight and risk stratification in breast cancer. Intrinsic molecular subtypes defined by mRNA expression of 50 genes (PAM50) are prognostic in hormone-receptor positive postmenopausal breast cancer. Yet, for 25–40% in the PAM50 intermediate risk group, long-term risk remains uncertain. Our study aimed to (i) test the long-term prognostic value of the PAM50 signature in pre- and post-menopausal breast cancer; (ii) investigate if the PAM50 model could be improved by addition of other mRNAs implicated in oncogenesis.

Methods

We used archived FFPE samples from 1723 breast cancer survivors; high quality reads were obtained on 1253 samples. Transcript expression was quantified using a custom codeset with probes for > 100 targets. Cox models assessed gene signatures for breast cancer relapse and survival.

Results

Over 15 + years of follow-up, PAM50 subtypes were (P < 0.01) associated with breast cancer outcomes after accounting for tumor stage, grade and age at diagnosis. Results did not differ by menopausal status at diagnosis. Women with Luminal B (versus Luminal A) subtype had a > 60% higher hazard. Addition of a 13-gene hypoxia signature improved prognostication with > 40% higher hazard in the highest vs lowest hypoxia tertiles.

Conclusions

PAM50 intrinsic subtypes were independently prognostic for long-term breast cancer survival, irrespective of menopausal status. Addition of hypoxia signatures improved risk prediction. If replicated, incorporating the 13-gene hypoxia signature into the existing PAM50 risk assessment tool, may refine risk stratification and further clarify treatment for breast cancer.

Electronic supplementary material

The online version of this article (10.1007/s10549-019-05446-y) contains supplementary material, which is available to authorized users.

Panoptic View of Prognostic Models for Personalized Breast Cancer Management

The efforts to personalize treatment for patients with breast cancer have led to a focus on the deeper characterization of genotypic and phenotypic heterogeneity among breast cancers. Traditional pathology utilizes microscopy to profile the morphologic features and organizational architecture of tumor tissue for predicting the course of disease, and is the first-line set of guiding tools for customizing treatment decision-making. Currently, clinicians use this information, combined with the disease stage, to predict patient prognosis to some extent. However, tumoral heterogeneity stubbornly persists among patient subgroups delineated by these clinicopathologic characteristics, as currently used methodologies in diagnostic pathology lack the capability to discern deeper genotypic and subtler phenotypic differences among individual patients. Recent advancements in molecular pathology, however, are poised to change this by joining forces with multiple-omics technologies (genomics, transcriptomics, epigenomics, proteomics, and metabolomics) that provide a wealth of data about the precise molecular complement of each patient's tumor. In addition, these technologies inform the drivers of disease aggressiveness, the determinants of therapeutic response, and new treatment targets in the individual patient. The tumor architecture information can be integrated with the knowledge of the detailed mutational, transcriptional, and proteomic phenotypes of cancer cells within individual tumors to derive a new level of biologic insight that enables powerful, data-driven patient stratification and customization of treatment for each patient, at each stage of the disease. This review summarizes the prognostic and predictive insights provided by commercially available gene expression-based tests and other multivariate or clinical -omics-based prognostic/predictive models currently under development, and proposes a more inclusive multiplatform approach to tackling the challenging heterogeneity of breast cancer to individualize its management. "The future is already here-it's just not very evenly distributed."-William Ford Gibson.

Identification of risk in cutaneous melanoma patients: Prognostic and predictive markers

New therapeutic modalities for melanoma promise benefit in selected individuals. Efficacy appears greater in patients with lower tumor burden, suggesting an important role for risk-stratified surveillance. Robust predictive markers might permit optimization of agent to patient, while low-risk prognostic markers might guide more conservative management. This review evaluates protein, gene, and multiplexed marker panels that may contribute to better risk assessment and improved management of patients with cutaneous melanoma.

Molecular determinants of post-mastectomy breast cancer recurrence

Breast cancer (BC) adjuvant therapy after mastectomy in the setting of 1-3 positive lymph nodes has been controversial. This retrospective Translational Breast Cancer Research Consortium study evaluated molecular aberrations in primary cancers associated with locoregional recurrence (LRR) or distant metastasis (DM) compared to non-recurrent controls. We identified 115 HER2 negative, therapy naïve, T 1-3 and N 0-1 BC patients treated with mastectomy but no post-mastectomy radiotherapy. This included 32 LRR, 34 DM, and 49 controls. RNAseq was performed on primary tumors in 110 patients; with no difference in RNA profiles between patients with LRR, DM, or controls. DNA analysis on 57 primary tumors (17 LRR, 15 DM, and 25 controls) identified significantly more NF1 mutations and mitogen-activated protein kinase (MAPK) pathway gene mutations in patients with LRR (24%, 47%) and DM (27%, 40%) compared to controls (0%, 0%; p < 0.0001 and p = 0.0070, respectively). Three patients had matched primary vs. LRR samples, one patient had a gain of a NF1 mutation in the LRR. There was no significant difference between the groups for PTEN loss or cleaved caspase 3 expression. The mean percentage Ki 67 labeling index was higher in patients with LRR (29.2%) and DM (26%) vs. controls (14%, p = 0.0045). In summary, mutations in the MAPK pathway, specifically NF1, were associated with both LRR and DM, suggesting that alterations in MAPK signaling are associated with a more aggressive tumor phenotype. Validation of these associations in tissues from randomized trials may support targeted therapy to reduce breast cancer recurrence.

Clinical and molecular aspects of breast cancer: Targets and therapies

Breast Cancer is a complex disease characterized by the occurrence of multiple molecular alterations. Currently, some molecular markers are in use for breast cancer diagnostic, prognostic, and predictive purposes. Thus, genetic signatures are available for improving the decision-making. The biomarkers are also essential as therapeutic approaches, but many questions remain due to the lack of efficacy on breast cancer treatment, mainly for triple-negative breast cancer subtype. Since the genetic profile of breast cancer can also be related to different ethnic groups and geographic areas, the reference populations of the genetic assays and clinical trials need to include a broader population beyond the European and North American patients. In this review, we analyzed the current and potential molecular markers that could help to improve the strategies for breast cancer therapy.

Molecular Genomic Testing for Breast Cancer: Utility for Surgeons

Molecular genomic testing provides clinicians with both prognostic and (sometimes) predictive information that can help individualize treatment and decrease the risk of over- or under-treatment. We review the genomic tests that are currently available for clinical use in management of breast cancer, discuss ongoing research related to validating and expanding their utility in different patient populations, and explain why it is important for surgeons to know how to incorporate these tools into their clinical practice in order to individualize patient treatment, reduce unnecessary morbidity, and, accordingly, improve outcomes.

Beyond Correlations, Sensitivities, and Specificities: A Roadmap for Demonstrating Utility of Advanced Imaging in Oncology Treatment and Clinical Trial Design

Despite the widespread belief that advanced imaging should be very helpful in guiding oncology treatment decision and improving efficiency and success rates in treatment clinical trials, its acceptance has been slow. Part of this is likely attributable to gaps in study design and statistical methodology for these imaging studies. Also, results supporting the performance of the imaging in these roles have largely been insufficient to justify their use within the design of a clinical trial or in treatment decision making. Statistically significant correlations between the imaging results and clinical outcomes are often incorrectly taken as evidence of adequate performance. Assessments of whether the imaging can outperform standard techniques or meaningfully supplement them are also frequently neglected. This paper provides guidance on study designs and statistical analyses for evaluating the performance of advanced imaging in the various roles in treatment decision guidance and clinical trial conduct. Relevant methodology from the imaging literature is reviewed; gaps in the literature are addressed using related concepts from the more extensive genomic and in vitro biomarker literature.

The Era of Multigene Panels Comes? The Clinical Utility of Oncotype DX and MammaPrint

The AJCC Cancer Staging Manual, eighth edition published in late 2016, will become the new global guideline for cancer diagnosis and treatment from January 1, 2018. The new edition for the tumor staging system has numerous updates, including building up the prognostic stage group of tumors for the first time and adding a large number of non-anatomical factors into the prognostic evaluation. Oncotype DX and MammaPrint are two of the genomic predictors that will be part of routine clinical practice in the future. Numerous studies have proved the clinical utility of multigene panels in predicting clinical outcome and treatment response. Here we present our review of the studies on these multigene panels and their application to breast cancer.

Extended Adjuvant Endocrine Therapy in Breast Cancer: Evidence and Update - A Review

The optimal duration and treatment strategies involving adjuvant endocrine therapy in early breast cancer remained largely undetermined. As data emerge on the various modalities of treatment in both pre- and postmenopausal groups, debates, and discussions continue. Most studies to date focused on the 5-year duration of treatment consisting of mainly tamoxifen. The Arimidex, Tamoxifen, Alone or in Combination (ATAC) study demonstrated that anastrozole is superior to tamoxifen and has become the mainstream treatment in postmenopausal women with early breast cancer, although the duration was arbitrarily set for 5 years, analogous to tamoxifen treatment. Several clinical trials, however, have emerged to support extended endocrine therapy as it becomes clear that the recurrence risk of breast cancer does not decrease beyond the initial 5 years of treatment. The advent of molecular signatures also plays an important role in the breast cancer profiling, and where available should be incorporated in the overall decision-making. Furthermore, side effects and noncompliance pose another issue in achieving an optimal treatment benefit. The decision-making as regards to extended endocrine treatment should therefore focus not only on the cancer biology alone but also include treatment side effects, assessment of risk of recurrence and patients' preference. In this review, we present an overview of the published studies to date as well as ongoing studies on the topic to better refine the options for adjuvant hormonal therapy.

Use of maintenance endocrine therapy after chemotherapy in metastatic breast cancer

BACKGROUND

For women with oestrogen receptor+ metastatic breast cancer (MBC), the options for systemic treatment include endocrine therapy (ET) and chemotherapy. For women whose disease is also HER2+, anti-HER2 therapies are also routinely used either with chemotherapy or less commonly with ET. Where chemotherapy is used as initial therapy, treatment is often discontinued due to cumulative toxicity in the absence of disease progression. In this setting, there is the option of introducing ET with the aim of prolonging response and delaying relapse.

METHODS

Literature review revealed four trials addressing the question of whether there is a benefit from introducing ET following chemotherapy for MBC. We also sought evidence for alternative approaches, including concurrent chemotherapy and ET and continuing chemotherapy until disease progression.

RESULTS

The evidence for the use of ET after chemotherapy in MBC is limited, and the trials done were small. Furthermore, they were performed at a time when both the chemotherapy regimens and ET were different from those used currently. Despite these limitations, there is probably a modest improvement in time to progression for the sequential use of ET after chemotherapy but with no overall survival benefit. An alternative approach, particularly considering agents with relatively low toxicity, such as orally bioavailable fluoropyrimidines, is to continue chemotherapy until disease progression.

CONCLUSION

Where chemotherapy for MBC is discontinued due to toxicity, in the absence of progression, the use of ET, with its relatively low toxicity, is a reasonable approach with the aim of delaying relapse.

The Evolution of Oncology Companion Diagnostics from Signal Transduction to Immuno-Oncology

Sixteen oncology drugs have been approved with a companion diagnostic (CDx) test by the FDA. These represent only 9.6% of the 167 oncology drug approvals since 1998, the year the first CDx test for Herceptin was approved. The great majority of CDx tests are for drugs that inhibit signal transduction pathways by either inhibiting the intracellular kinase activity with a small molecule or preventing ligand-induced receptor activation with a monoclonal antibody. In most of these cases, prospective patient selection for the biomarker-positive subpopulation was initiated in or before Phase II. The development of CDx tests for emerging immunotherapies will be more complicated because they are not dependent on driver mutations in the drug target, the mechanism of action is often pleiotropic, and will require both protein and cell-based assays to evaluate the interaction of the tumor with the immune system. Consequently, we will need to develop new biomarker strategies for the development of immunotherapies and to determine whether the optimum strategy is to release a prior checkpoint blockade in patients with a suppressed immune response, or to prime a new immune response to the tumor.

Equivalence of MammaPrint array types in clinical trials and diagnostics

MammaPrint is an FDA-cleared microarray-based test that uses expression levels of the 70 MammaPrint genes to assess distant recurrence risk in early-stage breast cancer. The prospective RASTER study proved that MammaPrint Low Risk patients can safely forgo chemotherapy, which is further subject of the prospective randomized MINDACT trial. While MammaPrint diagnostic results are obtained from mini-arrays, clinical trials may be performed on whole-genome arrays. Here we demonstrate the equivalence and reproducibility of the MammaPrint test. MammaPrint indices were collected for breast cancer samples: (i) on both customized certified array types (n = 1,897 sample pairs), (ii) with matched fresh and FFPE tissues (n = 552 sample pairs), iii) for control samples replicated over a period of 10 years (n = 11,333), and iv) repeated measurements (n = 280). The array type indicated a near perfect Pearson correlation of 0.99 (95 % CI: 0.989-0.991). Paired fresh and FFPE samples showed an excellent Pearson correlation of 0.93 (95 % CI 0.92-0.94), in spite of the variability introduced by intratumoral tissue heterogeneity. Control samples showed high consistency over 10 year's time (overall reproducibility of 97.4 %). Precision and repeatability are overall 98.2 and 98.3 %, respectively. Results confirm that the combination of the near perfect correlation between array types, excellent equivalence between tissue types, and a very high stability, precision, and repeatability demonstrate that results from clinical trials (such as MINDACT and I-SPY 2) are equivalent to current MammaPrint FFPE and fresh diagnostics, and can be used interchangeably.

Prospective Validation of a 21-Gene Expression Assay in Breast Cancer

BACKGROUND

Prior studies with the use of a prospective-retrospective design including archival tumor samples have shown that gene-expression assays provide clinically useful prognostic information. However, a prospectively conducted study in a uniformly treated population provides the highest level of evidence supporting the clinical validity and usefulness of a biomarker.

METHODS

We performed a prospective trial involving women with hormone-receptor-positive, human epidermal growth factor receptor type 2 (HER2)-negative, axillary node-negative breast cancer with tumors of 1.1 to 5.0 cm in the greatest dimension (or 0.6 to 1.0 cm in the greatest dimension and intermediate or high tumor grade) who met established guidelines for the consideration of adjuvant chemotherapy on the basis of clinicopathologic features. A reverse-transcriptase-polymerase-chain-reaction assay of 21 genes was performed on the paraffin-embedded tumor tissue, and the results were used to calculate a score indicating the risk of breast-cancer recurrence; patients were assigned to receive endocrine therapy without chemotherapy if they had a recurrence score of 0 to 10, indicating a very low risk of recurrence (on a scale of 0 to 100, with higher scores indicating a greater risk of recurrence).

RESULTS

Of the 10,253 eligible women enrolled, 1626 women (15.9%) who had a recurrence score of 0 to 10 were assigned to receive endocrine therapy alone without chemotherapy. At 5 years, in this patient population, the rate of invasive disease-free survival was 93.8% (95% confidence interval [CI], 92.4 to 94.9), the rate of freedom from recurrence of breast cancer at a distant site was 99.3% (95% CI, 98.7 to 99.6), the rate of freedom from recurrence of breast cancer at a distant or local-regional site was 98.7% (95% CI, 97.9 to 99.2), and the rate of overall survival was 98.0% (95% CI, 97.1 to 98.6).

CONCLUSIONS

Among patients with hormone-receptor-positive, HER2-negative, axillary node-negative breast cancer who met established guidelines for the recommendation of adjuvant chemotherapy on the basis of clinicopathologic features, those with tumors that had a favorable gene-expression profile had very low rates of recurrence at 5 years with endocrine therapy alone. (Funded by the National Cancer Institute and others; ClinicalTrials.gov number, NCT00310180.).

Identifying patients at high risk of breast cancer recurrence: strategies to improve patient outcomes

Identifying patients at high risk of breast cancer recurrence has important implications not only for enabling the ability to provide accurate information to patients but also the potential to improve patient outcomes. Patients at high recurrence risk can be offered appropriate treatment to improve the overall survival. However, the major challenge is identifying patients with early-stage breast cancer at lower risk who may be spared potentially toxic therapy. The successful integration of molecular assays into clinical practice may address the problem of overtreatment and improve overall patient outcomes.

Placental transcriptome in development and pathology: expression, function, and methods of analysis

The placenta is the essential organ of mammalian pregnancy and errors in its development and function are associated with a wide range of human pathologies of pregnancy. Genome sequencing has led to methods for investigation of the transcriptome (all expressed RNA species) using microarrays and next-generation sequencing, and implementation of these techniques has identified many novel species of RNA including: micro-RNA, long noncoding RNA, and circular RNA. These species can physically interact with both each other and regulatory proteins to modify gene expression and messenger RNA to protein translation. Transcriptome analysis is actively used to investigate placental development and dysfunction in pathologies ranging from preeclampsia and fetal growth restriction to preterm labor. Genome-wide gene expression analysis is also being applied to identify prognostic and diagnostic biomarkers of these disorders. In this comprehensive review we summarize transcriptome biology, methods of isolation and analysis, application to placental development and pathology, and use in diagnostic analysis in maternal blood. Key information for analysis methods is organized into quick reference tables where current analysis techniques and tools are cited and compared. We have created this review as a practical guide and starting reference for those interested in beginning an investigation into the transcriptome of the placenta.

Subtype-Specific Metagene-Based Prediction of Outcome after Neoadjuvant and Adjuvant Treatment in Breast Cancer

PURPOSE

In spite of improvements of average benefit from adjuvant/neoadjuvant treatments, there are still individual patients with early breast cancer at high risk of relapse. We explored the association with outcome of robust gene cluster-based metagenes linked to proliferation, ER-related genes, and immune response to identify those high-risk patients.

EXPERIMENTAL DESIGN

A total of 3,847 publicly available gene-expression profiles were analyzed (untreated, N = 826; tamoxifen-treated, N = 685; chemotherapy-treated, N = 1,150). Genes poorly performing in formalin-fixed samples were removed. Outcomes of interest were pathologic-complete response (pCR) and distant metastasis-free survival (DMFS). In ER(+)HER2(-), the proliferation and ER-related metagenes were combined to define three risk groups. In HER2(+) and ER(-)HER2(-) risk groups were defined by tertiles of an immune-related metagene.

RESULTS

The high-proliferation/low-ER group of ER(+)HER2(-) breast cancer had significantly higher pCR rate [OR, 5.01 (1.76-17.99), P = 0.005], but poorer outcome [HR = 3.73 (1.63-8.51), P = 0.0018] than the low-proliferation/high-ER. A similar association with outcome applied to patients with residual disease (RD) after neoadjuvant chemotherapy (P = 0.01). In ER(-)HER2(-) and HER2(+) breast cancer, immune metagene in the high tertile was linked to higher pCR [33.7% vs. 11.6% in high and low tertile, respectively; OR, 3.87 (1.79-8.95); P = 0.0009]. In ER(-)HER2(-), after adjuvant/neoadjuvant chemotherapy, 5-year DMFS was 85.4% for high-tertile immune metagene, and 43.9% for low tertile. The outcome association was similar in patients with RD (P = 0.0055). In HER2(+) breast cancer treated with chemotherapy the association with risk of relapse was not significant.

CONCLUSIONS

We developed metagene-based predictors able to define low and high risk of relapse after adjuvant/neoadjuvant therapy. High-risk patients so defined should be preferably considered for trials with investigational agents.

Progress in adjuvant chemotherapy for breast cancer: an overview

Breast cancer is the most common cause of cancer and cancer death worldwide. Although most patients present with localized breast cancer and may be rendered disease-free with local therapy, distant recurrence is common and is the primary cause of death from the disease. Adjuvant systemic therapies are effective in reducing the risk of distant and local recurrence, including endocrine therapy, anti-HER2 therapy, and chemotherapy, even in patients at low risk of recurrence. The widespread use of adjuvant systemic therapy has contributed to reduced breast cancer mortality rates. Adjuvant cytotoxic chemotherapy regimens have evolved from single alkylating agents to polychemotherapy regimens incorporating anthracyclines and/or taxanes. This review summarizes key milestones in the evolution of adjuvant systemic therapy in general, and adjuvant chemotherapy in particular. Although adjuvant treatments are routinely guided by predictive factors for endocrine therapy (hormone receptor expression) and anti-HER2 therapy (HER2 overexpression), predicting benefit from chemotherapy has been more challenging. Randomized studies are now in progress utilizing multiparameter gene expression assays that may more accurately select patients most likely to benefit from adjuvant chemotherapy.

miR-30e* is an independent subtype-specific prognostic marker in breast cancer

Background:

Breast cancer clinical outcome is affected by tumor molecular features, and the identification of subtype-specific prognostic biomarkers is relevant for breast cancer translational research. Gene expression signatures proved to be able to complement prognostic information provided by classical clinico-pathological features. Recently, microRNAs (miRNAs) have been causally linked to tumorigenesis and cancer progression and have been associated with patient outcome, also in breast cancer.

Methods:

MicroRNAs associated with the development of distant metastasis were identified in a cohort of 92 ESR1+/ERBB2− lymph node-negative breast cancers from patients not receiving adjuvant treatment. Results were confirmed and further investigated in a total of 1246 miRNA and gene expression profiles of the Molecular Taxonomy of Breast Cancer International Consortium data set. Moderated t-test, univariable and multivariable Cox regression models were used for statistical analyses.

Results:

miR-30e* was identified as independent protective prognostic factor in lymph node-negative untreated patients with ESR1+/ERBB2− tumours and retained a significant association with a good prognosis in treated patients with the same tumor subtype as well as in the ERBB2+ subtype, but not in ESR1−/ERBB2− tumours.

Conclusions:

We highlighted a relevant and subtype-specific role in breast cancer for miR-30e* and demonstrated that adding miRNA markers to gene signatures and clinico-pathological features can help for a better prognostication.

Intra-tumour signalling entropy determines clinical outcome in breast and lung cancer

The cancer stem cell hypothesis, that a small population of tumour cells are responsible for tumorigenesis and cancer progression, is becoming widely accepted and recent evidence has suggested a prognostic and predictive role for such cells. Intra-tumour heterogeneity, the diversity of the cancer cell population within the tumour of an individual patient, is related to cancer stem cells and is also considered a potential prognostic indicator in oncology. The measurement of cancer stem cell abundance and intra-tumour heterogeneity in a clinically relevant manner however, currently presents a challenge. Here we propose signalling entropy, a measure of signalling pathway promiscuity derived from a sample's genome-wide gene expression profile, as an estimate of the stemness of a tumour sample. By considering over 500 mixtures of diverse cellular expression profiles, we reveal that signalling entropy also associates with intra-tumour heterogeneity. By analysing 3668 breast cancer and 1692 lung adenocarcinoma samples, we further demonstrate that signalling entropy correlates negatively with survival, outperforming leading clinical gene expression based prognostic tools. Signalling entropy is found to be a general prognostic measure, valid in different breast cancer clinical subgroups, as well as within stage I lung adenocarcinoma. We find that its prognostic power is driven by genes involved in cancer stem cells and treatment resistance. In summary, by approximating both stemness and intra-tumour heterogeneity, signalling entropy provides a powerful prognostic measure across different epithelial cancers.

Predictive markers in breast cancer: An update on ER and HER2 testing and reporting

Gene expression profiling of human tumors has provided a new paradigm for classifying breast carcinomas, predicting response to treatment, and risk of recurrence. Estrogen receptor (ER), human epidermal growth factor 2 (HER2) receptor, and proliferation-related genes are the main drivers of classification in many of the gene expression profiling tests for breast cancer. However, ER, progesterone receptor (PR), and HER2 receptor status remain essential in determining the need and type of adjuvant therapy. These biomarkers are routinely tested for in all invasive breast carcinomas; ER testing is also performed on cases of ductal carcinoma in situ (DCIS). This article will provide an update on current guidelines from the American Society of Clinical Oncologists (ASCO) and the College of American Pathologists (CAP) for ER and HER2 testing by immunohistochemistry (IHC) and in situ hybridization (ISH). The populations to be tested, antibody selection, criteria for interpretation, and reporting are discussed. The molecular alterations that correlate with IHC results, alternative methods of testing, and the current approach to complex aspects of HER2 testing, including heterogeneity and polysomy, also are summarized.

A tumor DNA complex aberration index is an independent predictor of survival in breast and ovarian cancer

Complex focal chromosomal rearrangements in cancer genomes, also called "firestorms", can be scored from DNA copy number data. The complex arm-wise aberration index (CAAI) is a score that captures DNA copy number alterations that appear as focal complex events in tumors, and has potential prognostic value in breast cancer. This study aimed to validate this DNA-based prognostic index in breast cancer and test for the first time its potential prognostic value in ovarian cancer. Copy number alteration (CNA) data from 1950 breast carcinomas (METABRIC cohort) and 508 high-grade serous ovarian carcinomas (TCGA dataset) were analyzed. Cases were classified as CAAI positive if at least one complex focal event was scored. Complex alterations were frequently localized on chromosome 8p (n = 159), 17q (n = 176) and 11q (n = 251). CAAI events on 11q were most frequent in estrogen receptor positive (ER+) cases and on 17q in estrogen receptor negative (ER-) cases. We found only a modest correlation between CAAI and the overall rate of genomic instability (GII) and number of breakpoints (r = 0.27 and r = 0.42, p < 0.001). Breast cancer specific survival (BCSS), overall survival (OS) and ovarian cancer progression free survival (PFS) were used as clinical end points in Cox proportional hazard model survival analyses. CAAI positive breast cancers (43%) had higher mortality: hazard ratio (HR) of 1.94 (95%CI, 1.62-2.32) for BCSS, and of 1.49 (95%CI, 1.30-1.71) for OS. Representations of the 70-gene and the 21-gene predictors were compared with CAAI in multivariable models and CAAI was independently significant with a Cox adjusted HR of 1.56 (95%CI, 1.23-1.99) for ER+ and 1.55 (95%CI, 1.11-2.18) for ER- disease. None of the expression-based predictors were prognostic in the ER- subset. We found that a model including CAAI and the two expression-based prognostic signatures outperformed a model including the 21-gene and 70-gene signatures but excluding CAAI. Inclusion of CAAI in the clinical prognostication tool PREDICT significantly improved its performance. CAAI positive ovarian cancers (52%) also had worse prognosis: HRs of 1.3 (95%CI, 1.1-1.7) for PFS and 1.3 (95%CI, 1.1-1.6) for OS. This study validates CAAI as an independent predictor of survival in both ER+ and ER- breast cancer and reveals a significant prognostic value for CAAI in high-grade serous ovarian cancer.

Gene expression profiling of circulating tumor cells in breast cancer

BACKGROUND

Determining the transcriptional profile of circulating tumor cells (CTCs) may allow the acquisition of clinically relevant information while overcoming tumor heterogeneity-related biases associated with use of tissue samples for biomarker assessment. However, such molecular characterization is challenging because CTCs are rare and outnumbered by blood cells.

METHODS

Here, we describe a technical protocol to measure the expression of >29 000 genes in CTCs captured from whole blood with magnetic beads linked with antibodies against epithelial cell adhesion molecule (EpCAM) and the carcinoma-associated mucin, MUC1, designed to be used for CTC characterization in clinical samples. Low numbers of cells (5-200) from the MCF7 and MDA-MB-468 breast cancer cell lines were spiked in healthy donor blood samples and isolated with the AdnaTest EMT-1/Stem CellSelect kit. Gene expression profiles (GEPs) were obtained with the WG-DASL HT assay and compared with GEPs obtained from RNA isolated from cultured cell lines and unspiked samples.

RESULTS

GEPs from samples containing 25 or more spiked cells correlated (r = 0.95) with cognate 100-ng RNA input samples, clustered separately from blood control samples, and allowed MCF7 and MDA-MB-468 cells to be distinguished. GEPs with comparable technical quality were also obtained in a preliminary series of clinical samples.

CONCLUSIONS

Our approach allows technically reliable GEPs to be obtained from isolated CTCs for the acquisition of biologically useful information. It is reproducible and suitable for application in prospective studies to assess the clinical utility of CTC GEPs, provided that >25 CTCs can be isolated.

A thirteen-gene expression signature predicts survival of patients with pancreatic cancer and identifies new genes of interest

BACKGROUND

Currently, prognostication for pancreatic ductal adenocarcinoma (PDAC) is based upon a coarse clinical staging system. Thus, more accurate prognostic tests are needed for PDAC patients to aid treatment decisions.

METHODS AND FINDINGS

Affymetrix gene expression profiling was carried out on 15 human PDAC tumors and from the data we identified a 13-gene expression signature (risk score) that correlated with patient survival. The gene expression risk score was then independently validated using published gene expression data and survival data for an additional 101 patients with pancreatic cancer. Patients with high-risk scores had significantly higher risk of death compared to patients with low-risk scores (HR 2.27, p = 0.002). When the 13-gene score was combined with lymph node status the risk-score further discriminated the length of patient survival time (p<0.001). Patients with a high-risk score had poor survival independent of nodal status; however, nodal status increased predictability for survival in patients with a low-risk gene signature score (low-risk N1 vs. low-risk N0: HR = 2.0, p = 0.002). While AJCC stage correlated with patient survival (p = 0.03), the 13-gene score was superior at predicting survival. Of the 13 genes comprising the predictive model, four have been shown to be important in PDAC, six are unreported in PDAC but important in other cancers, and three are unreported in any cancer.

CONCLUSIONS

We identified a 13-gene expression signature that predicts survival of PDAC patients and could prove useful for making treatment decisions. This risk score should be evaluated prospectively in clinical trials for prognostication and for predicting response to chemotherapy. Investigation of new genes identified in our model may lead to novel therapeutic targets.

Correlation Between E-cadherin Immunoexpression and Efficacy of First Line Platinum-Based Chemotherapy in Advanced High Grade Serous Ovarian Cancer

To analyze correlation between immunoexpression of E-cadherin and efficacy of first line platinum-based chemotherapy in patients with advanced-stage high-grade serous ovarian carcinoma. The expression of E-cadherin was analyzed immunohistochemically in formalin-fixed, paraffin-embedded samples from 98 patients with advanced-stage high-grade serous ovarian cancer and related to clinical features (stage according to the International Federation of Gynecology and Obstetrics (FIGO) and residual tumors after initial cytoreductive surgery), response to platinum-based chemotherapy (according to Response Evaluation Criteria in Solid tumors (RECIST 1.1 criteria)), platinum sensitivity (according to platinum free interval (PFI) as platinum-refractory, platinum-resistant and platinum-sensitive) and patients progression free survival (PFS) and overall survival (OS). E-cadherin immunostaining was positive in 74 and negative in 24 serous ovarian carcinomas. E-cadherin immunoreactivity was not associated with FIGO stage, residual tumor after initial cytoreductive surgery and number of chemotherapy cycles. Positive E-cadherin expression predict significantly better response to first line platinum-based chemotherapy (p < 0.001) and platinum sensitivity (p < 0.001). Moreover, positive E-cadherin expression predict significantly longer PFS (p < 0.001) and OS (p < 0.001). The multivariate analysis for OS showed that positive E-cadherin expression is predictor to platinum sensitivity (p < 0.001) and longer OS (p = 0.01). Positive E-cadherin expression seems to be a predictor of better response to first line platinum-based chemotherapy, platinum sensitivity and favorable clinical outcome in patients with advanced-stage serous ovarian cancer. Negative E-cadherin expression was shown to be significant, independent predictor of poorer PFS and OS. E-cadherin as a marker has predictive and prognostic value.

Luminal B breast cancer: molecular characterization, clinical management, and future perspectives

Gene expression profiling has reshaped our understanding of breast cancer by defining and characterizing four main intrinsic molecular subtypes: human epidermal growth factor receptor 2-enriched, basal-like, luminal A, and luminal B subtypes. Luminal B breast cancer has been reported to have lower expression of hormone receptors, higher expression of proliferation markers, and higher histologic grade than luminal A. It also exhibits worse prognosis and has a distinct profile of response to hormone therapy and chemotherapy. Although luminal cancers share similarities, the studies conducted in recent years using next-generation sequencing technology show that luminal A and B breast cancers should be perceived as distinct entities, with specific oncogenic drivers, rather than more proliferative varieties of luminal tumors. This review discusses the definition and molecular characterization of luminal B breast cancer and presents the available clinical evidence for chemotherapy and endocrine therapy patterns of response. It also provides an overview of ongoing research on molecularly targeted agents for this disease.

Subtype-dependent prognostic relevance of an interferon-induced pathway metagene in node-negative breast cancer

The majority of gene expression signatures developed to predict the likelihood to relapse in breast cancer (BC) patients assigns a high risk score to patients with Estrogen Receptor (ER) negative or highly proliferating tumors. We aimed to identify a signature of differentially expressed (DE) metagenes, rather than single DE genes, associated with distant metastases beyond classical risk factors. We used 105 gene expression profiles from consecutive BCs to identify metagenes whose prognostic role was defined on an independent series of 92 ESR1+/ERBB2- node-negative BCs (42 cases developing metastases within 5 years from diagnosis and 50 cases metastasis-free for more than 5 years, comparable for age, tumor size, ER status and surgery). Findings were validated on publicly available datasets of 684 node-negative BCs including all the subtypes. Only a metagene containing interferon-induced genes (IFN metagene) proved to be predictive of distant metastasis in our series of patients with ESR1+/ERBB2- tumors (P = 0.029), and such a finding was validated on 457 ESR1+/ERBB2- BCs from public datasets (P = 0.0424). Conversely, the IFN metagene was associated with a low risk of metastasis in 104 ERBB2+ tumors (P = 0.0099) whereas it did not prove to significantly affect prognosis in 123 ESR1-/ERBB2- tumors (P = 0.2235). A complex prognostic interaction was revealed in ESR1+/ERBB2- and ERBB2+ tumors when the association between the IFN metagene and a T-cell metagene was considered. The study confirms the importance of analyzing prognostic variables separately within BC subtypes, highlights the advantages of using metagenes rather than genes, and finally identifies in node-negative ESR1+/ERBB2- BCs, the unfavorable role of high IFN metagene expression.