Molecular Testing and the Pathologist's Role in Clinical Trials of Breast Cancer

A color-based tumor segmentation method for clinical ex vivo breast tissue assessment utilizing a multi-contrast brightfield imaging strategy

We demonstrate an automated two-step tumor segmentation method leveraging color information from brightfield images of fresh core needle biopsies of breast tissue. Three different color spaces (HSV, CIELAB, YCbCr) were explored for the segmentation task. By leveraging white-light and green-light images, we identified two different types of color transformations that could separate adipose from benign and tumor or cancerous tissue. We leveraged these two distinct color transformation methods in a two-step process where adipose tissue segmentation was followed by benign tissue segmentation thereby isolating the malignant region of the biopsy. Our tumor segmentation algorithm and imaging probe could highlight suspicious regions on unprocessed biopsy tissue to guide selection of areas most similar to malignant tissues for tissue pathology whether it be formalin fixed or frozen sections, expedite tissue selection for molecular testing, detect positive tumor margins, or serve an alternative to tissue pathology, in countries where these services are lacking.

Molecular subtypes as a prognostic breast cancer factor in women users of the São Paulo public health system, Brazil

OBJECTIVE

This study aimed to analyze the prognosis of women with breast cancer by molecular subtypes, sociodemographic variables, and clinical and treatment characteristics.

METHODS

This hospital-based retrospective cohort study analyzed 1,654 women over 18 years of age diagnosed with invasive breast cancer from 2000 to 2018. Data were extracted from Brazil's Oncocenter Foundation of São Paulo. The variables analyzed were age, histology, molecular subtypes, clinical staging, treatment type, and diagnosis-to-treatment time. Cox regression analysis was applied to estimate death risk.

RESULTS

Women with HER-2-positive (nonluminal) and triple-negative molecular subtypes were more than twice more likely to be at risk of death, with adjusted hazard ratio - HRadj=2.30 (95% confidence interval - 95%CI 1.34-3.94) and HRadj=2.51 (95%CI 1.61-3.92), respectively. A delayed treatment associated with an advanced clinical stage at diagnosis increased fourfold the risk of death (HRadj=4.20 (95%CI 2.36-7.49).

CONCLUSION

In summary, besides that interaction between advanced clinical stage and longer time between diagnosis and treatment, HER-2-positive (nonluminal) and triple-negative phenotypes were associated with a worse prognosis. Therefore, actions to reduce barriers in diagnosis and treatment can provide better outcome, even in aggressive phenotypes.

Expression analysis of novel long non-coding RNAs for invasive ductal and invasive lobular breast carcinoma cases

AIM

Long non-coding RNAs (LncRNAs) serve as important regulatory molecules of gene expression and protein functionality at multiple biological levels, and their deregulation plays a key role in tumorigenesis including in breast cancer metastasis. Therefore, in this study, we aim to compare the expression of novel lncRNAs in the landscape of invasive ductal carcinoma (IDC) and invasive lobular (ILC) carcinoma of breast.

MAIN METHODS

We have designed an in-silico approach to find the lncRNAs that regulate the breast cancer. Then, we used the clinical samples to carry out the verification of our in silico finding. In the present study, the tissues of breast cancer were deparaffinized. RNA was extracted by the TRIzole method. After synthesizing cDNA from the extracted RNA, expression levels of lncRNAs were analyzed by qPCR using primers specifically designed and validated for the targeted lncRNAs. In this study, breast biopsy materials from 41 female patients with IDC and 10 female patients with ILC were examined histopathological and expression changes of candidate lncRNAs were investigated in line with the findings. The results were analyzed using IBM SPSS Statistics 25 version.

RESULTS

The mean age of the cases was 53.78 ± 14.96. The minimum age was 29, while the maximum age was 87. While 27 of the cases were pre-menopausal, 24 cases were post-menopausal. The number of hormone receptor-positive cases was found to be 40, 35, and 27 for ER, PR, and cerb2/neu, respectively. While the expressions of LINC00501, LINC00578, LINC01209, LINC02015, LINC02584, ABCC5-AS1, PEX5L-AS2, SHANK2-AS3 and SOX2-OT showed significant differences (p < 0.05), the expressions of LINC01206, LINC01994, SHANK2-AS1, and TPRG1-AS2 showed no significant differences (p > 0.05). In addition, it was determined that the regulation of all lncRNAs could be able to involve in the development of cancer such as the NOTCH1, NFKB, and estrogen receptor signalings.

CONCLUSION

As a result, it was thought that the discovery of novel lncRNAs might be an important player in the diagnosis, prognosis and therapeutic development of breast cancer.

Advancing Research on Medical Image Perception by Strengthening Multidisciplinary Collaboration

Medical image interpretation is central to detecting, diagnosing, and staging cancer and many other disorders. At a time when medical imaging is being transformed by digital technologies and artificial intelligence, understanding the basic perceptual and cognitive processes underlying medical image interpretation is vital for increasing diagnosticians’ accuracy and performance, improving patient outcomes, and reducing diagnostician burn-out. Medical image perception remains substantially understudied. In September of 2019, the National Cancer Institute convened a multidisciplinary panel of radiologists and pathologists together with researchers working in medical image perception and adjacent fields of cognition and perception for the “Cognition and Medical Image Perception Think Tank.” The Think Tank’s key objectives were: to identify critical unsolved problems related to visual perception in pathology and radiology from the perspective of diagnosticians; to discuss how these clinically relevant questions could be addressed through cognitive and perception research; to identify barriers and solutions for transdisciplinary collaborations; to define ways to elevate the profile of cognition and perception research within the medical image community; to determine the greatest needs to advance medical image perception; and to outline future goals and strategies to evaluate progress. The Think Tank emphasized diagnosticians’ perspectives as the crucial starting point for medical image perception research, with diagnosticians describing their interpretation process and identifying perceptual and cognitive problems that arise. This paper reports the deliberations of the Think Tank participants to address these objectives and highlight opportunities to expand research on medical image perception.

Transcriptome Analysis Identifies GATA3-AS1 as a Long Noncoding RNA Associated with Resistance to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer Patients

Breast cancer is one of the leading causes of mortality in women worldwide, and neoadjuvant chemotherapy has emerged as an option for the management of locally advanced breast cancer. Extensive efforts have been made to identify new molecular markers to predict the response to neoadjuvant chemotherapy. Transcripts that do not encode proteins, termed long noncoding RNAs (lncRNAs), have been shown to display abnormal expression profiles in different types of cancer, but their role as biomarkers in response to neoadjuvant chemotherapy has not been extensively studied. Herein, lncRNA expression was profiled using RNA sequencing in biopsies from patients who subsequently showed either response or no response to treatment. The GATA3-AS1 transcript was overexpressed in the nonresponder group and was the most stable feature when performing selection in multiple random forest models. GATA3-AS1 was experimentally validated by RT-qPCR in an extended group of 68 patients. Expression analysis confirmed that GATA3-AS1 is overexpressed primarily in patients who were nonresponsive to neoadjuvant chemotherapy, with a sensitivity of 92.9%, a specificity of 75.0%, and an area under the curve of approximately 0.90, as measured by receiver operating characteristic curve analysis. The statistical model was based on luminal B-like patients and adjusted by menopausal status and phenotype (odds ratio, 37.49; 95% CI, 6.74-208.42; P = 0.001); GATA3-AS1 was established as an independent predictor of response. Thus, lncRNA GATA3-AS1 is proposed as a potential predictive biomarker of nonresponse to neoadjuvant chemotherapy.

Differences of time-dependent microRNA expressions in breast cancer cells

MicroRNA (miRNA) expression is a dynamic process in the cell, and the proper time period for post-transcriptional regulation might be critical due to the gene-on/-off expression times of the cell. Here, we investigated the effect of different time-points on proliferation, invasion and miRNA expression profiles of human breast cancer cell lines MCF-7 (non-metastatic, epithelium-like breast cancer cell line with oestrogen receptor (ER) positive (+) and human breast cancer cell lines MDA-MB-435 (metastatic, invasive, ER negative (-). For this purpose, MCF-7 and MDA-MB-435 cells were seeded different number in E-plate 16 for proliferation experiment using an electrical impedance-based real-time cell analyzer system (RTCA) for 168 h. Similarly, invasion potential of MCF-7 and MDA-MB-435 were determined by RTCA for 90 h. Total RNAs including miRNAs were isolated at 2, 4, 6, 12, 24, 48 h from the MCF-7 and MDA-MB-435 cells. Afterward, the quantitative 84 miRNA expressions of MCF-7 and MDA-MB-435 were analyzed by Fluidigm Microfluidic 96.96 Dynamic Array. The results of these study demonstrated that both proliferation potential and invasion capacity of MDA-MB-435 is higher than MCF-7 as time-dependent manner. Furthermore, we detected that up/down expressions of 32 miRNAs at all time points in MDA-MB-435 compared to MCF-7 (at least ten-fold increased). Because of the high number of miRNAs, we more closely evaluated the expression of six of them (miR-100-5p, miR-29a-3p, miR-130a-3p, miR-10a-5p, miR-10b-5p, miR-203a), and determined that their levels were dramatically changed by at least 50-fold at different time points of the experiment (p < 0.01). The expression levels of five of these miRNAs (miR-100-5p, miR-10a-5p, miR-10b-5p, miR-130a-3p, and miR-29a-3p) started to increase from the fourth hour and continued to increase until the 48th hour in MDA-MB-435 cells compared to MCF-7 cells (p < 0.01). Simultaneously, the expression of one of these miRNAs (miR-203a) decreased from the sixth hour to the 48th hour in MDA-MB-435 as compared to MCF-7. We determined pathways associated with target genes using mirPath - DIANA TOOLS. Small RNAs including miRNA are essential regulatory molecules for gene expressions. In the literature, gene expressions have been published as burst and pulse in the form of discontinuous transcription. The data of the research suggested that time-dependent changes of miRNA expressions can be affected target gene transcriptional fluctuations in breast cancer cell and can be base for the further studies.

Prognostic and predictive parameters in breast pathology: a pathologist's primer

The pathologist's role in the breast cancer treatment team has evolved from rendering a diagnosis of breast cancer, to providing a growing list of prognostic and predictive parameters such that individualized treatment decisions can be made based on likelihood of benefit from additional treatments and potential benefit from specific therapies. In all stages, ER and HER2 status help segregate breast cancers into treatment groups with similar outcomes and treatment response rates, however, traditional pathologic parameters such as favorable histologic subtype, size, lymph node status, and Nottingham grade also have remained clinically relevant in early stage disease decision-making. This is especially true for the most common subtype of breast cancer; ER positive, HER2 negative disease. For this same group of breast cancers, an ever-expanding list of gene-expression panels also can provide prediction and prognostication about potential chemotherapy benefit beyond standard endocrine therapies, with the 21-gene Recurrence Score, currently the only prospectively validated predictive test for this purpose. In the more aggressive ER-negative cancer subtypes, response to neoadjuvant therapy and` the extent of tumor infiltrating lymphocytes (TILs) are more recently recognized powerful prognostic parameters, and clinical guidelines now offer additional treatment options for those high-risk patients with residual cancer after standard neoadjuvant therapy. In stage four disease, predictive tests like germline BRCA status, tumor PIK3CA mutation status (in ER+ metastatic disease) and PDL-1 status (in triple negative metastatic disease) are now used to determine additional new treatment options. The objective of this review is to describe the latest in prognostic and predictive parameters in breast cancer as they are relevant to standard pathology reporting and how they are used in breast cancer clinical treatment decisions.

Testing considerations for phosphatidylinositol-3-kinase catalytic subunit alpha as an emerging biomarker in advanced breast cancer

Breast cancer is the most common cancer in women, and approximately 71% of carcinomas are hormone receptor‐positive (HR+) and human epidermal growth factor receptor 2‐not‐amplified (HER2‐negative). Pathogenesis of breast cancer is associated with dysregulation of several signaling pathways, including the phosphatidylinositol‐3‐kinase (PI3K) pathway. PIK3CA, the gene encoding PI3K catalytic subunit p110α, is mutated in 20%‐40% of breast cancer patients. Several PI3K inhibitors have been developed and one, alpelisib, was recently approved for use in PIK3CA‐mutated, HR+, HER2‐negative advanced breast cancer. There are numerous types of assays and methods used in clinical studies to determine PIK3CA status in cancers. Additionally, there are several factors to consider for PIK3CA testing in clinical practice, including choice of assay, source of sample, and test timing. In this review, we discuss the use of PIK3CA as a biomarker to guide treatment decisions in patients with HR+, HER2‐negative advanced breast cancer, as well as practical considerations and recommendations for testing.

A Predictor of Early Disease Recurrence in Patients With Breast Cancer Using a Cell-free RNA and Protein Liquid Biopsy

INTRODUCTION

Circulating biomarkers have been increasingly used in the clinical management of breast cancer. The present study evaluated whether RNAs and a protein present in the plasma of patients with breast cancer might have utility as prognostic biomarkers complementary to existing clinical tests.

PATIENTS AND METHODS

We performed microarray profiling of small noncoding RNAs in plasma samples from 30 patients with breast cancer and 10 control individuals. Two small noncoding RNAs, including microRNA (miR)-923, were selected and quantified in plasma samples from an evaluation cohort of 253 patients with breast cancer, using droplet digital polymerase chain reaction. We also measured cancer antigen (CA) 15-3 protein levels in these samples. Cox regression survival analysis was used to determine which markers were associated with patient prognosis.

RESULTS

As independent markers of prognosis, the plasma levels of miR-923 and CA 15-3 at the time of surgery for breast cancer were significantly associated with prognosis, irrespective of treatment (Cox proportional hazards, P = 3.9 × 10^-3 and 1.9 × 10^-9, respectively). After building a multivariable model with standard clinical and pathological features, the addition of miR-923 and CA 15-3 information into the model resulted in a significantly better predictor of disease recurrence in patients, irrespective of treatment, compared with the use of clinicopathological data alone (area under the curve at 3 years, 0.858 vs. 0.770 with clinicopathological markers only; P = .017).

CONCLUSION

We propose that the plasma levels of miR-923 and CA 15-3, combined with standard clinicopathological predictors, could be used as a preoperative, noninvasive estimate of patient prognosis to identify which women might need more aggressive treatment or closer surveillance after surgery for breast cancer.

The future of lung cancer therapy: Striding beyond conventional EGFR and ALK treatments

Lung cancer, one of the most frequently diagnosed cancers worldwide has long relied on testing for the molecular biomarkers EGFR/ALK. However, achieving superior clinical outcomes for patients with lung cancer requires developing comprehensive techniques beyond contemporary EGFR/ALK testing. Current technologies are on par with molecular testing for EGFR/ALK in terms of efficacy, most of them failing to offer improvements perhaps primarily due to skepticism among clinicians, despite being recommended in the NCCN guidelines. The present study endeavored to minimize chemotherapy-dependence in EGFR/ALK-negative patient cohorts, and use evidence-based methods to identify ways to improve clinical outcomes. In total, 137 lung cancer cases obtained from 'PositiveSelect NGS data', comprising 91 males and 46 females, were investigated. EGFR- and ALK-positivity was used for data dichotomization to understand the therapeutic utility of rare gene alterations beyond just EGFR/ALK. Statistics obtained from PositiveSelect were collated with data from international studies to construct a meta-analysis intended to achieve better clinical outcomes. Upon dichotomization, 23% of cases harbored EGFR variants indicating that treating with EGFR TKIs would be beneficial; the remaining 77% exhibited no EGFR variants that would indicate favorable results using specific currently available chemotherapy practices. Similarly, 28% of cases had EGFR+ALK variants favoring EGFR/ALK-based targeted therapeutics; the remaining 72% harbored no EGFR/ALK variants with known beneficial chemotherapy routes. The present study aimed to overcome current inadequacies of targeted therapies in patients with a conventional EGFR/ALK-positive diagnosis and those in EGFR+ALK-negative cohorts. Upon analysis of the negative cohorts, significant and clinically relevant single nucleotide variants were identified in KRAS, ERBB2, MET and RET, with frequencies of 7, 1, 2 and 3% in patients who were EGFR-negative and 6, 1, 1, and 3% in patients who were EGFR and ALK-negative, respectively, enabling the use of targeted therapeutics aside from EGFR/ALK TKIs. From the results of the current study only 35% of the two negative arms (EGFR negative and EGFR+ALK negative) would be recommended NCCN or off-label chemotherapy; prior to the current study, the entire cohorts would have been recommended this treatment. The present study emphasizes the potential of comprehensive genomics in identifying hallmarks of lung cancer beyond EGFR/ALK, using broad-spectrum genetic testing and data-sharing among medical professionals to circumvent ineffective chemotherapy.

Nuclear shape and orientation features from H&E images predict survival in early-stage estrogen receptor-positive breast cancers

Early-stage estrogen receptor-positive (ER+) breast cancer (BCa) is the most common type of BCa in the United States. One critical question with these tumors is identifying which patients will receive added benefit from adjuvant chemotherapy. Nuclear pleomorphism (variance in nuclear shape and morphology) is an important constituent of breast grading schemes, and in ER+ cases, the grade is highly correlated with disease outcome. This study aimed to investigate whether quantitative computer-extracted image features of nuclear shape and orientation on digitized images of hematoxylin-stained and eosin-stained tissue of lymph node-negative (LN-), ER+ BCa could help stratify patients into discrete (<10 years short-term vs. >10 years long-term survival) outcome groups independent of standard clinical and pathological parameters. We considered a tissue microarray (TMA) cohort of 276 ER+, LN- patients comprising 150 patients with long-term and 126 patients with short-term overall survival, wherein 177 randomly chosen cases formed the modeling set, and 99 remaining cases the test set. Segmentation of individual nuclei was performed using multiresolution watershed; subsequently, 615 features relating to nuclear shape/texture and orientation disorder were extracted from each TMA spot. The Wilcoxon's rank-sum test identified the 15 most prognostic quantitative histomorphometric features within the modeling set. These features were then subsequently combined via a linear discriminant analysis classifier and evaluated on the test set to assign a probability of long-term vs. short-term disease-specific survival. In univariate survival analysis, patients identified by the image classifier as high risk had significantly poorer survival outcome: hazard ratio (95% confident interval) = 2.91(1.23-6.92), p = 0.02786. Multivariate analysis controlling for T-stage, histology grade, and nuclear grade showed the classifier to be independently predictive of poorer survival: hazard ratio (95% confident interval) = 3.17(0.33-30.46), p = 0.01039. Our results suggest that quantitative histomorphometric features of nuclear shape and orientation are strongly and independently predictive of patient survival in ER+, LN- BCa.

Barriers to the release of human tissue for clinical trials research in the UK: a national survey of cellular pathology laboratories on behalf of the National Cancer Research Institute's Cellular Molecular Pathology (CM-Path) initiative

AIM

To survey UK cellular pathology departments regarding their attitudes and practices relating to release of human tissue from their diagnostic archives for use in clinical trial research.

METHODS

A 30-item questionnaire was circulated to the National Cancer Research Institute's Cellular Molecular Pathology initiative and Confederation of Cancer Biobanks mailing lists. Responses were collected over a 10-month period from November 2016 to August 2017.

RESULTS

38 departments responded to the survey, the majority of which regularly receive requests for tissue for research purposes. Most requests come from academia and financial support to facilitate tissue release comes from a variety of sources. A range of practices were reported in relation to selection of the most appropriate sample to release, consent checking, costing and governance frameworks.

CONCLUSIONS

This survey demonstrates wide variation in practice across the UK and identifies barriers to release of human tissue for clinical trial research. Until we can overcome these obstacles, patient samples will remain inaccessible to research. Therefore, this study highlights the urgent need for clear and coordinated national guidance on this issue.

Ancillary Prognostic and Predictive Testing in Breast Cancer: Focus on Discordant, Unusual, and Borderline Results

Ancillary testing in breast cancer has become standard of care to determine what therapies may be most effective for individual patients with breast cancer. Single-marker tests are required on all newly diagnosed and newly metastatic breast cancers. Markers of proliferation are also used, and include both single-marker tests like Ki67 as well as panel-based gene expression tests, which have made more recent contributions to prognostic and predictive testing in breast cancers. This review focuses on pathologist interpretation of these ancillary test results, with a focus on expected versus unexpected results and troubleshooting borderline, unusual, or discordant results.

Characterization of a selective inverse agonist for estrogen related receptor α as a potential agent for breast cancer

The estrogen-related receptor α (ERRα) is an orphan nuclear receptor that plays a primary role in the regulation of cellular energy homeostasis and osteogenesis. It is reported that ERRα is widely expressed in a range of tissues and accumulating evidence has supported that the high expression of ERRα correlates with poor prognosis of various human malignancies, including breast, endometrium, colon, prostate and ovary cancers. Herein is described the discovery of a novel selective inverse agonist (HSP1604) of ERRα, but not of ERRβ and ERRγ, as determined using transient transfection luciferase reporter assay and a time-resolved fluorescence resonance energy transfer (TR-FRET) co-activator assay. HSP1604 potently inhibits ERRα transcriptional activity with IC50=1.47±0.17μM in cell-based luciferase reporter assay and also decreases the protein level of ERRα and the mRNA levels of its downstream target genes such as pyruvate dehydrogenase kinase 4 (PDK4), pS2 and osteopontin. HSP1604 has also suppressed the proliferation of different human cancer cell lines and the migration of breast cancer cells with high expression of ERRα. Representative in vivo results show that HSP1604 suppresses the growth of human breast cancer xenograft in nude mice as doses at 30mg/kg or 100mg/kg administered every other day during 28-day period. HSP1604 thus has the potential both as a new agent to inhibit the growth of tumors and as a chemical probe of ERRα biology.