Genome profiling of ERBB2-amplified breast cancers

Genomics in Clinical trials for Breast Cancer

Breast cancer (B.C.) still has increasing incidences and mortality rates globally. It is known that B.C. and other cancers have a very high rate of genetic heterogeneity and genomic mutations. Traditional oncology approaches have not been able to provide a lasting solution. Targeted therapeutics have been instrumental in handling the complexity and resistance associated with B.C. However, the progress of genomic technology has transformed our understanding of the genetic landscape of breast cancer, opening new avenues for improved anti-cancer therapeutics. Genomics is critical in developing tailored therapeutics and identifying patients most benefit from these treatments. The next generation of breast cancer clinical trials has incorporated next-generation sequencing technologies into the process, and we have seen benefits. These innovations have led to the approval of better-targeted therapies for patients with breast cancer. Genomics has a role to play in clinical trials, including genomic tests that have been approved, patient selection and prediction of therapeutic response. Multiple clinical trials in breast cancer have been done and are still ongoing, which have applied genomics technology. Precision medicine can be achieved in breast cancer therapy with increased efforts and advanced genomic studies in this domain. Genomics studies assist with patient outcomes improvement and oncology advancement by providing a deeper understanding of the biology behind breast cancer. This article will examine the present state of genomics in breast cancer clinical trials.

CDK12 is a potential biomarker for diagnosis, prognosis and immunomodulation in pan-cancer

Cell cycle-dependent protein kinase 12 (CDK12) plays a key role in a variety of carcinogenesis processes and represents a promising therapeutic target for cancer treatment. However, to date, there have been no systematic studies addressing its diagnostic, prognostic and immunological value across cancers. Here, we found that CDK12 was significantly upregulated in various types of cancers, and it expression increased with progression in ten cancer types, including breast cancer, cholangiocarcinoma and colon adenocarcinoma. Moreover, the ROC curves indicated that CDK12 showed diagnostic value in eight cancer types. High CDK12 expression was associated with poor prognosis in eight types of cancer, including low-grade glioma, mesothelioma, melanoma and pancreatic cancer. Furthermore, we conducted immunoassays to explore the exact mechanisms underlying CDK12-induced carcinogenesis, which revealed that increased expression of CDK12 allowed tumours to evade immune surveillance and upregulate immune checkpoint genes. Additionally, mutational studies have shown that amplification and missense mutations are the predominant mutational events affecting CDK12 across cancers. These findings establish CDK12 as a significant biological indicator of cancer diagnosis, prognosis, and immunotherapeutic targeting. Early surveillance and employment of CDK12 inhibitors, along with concomitant immunotherapy interventions, may enhance the clinical outcomes of cancer patients.

Synthesis of Novel Dual Target Inhibitors of CDK12 and PARP1 and Their Antitumor Activities in HER2-Positive Breast Cancers

Several anti-human epidermal growth factor receptor 2 (HER2) treatments have improved the landscape of HER2-positive breast cancer (BC) over the past few years; due to the heterogeneity of the disease itself, the drug resistance mechanisms and relapse are still the main issue in HER2-positive BC. Here, we intended to target simultaneous inhibition of both poly ADP-ribose polymerase 1 (PARP1) and cyclin-dependent kinase 12 (CDK12) that have had an impact on this disease up to their implementation in clinical practice. We successfully screened PARP1 inhibitors (PARPis) containing bicyclic tetrahydropyridine pyrimidines with antitumor activity. Most synthesized compounds with various alcohols were more effective at killing tumor cells than olaparib (ola), especially in HER2-positive cancer cells. Among them, compound 9 showed potent inhibitory effects on PARP1 enzymatic activity and the PAR protein level; moreover, the expression of CDK12 was inhibited by compound 9. Overall, compound 9 exhibited a significant antitumor effect by inhibiting DNA damage repair in tumors.

Short-Term UVB Irradiation Leads to Persistent DNA Damage in Limbal Epithelial Stem Cells, Partially Reversed by DNA Repairing Enzymes

The cornea is frequently exposed to ultraviolet (UV) radiation and absorbs a portion of this radiation. UVB in particular is absorbed by the cornea and will principally damage the topmost layer of the cornea, the epithelium. Epidemiological research shows that the UV damage of DNA is a contributing factor to corneal diseases such as pterygium. There are two main DNA photolesions of UV: cyclobutane pyrimidine dimers (CPDs) and pyrimidine-pyrimidone (6-4) photoproducts (6-4PPs). Both involve the abnormal linking of adjacent pyrimide bases. In particular, CPD lesions, which account for the vast majority of UV-induced lesions, are inefficiently repaired by nucleotide excision repair (NER) and are thus mutagenic and linked to cancer development in humans. Here, we apply two exogenous enzymes: CPD photolyase (CPDPL) and T4 endonuclease V (T4N5). The efficacy of these enzymes was assayed by the proteomic and immunofluorescence measurements of UVB-induced CPDs before and after treatment. The results showed that CPDs can be rapidly repaired by T4N5 in cell cultures. The usage of CPDPL and T4N5 in ex vivo eyes revealed that CPD lesions persist in the corneal limbus. The proteomic analysis of the T4N5-treated cells shows increases in the components of the angiogenic and inflammatory systems. We conclude that T4N5 and CPDPL show great promise in the treatment of CPD lesions, but the complete clearance of CPDs from the limbus remains a challenge.

Oncofetal reprogramming in tumour development and progression

Embryonic development is characterized by rapidly dividing cells, cellular plasticity and a highly vascular microenvironment. These features are similar to those of tumour tissue, in that malignant cells are characterized by their ability to proliferate and exhibit cellular plasticity. The tumour microenvironment also often includes immunosuppressive features. Reciprocal communication between various cellular subpopulations enables fetal and tumour tissues to proliferate, migrate and escape immune responses. Fetal-like reprogramming has been demonstrated in the tumour microenvironment, indicating extraordinary cellular plasticity and bringing an additional layer of cellular heterogeneity. More importantly, some of these features are also present during inflammation. This Perspective discusses the similarity between embryogenesis, inflammation and tumorigenesis, and describes the mechanisms of oncofetal reprogramming that enable tumour cells to escape from immune responses, promoting tumour growth and metastasis.

IKZF3 amplification frequently occurs in HER2-positive breast cancer and is a potential therapeutic target

Breast cancer is one of the leading causes of cancer death in women, and although treatment outcome has substantially improved in the past decades, advanced or metastatic breast cancers still carry a poor prognosis. Gene amplification is one of the frequent genetic alterations in cancer, and oncogene amplification may be associated with cancer aggressiveness and oncogenicity. Targeting amplified genes such as HER2 has vastly improved disease outcome and survival, and anti-HER2 therapeutics have revolutionized the standard of care in HER2 breast cancer. Besides currently known druggable gene amplifications including ERBB2 and FGFR2, other frequently amplified genes are relatively less well known for function and clinical significance. By querying four large databases from TCGA and AACR-Genie, from a total of 11,890 patients with invasive ductal breast carcinoma, we discover IKZF3, CCND1, ERBB2 to be consistently amplified across different cohorts. We further identify IKZF3 as a frequently amplified gene in breast cancer with a prevalence of 12-15% amplification rate. Interestingly, IKZF3 amplification is frequently co-amplified with ERBB2/HER2, and is also associated with worse prognosis compared to IKZF3 non-amplified cancers. Analysis of HER2 breast cancer patients treated with trastuzumab revealed decrease in both ERBB2/HER2 and IKZF3 expression. Further investigation using the DepMap for gene dependency by genome-wide CRISPR screening revealed dependence on IKZF3 in HER2 breast cancer cell lines. Our study utilized an integrative analysis of large-scale patient genomics, transcriptomics and clinical data to reveal IKZF3 as a frequently amplified gene, and suggest a potential role of IKZF3 as a druggable target for HER2 breast cancer.

JWA suppresses proliferation in trastuzumab-resistant breast cancer by downregulating CDK12

Breast cancer is the most common cancer worldwide. JWA is a microtubule-associated protein that has been identified as a tumor suppressor, and its downregulation in tumors is an independent adverse prognostic factor. The objective of this study was to explore the expression, regulation, and mechanism of JWA in trastuzumab-resistant breast cancers. In this study, we found that JWA expression was lower in trastuzumab-resistant breast cancers than that in trastuzumab-sensitive breast cancers. Furthermore, it was confirmed that overexpression of JWA inhibited proliferation and promoted apoptosis in trastuzumab-resistant breast cancers both in vitro and in vivo. In addition, the low expression of JWA in trastuzumab-resistant breast cancers is associated with a poor prognosis. Combining RNA-sequence datasets and next-generation sequencing, it was found that JWA negatively regulated CDK12, and was involved in the G1-to-S transition of the cell cycle. It has been reported that CDK12 drives breast cancer initiation and induces trastuzumab resistance. Taken together, high expression of JWA could inhibit the growth of trastuzumab-resistant breast cancer, and JWA is a potential predictive marker for trastuzumab resistance. In addition, targeted therapy with JWA may be a novel therapeutic strategy to improve the survival rate of trastuzumab-resistant breast cancer.

Amplification of ERBB2 (HER2) in embryonal rhabdomyosarcoma: A potential treatment target in rare cases?

The ERBB2 gene encodes a receptor tyrosine kinase also known as HER2. The gene is amplified and overexpressed in one-fifth of breast carcinomas; patients with such tumors benefit from targeted treatment with trastuzumab or other drugs blocking the receptor. In addition, ERBB2 has been shown to be amplified and/or overexpressed in a variety of other malignancies. Notably, both alveolar and embryonal rhabdomyosarcoma (RMS), especially in children, often show increased expression of ERBB2. Although high-level amplification of the gene has not been described in RMS, its frequent expression at the cell surface of RMS cells has been exploited for chimeric antigen receptor T-cell (CAR T)-based treatment strategies. We here describe two cases of pediatric, fusion-negative embryonal RMS with high-level amplification of the ERBB2 gene. One patient is currently treated with conventional chemotherapy for a recently detected standard risk RMS, whereas the other patient died from metastatic disease. Both tumors displayed focal amplicons (210 and 274 Kb, respectively) in chromosome band 17q12, with proximal and distal borders corresponding to those typically seen in breast cancer. In both tumors, the ERBB2 amplicon correlated with high expression at the RNA and protein levels. Thus, breast cancer-like ERBB2 amplification is a very rare, but recurrent feature of pediatric RMS, and should be exploited as an alternative treatment target.

Chromoanagenesis Landscape in 10,000 TCGA Patients

During the past decade, whole-genome sequencing of tumor biopsies and individuals with congenital disorders highlighted the phenomenon of chromoanagenesis, a single chaotic event of chromosomal rearrangement. Chromoanagenesis was shown to be frequent in many types of cancers, to occur in early stages of cancer development, and significantly impact the tumor's nature. However, an in-depth, cancer-type dependent analysis has been somewhat incomplete due to the shortage in whole genome sequencing of cancerous samples. In this study, we extracted data from The Pan-Cancer Analysis of Whole Genome (PCAWG) and The Cancer Genome Atlas (TCGA) to construct and test a machine learning algorithm that can detect chromoanagenesis with high accuracy (86%). The algorithm was applied to ~10,000 unlabeled TCGA cancer patients. We utilize the chromoanagenesis assignment results, to analyze cancer-type specific chromoanagenesis characteristics in 20 TCGA cancer types. Our results unveil prominent genes affected in either chromoanagenesis or non-chromoanagenesis tumorigenesis. The analysis reveals a mutual exclusivity relationship between the genes impaired in chromoanagenesis versus non-chromoanagenesis cases. We offer the discovered characteristics as possible targets for cancer diagnostic and therapeutic purposes.

A review of the endocrine resistance in hormone-positive breast cancer

Hormone-positive breast cancer (BC) is a unique heterogeneous disease with a favorable prognosis compared to other types of breast cancer. As tumor biology influences the prognosis and clinical treatment, a deep understanding of how the molecular mechanisms regulate hormone sensitivity or resistance is critical in improving the efficacy and overcoming the endocrine resistance. This article comprehensively reviews the endocrine resistance in hormone-positive BC from a molecular and genetic perspective, encompassing the updated treatment and developing direction. This review includes the mechanisms of hormone resistance, which vary from epigenetic changes, crosstalk between signaling networks, cell cycle aberrance, and even change in the tumor microenvironment (TME) or stem cell. These mechanisms may contribute to treatment resistance. Current targeted therapy for hormone-resistant tumors includes PI3K/AKT/mTOR and cdk4/6 inhibitors. Several relevant pathways, biomarkers, and predictor genes have also been identified. Immunotherapy so far has a relatively less crucial role in hormone-positive than in triple-negative BC. Furthermore, the methodology to identify the PDL1 is not standardized. In a molecule and gene study, next-generation sequencing with circulating tumor DNA (ctDNA) has recently appeared as a sensitive and minimally invasive tool worth investigating.

WBP2 promotes BTRC mRNA stability to drive migration and invasion in triple-negative breast cancer via NF-κB activation

WW‐domain‐binding protein 2 (WBP2) is an oncogene that drives breast carcinogenesis through regulating Wnt, estrogen receptor (ER), and Hippo signaling. Recent studies have identified neoteric modes of action of WBP2 other than its widely recognized function as a transcriptional coactivator. Here, we identified a previously unexplored role of WBP2 in inflammatory signaling in breast cancer via an integrated proteogenomic analysis of The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA BRCA) dataset. WBP2 was shown to enhance the migration and invasion in triple‐negative breast cancer (TNBC) cells especially under tumor necrosis factor alpha (TNF‐α) stimulation. Molecularly, WBP2 potentiates TNF‐α‐induced nuclear factor kappa B (NF‐κB) transcriptional activity and nuclear localization through aggrandizing ubiquitin‐mediated proteasomal degradation of its upstream inhibitor, NF‐κB inhibitor alpha (NFKBIA; also known as IκBα). We further demonstrate that WBP2 induces mRNA stability of beta‐transducin repeat‐containing E3 ubiquitin protein ligase (BTRC), which targets IκBα for ubiquitination and degradation. Disruption of IκBα rescued the impaired migratory and invasive phenotypes in WBP2‐silenced cells, while loss of BTRC ameliorated WBP2‐driven migration and invasion. Clinically, the WBP2‐BTRC‐IκBα signaling axis correlates with poorer prognosis in breast cancer patients. Our findings reveal a pivotal mechanism of WBP2 in modulating BTRC‐IκBα‐NF‐κB pathway to promote TNBC aggressiveness.

Evaluation of Somatic Mutations in Solid Metastatic Pan-Cancer Patients

Metastasis continues to be the primary cause of all cancer-related deaths despite the recent advancements in cancer treatments. To evaluate the role of mutations in overall survival (OS) and treatment outcomes, we analyzed 957 metastatic patients with seven major cancer types who had available molecular testing results with a FoundationOne CDx® panel. The most prevalent genes with somatic mutations were TP53, KRAS, APC, and LRP1B. In this analysis, these genes had mutation frequencies higher than in publicly available datasets. We identified that the somatic mutations were seven mutually exclusive gene pairs and an additional fifty-two co-occurring gene pairs. Mutations in the mutually exclusive gene pair APC and CDKN2A showed an opposite effect on the overall survival. However, patients with CDKN2A mutations showed significantly shorter OS (HR: 1.72, 95% CI: 1.34-2.21, p < 0.001) after adjusting for cancer type, age at diagnosis, and sex. Five-year post metastatic diagnosis survival analysis showed a significant improvement in OS (median survival 28 and 43 months in pre-2015 and post-2015 metastatic diagnosis, respectively, p = 0.00021) based on the year of metastatic diagnosis. Although the use of targeted therapies after metastatic diagnosis prolonged OS, the benefit was not statistically significant. However, longer five-year progression-free survival (PFS) was significantly associated with targeted therapy use (median 10.9 months (CI: 9.7-11.9 months) compared to 9.1 months (CI: 8.1-10.1 months) for non-targeted therapy, respectively, p = 0.0029). Our results provide a clinically relevant overview of the complex molecular landscape and survival mechanisms in metastatic solid cancers.

Tumor levels of the mediators of ErbB2-driven anoikis resistance correlate with breast cancer relapse in patients receiving trastuzumab-based therapies

PURPOSE

Patients with ErbB2/Her2 oncoprotein-positive breast cancers often receive neoadjuvant therapies (NATs) containing the anti-ErbB2 antibody trastuzumab. Tumors that are still present after NATs are resected, and patients continue receiving trastuzumab. These cancers are associated with high relapse risk. Whether relapse will occur cannot be presently reliably predicted. The ability to make such predictions could improve disease management. We found previously that ErbB2 blocks breast tumor cell anoikis, apoptosis induced by cell detachment from the extracellular matrix, by downregulating the pro-apoptotic protein Irf6 and upregulating the anti-apoptotic protein Epidermal Growth Factor Receptor (EGFR) in the cells and, thus, promotes their three-dimensional growth. We now tested whether tumor levels of these proteins before and after NATs correlate with patients' relapse-free survival (RFS) and overall survival (OS).

METHODS

We selected archival breast tumor samples collected from 37 women with ErbB2-positive stages II and III breast cancer before and after NATs. We used immunohistochemistry to test whether levels of the indicated proteins in respective tumors correlate with RFS and OS.

RESULTS

We observed that the presence of high Irf6 levels in the tumors following NATs correlated with reduced RFS and OS. Perhaps not by coincidence, we noticed that trastuzumab-sensitive ErbB2-positive breast cancer cells selected for the ability to overproduce exogenous Irf6 in culture acquired trastuzumab resistance. Finally, EGFR presence in patients' tumors before or after NATs was associated with decreased RFS and OS.

CONCLUSIONS

This study could help identify patients with ErbB2-positive tumors that are at increased risk of disease relapse following NATs.

CDK12: a potential therapeutic target in cancer

Cyclin-dependent kinase (CDK) 12 engages in diversified biological functions, from transcription, post-transcriptional modification, cell cycle, and translation to cellular proliferation. Moreover, it regulates the expression of cancer-related genes involved in DNA damage response (DDR) and replication, which are responsible for maintaining genomic stability. CDK12 emerges as an oncogene or tumor suppressor in different cellular contexts, where its dysregulation results in tumorigenesis. Current CDK12 inhibitors are nonselective, which impedes the process of pharmacological target validation and drug development. Herein, we discuss the latest understanding of the biological roles of CDK12 in cancers and provide molecular analyses of CDK12 inhibitors to guide the rational design of selective inhibitors.

Targeting CDK12 for Cancer Therapy: Function, Mechanism, and Drug Discovery

Cyclin-dependent kinase 12 (CDK12) is a member of the CDK family of proteins (CDK) and is critical for cancer development. Years of study into CDK12 have generated much information regarding the intricacy of its function and mechanism as well as inhibitors against it for oncological research. However, there remains a lack of understanding regarding the role of CDK12 in carcinogenesis and cancer prevention. An exhaustive comprehension of CDK12 will highly stimulate the development of new strategies for treating and preventing cancer. Here, we review the literature of CDK12, with a focus on its function, its role in signaling, and how to use it as a target for discovery of novel drugs for cancer prevention and therapy.

Integrated system for detection and molecular characterization of circulating tumor cells

Circulating tumor cells (CTCs) invade blood vessels in solid tumors and promote metastases by circulating in the blood. CTCs are thus recognized as targets for liquid biopsy and can provide useful information for design of treatments. This diagnostic approach must consider not only the number of CTCs but also their molecular and genetic characteristics. For this purpose, use of devices that enrich CTCs independent of these characteristics and detectors that recognize various CTC characteristics is essential. In the present study, we developed a CTC detection system comprising ClearCell FX and ImageStream Mark II. We clarified the analytical performance of this system by evaluating recovery rate, lower limits of detection, and linearity. These parameters are critical for detecting rare cells, such as CTCs. We tested these parameters using three cell lines with different expression levels of the epithelial marker-epithelial cell adhesion molecule (EpCAM) and spiked these cells into whole-blood samples from healthy donors. The average recovery rate and lower limit of detection were approximately 40% and five cells/7.5 mL of whole blood, respectively. High linearity was observed for all evaluated samples. We also evaluated the ability of the system to distinguish between normal and abnormal cells based on protein expression levels and gene amplification and found that the system can identify abnormal cells using these characteristics. The CTC detection system thus displays the ability to distinguish specific characteristics of CTC, thereby providing valuable information for cancer treatment.

Identification of specific microRNA-messenger RNA regulation pairs in four subtypes of breast cancer

Four subtypes of breast cancer, luminal A, luminal B, basal-like, human epidermal growth factor receptor-enriched, have been identified based on gene expression profiles of human tumours. The goal of this study is to find whether the same groups' genes would exhibit different networks among the four subtypes. Differential expressed genes between each of the four subtypes and the normal samples were identified. The overlaps between the four groups of differentially expressed genes were used to construct regulations networks for each of the four subtypes. Univariate and multivariate Cox regressions were employed to test the genes in the four regulation networks. This study demonstrated that the common genes in four subtypes showed different regulation. Also, the hsa-miR-182 and decorin pair performs different functions among the four subtypes of breast cancer. The result indicated that heterogeneity of breast cancer is not only reflected in the different expression patterns among different genes, but also in the different regulatory networks of the same group of genes.

Development and Validation of a 12-Gene Immune Relevant Prognostic Signature for Lung Adenocarcinoma Through Machine Learning Strategies

Background: Although immunotherapy with checkpoint inhibitors is changing the face of lung adenocarcinoma (LUAD) treatments, only limited patients could benefit from it. Therefore, we aimed to develop an immune-relevant-gene-based signature to predict LUAD patients' prognosis and to characterize their tumor microenvironment thus guiding therapeutic strategy.

Methods and Materials: Gene expression data of LUAD patients from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were systematically analyzed. We performed Cox regression and random survival forest algorithm to identify immune-relevant genes with potential prognostic value. A risk score formula was then established by integrating these selected genes and patients were classified into high- and low-risk score group. Differentially expressed genes, infiltration level of immune cells, and several immune-associated molecules were further compared across the two groups.

Results: Nine hundred and fifty-four LUAD patients were enrolled in this study. After implementing the 2-steps machine learning screening methods, 12 immune-relevant genes were finally selected into the risk-score formula and the patients in high-risk group had significantly worse overall survival (HR = 10.6, 95%CI = 3.21–34.95, P < 0.001). We also found the distinct immune infiltration patterns in the two groups that several immune cells like cytotoxic cells and immune checkpoint molecules were significantly enriched and upregulated in patients from the high-risk group. These findings were further validated in two independent LUAD cohorts.

Conclusion: Our risk score formula could serve as a powerful and accurate tool for predicting survival of LUAD patients and may facilitate clinicians to choose the optimal therapeutic regimen more precisely.

Multi-omic signatures identify pan-cancer classes of tumors beyond tissue of origin

Despite recent advances in treatment, cancer continues to be one of the most lethal human maladies. One of the challenges of cancer treatment is the diversity among similar tumors that exhibit different clinical outcomes. Most of this variability comes from wide-spread molecular alterations that can be summarized by omic integration. Here, we have identified eight novel tumor groups (C1-8) via omic integration, characterized by unique cancer signatures and clinical characteristics. C3 had the best clinical outcomes, while C2 and C5 had poorest. C1, C7, and C8 were upregulated for cellular and mitochondrial translation, and relatively low proliferation. C6 and C4 were also downregulated for cellular and mitochondrial translation, and had high proliferation rates. C4 was represented by copy losses on chromosome 6, and had the highest number of metastatic samples. C8 was characterized by copy losses on chromosome 11, having also the lowest lymphocytic infiltration rate. C6 had the lowest natural killer infiltration rate and was represented by copy gains of genes in chromosome 11. C7 was represented by copy gains on chromosome 6, and had the highest upregulation in mitochondrial translation. We believe that, since molecularly alike tumors could respond similarly to treatment, our results could inform therapeutic action.

ERα-related chromothripsis enhances concordant gene transcription on chromosome 17q11.1-q24.1 in luminal breast cancer

Background

Chromothripsis is an event of genomic instability leading to complex chromosomal alterations in cancer. Frequent long-range chromatin interactions between transcription factors (TFs) and targets may promote extensive translocations and copy-number alterations in proximal contact regions through inappropriate DNA stitching. Although studies have proposed models to explain the initiation of chromothripsis, few discussed how TFs influence this process for tumor progression.

Methods

This study focused on genomic alterations in amplification associated regions within chromosome 17. Inter−/intra-chromosomal rearrangements were analyzed using whole genome sequencing data of breast tumors in the Cancer Genome Atlas (TCGA) cohort. Common ERα binding sites were defined based on MCF-7, T47D, and MDA-MB-134 breast cancer cell lines using univariate K-means clustering methods. Nanopore sequencing technology was applied to validate frequent rearrangements detected between ATC loci on 17q23 and an ERα hub on 20q13. The efficacy of pharmacological inhibition of a potentially druggable target gene on 17q23 was evaluated using breast cancer cell lines and patient-derived circulating breast tumor cells.

Results

There are five adjoining regions from 17q11.1 to 17q24.1 being hotspots of chromothripsis. Inter−/intra-chromosomal rearrangements of these regions occurred more frequently in ERα-positive tumors than in ERα-negative tumors. In addition, the locations of the rearrangements were often mapped within or close to dense ERα binding sites localized on these five 17q regions or other chromosomes. This chromothriptic event was linked to concordant upregulation of 96 loci that predominantly regulate cell-cycle machineries in advanced luminal tumors. Genome-editing analysis confirmed that an ERα hub localized on 20q13 coordinately regulates a subset of these loci localized on 17q23 through long-range chromosome interactions. One of these loci, Tousled Like Kinase 2 (TLK2) known to participate in DNA damage checkpoint control, is an actionable target using phenothiazine antipsychotics (PTZs). The antiproliferative effect of PTZs was prominent in high TLK2-expressing cells, compared to low expressing cells.

Conclusion

This study demonstrates a new approach for identifying tumorigenic drivers from genomic regions highly susceptible to ERα-related chromothripsis. We found a group of luminal breast tumors displaying 17q-related chromothripsis for which antipsychotics can be repurposed as treatment adjuncts.

Molecular signatures for inflammation vary across cancer types and correlate significantly with tumor stage, sex and vital status of patients

Cancer affects millions of individuals worldwide. One shortcoming of traditional cancer classification systems is that, even for tumors affecting a single organ, there is significant molecular heterogeneity. Precise molecular classification of tumors could be beneficial in personalizing patients’ therapy and predicting prognosis. To this end, here we propose to use molecular signatures to further refine cancer classification. Molecular signatures are collections of genes characterizing particular cell types, tissues or disease. Signatures can be used to interpret expression profiles from heterogeneous samples. Large collections of gene signatures have previously been cataloged in the MSigDB database. We have developed a web-based Signature Visualization Tool (SaVanT) to display signature scores in user-generated expression data. Here we have undertaken a systematic analysis of correlations between inflammatory signatures and cancer samples, to test whether inflammation can differentiate cancer types. Inflammatory response signatures were obtained from MsigDB and SaVanT and a signature score was computed for samples associated with 7 different cancer types. We first identified types of cancers that had high inflammation levels as measured by these signatures. The correlation between signature scores and metadata of these patients (sex, age at initial cancer diagnosis, cancer stage, and vital status) was then computed. We sought to evaluate correlations between inflammation with other clinical parameters and identified four cancer types that had statistically significant association (p-value < 0.05) with at least one clinical characteristic: pancreas adenocarcinoma (PAAD), cholangiocarcinoma (CHOL), kidney chromophobe (KICH), and uveal melanoma (UVM). These results may allow future studies to use these approaches to further refine cancer subtyping and ultimately treatment.

Somatic mutations and copy number variations in breast cancers with heterogeneous HER2 amplification

Intratumour heterogeneity fuels carcinogenesis and allows circumventing specific targeted therapies. HER2 gene amplification is associated with poor outcome in invasive breast cancer. Heterogeneous HER2 amplification has been described in 5–41% of breast cancers. Here, we investigated the genetic differences between HER2‐positive and HER2‐negative admixed breast cancer components. We performed an in‐depth analysis to explore the potential heterogeneity in the somatic mutational landscape of each individual tumour component. Formalin‐fixed, paraffin‐embedded breast cancer tissue of ten patients with at least one HER2‐negative and at least one HER2‐positive component was microdissected. Targeted next‐generation sequencing was performed using a customized 53‐gene panel. Somatic mutations and copy number variations were analysed. Overall, the tumours showed a heterogeneous distribution of 12 deletions, 9 insertions, 32 missense variants and 7 nonsense variants in 26 different genes, which are (likely) pathogenic. Three splice site alterations were identified. One patient had an EGFR copy number gain restricted to a HER2‐negative in situ component, resulting in EGFR protein overexpression. Two patients had FGFR1 copy number gains in at least one tumour component. Two patients had an 8q24 gain in at least one tumour component, resulting in a copy number increase in MYC and PVT1. One patient had a CCND1 copy number gain restricted to a HER2‐negative tumour component. No common alternative drivers were identified in the HER2‐negative tumour components. This series of 10 breast cancers with heterogeneous HER2 gene amplification illustrates that HER2 positivity is not an unconditional prerequisite for the maintenance of tumour growth. Many other molecular aberrations are likely to act as alternative or collaborative drivers. This study demonstrates that breast carcinogenesis is a dynamically evolving process characterized by a versatile somatic mutational profile, of which some genetic aberrations will be crucial for cancer progression, and others will be mere ‘passenger’ molecular anomalies.

CDK12: cellular functions and therapeutic potential of versatile player in cancer

Cyclin-dependent kinase 12 (CDK12) phosphorylates the C-terminal domain of RNA polymerase II and is needed for the optimal transcription elongation and translation of a subset of human protein-coding genes. The kinase has a pleiotropic effect on the maintenance of genome stability, and its inactivation in prostate and ovarian tumours results in focal tandem duplications, a CDK12-unique genome instability phenotype. CDK12 aberrations were found in many other malignancies and have the potential to be used as biomarkers for therapeutic intervention. Moreover, the inhibition of CDK12 emerges as a promising strategy for treatment in several types of cancers. In this review, we summarize mechanisms that CDK12 utilizes for the regulation of gene expression and discuss how the perturbation of CDK12-sensitive genes contributes to the disruption of cell cycle progression and the onset of genome instability. Furthermore, we describe tumour-suppressive and oncogenic functions of CDK12 and its potential as a biomarker and inhibition target in anti-tumour treatments.

Comutation of PIK3CA and TP53 in Residual Disease After Preoperative Anti-HER2 Therapy in ERBB2 (HER2)-Amplified Early Breast Cancer

PURPOSE

To identify proteomic and genomic alterations in residual disease (RD) for human epidermal growth factor receptor 2 (HER2)-positive (HER2+) breast cancer (BC) after preoperative trastuzumab (H), lapatinib (L), or both (H+L) in combination with chemotherapy.

PATIENTS AND METHODS

Patients with stage II/III HER2+ BC (n = 100) were randomly assigned to preoperative treatment with H versus L 1,250mg versus H+L (L: 750 to 1,000 mg) plus 5-fluorouracil, epirubicin, and cyclophosphamide, followed by weekly paclitaxel. After receiving institutional review board–approved informed consent, targeted next-generation sequencing was performed on 20 patients’ formalin-fixed paraffin embedded tumors to characterize genomic alterations across 287 cancer-related genes. Reverse phase protein array (RPPA) analysis was performed on both the baseline biopsy and RD specimens, when available.

RESULTS

Two of 20 RD tissues were HER2 negative per next-generation sequencing; one sample had insufficient tissue. Of six pretreatment biopsy specimens, four were comutated with TP53 and PIK3CA. Of 17 HER2+ RD, seven specimens (41%) had PIK3CA mutations always comutated with TP53, and four (24%) also had concurrent CDK12 amplification. Overall, CDK12 amplification was observed in eight of the 17 (47%) HER2+ RD specimens. A total of 12 RD specimens (71%) had TP53 mutations. Although prevalence of individual TP53 and PIK3CA mutations was only modestly higher than published estimates for those in HER2+ primary BCs (55% and 32% for TP53 and PIK3CA, respectively), prevalence of these as comutations appeared higher (41%), compared with less than 10% in several series. On RPPA analysis of the RD tissue with comutations, the strongest Spearman ρ correlations were limited to EGFR and phospho-AKT (ρ, 0.999; P = .019) and phospho-mTOR and phospho-S6 ribosomal protein (ρ, 0.994; P = .048).

CONCLUSION

HER2-amplified RD tissue after preoperative H, L, or H+L plus chemotherapy was enriched for PIK3CA and TP53 comutations, and the RD tissue demonstrated activation of EGFR/AKT/mTOR signaling on RPPA.

Potent Antitumor Activity of Liposomal Irinotecan in an Organoid- and CRISPR-Cas9-Based Murine Model of Gallbladder Cancer

Gallbladder cancer is associated with a dismal prognosis, and accurate in vivo models will be elemental to improve our understanding of this deadly disease and develop better treatment options. We have generated a transplantation-based murine model for gallbladder cancer that histologically mimics the human disease, including the development of distant metastasis. Murine gallbladder–derived organoids are genetically modified by either retroviral transduction or transfection with CRISPR/Cas9 encoding plasmids, thereby allowing the rapid generation of complex cancer genotypes. We characterize the model in the presence of two of the most frequent oncogenic drivers—Kras and ERBB2—and provide evidence that the tumor histology is highly dependent on the driver oncogene. Further, we demonstrate the utility of the model for the preclinical assessment of novel therapeutic approaches by showing that liposomal Irinotecan (Nal-IRI) is retained in tumor cells and significantly prolongs the survival of gallbladder cancer–bearing mice compared to conventional irinotecan.

CDK12 drives breast tumor initiation and trastuzumab resistance via WNT and IRS1-ErbB-PI3K signaling

Cyclin-dependent kinase 12 (CDK12) has emerged as an effective therapeutic target due to its ability to regulate DNA damage repair in human cancers, but little is known about the role of CDK12 in driving tumorigenesis. Here, we demonstrate that CDK12 promotes tumor initiation as a novel regulator of cancer stem cells (CSCs) and induces anti-HER2 therapy resistance in human breast cancer. High CDK12 expression caused by concurrent amplification of CDK12 and HER2 in breast cancer patients is associated with disease recurrence and poor survival. CDK12 induces self-renewal of breast CSCs and in vivo tumor-initiating ability, and also reduces susceptibility to trastuzumab. Furthermore, CDK12 kinase activity inhibition facilitates anticancer efficacy of trastuzumab in HER2+ tumors, and mice bearing trastuzumab-resistant HER2+ tumor show sensitivity to an inhibitor of CDK12. Mechanistically, the catalytic activity of CDK12 is required for the expression of genes involved in the activation of ErbB-PI3K-AKT or WNT-signaling cascades. These results suggest that CDK12 is a major oncogenic driver and an actionable target for HER2+ breast cancer to replace or augment current anti-HER2 therapies.

A meta-analysis of multiple matched aCGH/expression cancer datasets reveals regulatory relationships and pathway enrichment of potential oncogenes

The copy numbers of genes in cancer samples are often highly disrupted and form a natural amplification/deletion experiment encompassing multiple genes. Matched array comparative genomics and transcriptomics datasets from such samples can be used to predict inter-chromosomal gene regulatory relationships. Previously we published the database METAMATCHED, comprising the results from such an analysis of a large number of publically available cancer datasets. Here we investigate genes in the database which are unusual in that their copy number exhibits consistent heterogeneous disruption in a high proportion of the cancer datasets. We assess the potential relevance of these genes to the pathology of the cancer samples, in light of their predicted regulatory relationships and enriched biological pathways. A network-based method was used to identify enriched pathways from the genes’ inferred targets. The analysis predicts both known and new regulator-target interactions and pathway memberships. We examine examples in detail, in particular the gene POGZ, which is disrupted in many of the cancer datasets and has an unusually large number of predicted targets, from which the network analysis predicts membership of cancer related pathways. The results suggest close involvement in known cancer pathways of genes exhibiting consistent heterogeneous copy number disruption. Further experimental work would clarify their relevance to tumor biology. The results of the analysis presented in the database METAMATCHED, and included here as an R archive file, constitute a large number of predicted regulatory relationships and pathway memberships which we anticipate will be useful in informing such experiments.

ClearF: a supervised feature scoring method to find biomarkers using class-wise embedding and reconstruction

BACKGROUND

Feature selection or scoring methods for the detection of biomarkers are essential in bioinformatics. Various feature selection methods have been developed for the detection of biomarkers, and several studies have employed information-theoretic approaches. However, most of these methods generally require a long processing time. In addition, information-theoretic methods discretize continuous features, which is a drawback that can lead to the loss of information.

RESULTS

In this paper, a novel supervised feature scoring method named ClearF is proposed. The proposed method is suitable for continuous-valued data, which is similar to the principle of feature selection using mutual information, with the added advantage of a reduced computation time. The proposed score calculation is motivated by the association between the reconstruction error and the information-theoretic measurement. Our method is based on class-wise low-dimensional embedding and the resulting reconstruction error. Given multi-class datasets such as a case-control study dataset, low-dimensional embedding is first applied to each class to obtain a compressed representation of the class, and also for the entire dataset. Reconstruction is then performed to calculate the error of each feature and the final score for each feature is defined in terms of the reconstruction errors. The correlation between the information theoretic measurement and the proposed method is demonstrated using a simulation. For performance validation, we compared the classification performance of the proposed method with those of various algorithms on benchmark datasets.

CONCLUSIONS

The proposed method showed higher accuracy and lower execution time than the other established methods. Moreover, an experiment was conducted on the TCGA breast cancer dataset, and it was confirmed that the genes with the highest scores were highly associated with subtypes of breast cancer.

Grade-specific diagnostic and prognostic biomarkers in breast cancer

An integrative approach is presented to identify grade-specific biomarkers for breast cancer. Grade-specific molecular interaction networks were constructed with differentially expressed genes (DEGs) of cancer grade 1, 2, and 3. We observed that the molecular network of grade3 is predominantly associated with cancer-specific processes. Among the top ten connected DEGs in the grade3, the increase in the expression of UBE2C and CCNB2 genes was statistically significant across different grades. Along with UBE2C and CCNB2 genes, the CDK1, KIF2C, NDC80, and CCNB2 genes are also profoundly expressed in different grades and reduce the patient's survival. Gene set enrichment analysis of these six genes reconfirms their role in metastatic phenotype. Moreover, the coexpression network shows a strong association of these six genes promotes cancer specific biological processes and possibly drives cancer from lower to a higher grade. Collectively the identified genes can act as potential biomarkers for breast cancer diagnosis and prognosis.

EYA2 Correlates With Clinico-Pathological Features of Breast Cancer, Promotes Tumor Proliferation, and Predicts Poor Survival

Eyes absent homolog 2 (EYA2), a transcriptional activator, is pivotal for organ development, but aberrant regulation of EYA2 has been reported in multiple human tumors. However, the role of EYA2 in breast cancer is still lack of full understanding. To explore the biological significance of EYA2 in breast cancer, we conducted data analysis on public breast cancer datasets, and performed immunohistochemistry (IHC) analysis, colony-forming unit assays, EdU assay, western blotting, and immunofluorescence (IF). Meta-analysis showed that EYA2 mRNA expression was correlated with tumor grade, the status of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). IHC analysis displayed that EYA2 protein abundance was inversely associated with the status of ER and PR, and enriched in triple-negative breast cancer in comparison with luminal-type tumors. Additionally, correlation analysis reflected that EYA2 mRNA was negatively correlated with luminal markers, and positively associated with markers of basal cells, epithelial-mesenchymal transition and cancer stem cells. Clone-forming assay and EdU experiment showed that EYA2 overexpression enhanced proliferation of breast cancer cells. Results from western blotting and IF displayed that overexpression of EYA2 up-regulated the protein abundance of proliferation markers. Importantly, survival analysis indicated that higher EYA2 mRNA level predicted worse overall survival, relapse-free survival and metastasis-free survival among whole enrolled breast cancer patients. Collectively, EYA2 was closely correlated with clinico-pathological characteristics, and served as a proliferation stimulator for breast cancer cells and an unfavorable prognostic element for breast cancer patients, suggesting that EYA2 is involved in the progression of breast carcinoma.

Teneurins: An Integrative Molecular, Functional, and Biomedical Overview of Their Role in Cancer

Teneurins are large transmembrane proteins originally identified in Drosophila. Their essential role in development of the central nervous system is conserved throughout species, and evidence supports their involvement in organogenesis of additional tissues. Homophilic and heterophilic interactions between Teneurin paralogues mediate cellular adhesion in crucial processes such as neuronal pathfinding and synaptic organization. At the molecular level, Teneurins are proteolytically processed into distinct subdomains that have been implicated in extracellular and intracellular signaling, and in transcriptional regulation. Phylogenetic studies have shown a high degree of intra- and interspecies conservation of Teneurin genes. Accordingly, the occurrence of genetic variants has been associated with functional and phenotypic alterations in experimental systems, and with some inherited or sporadic conditions. Recently, tumor-related variations in Teneurin gene expression have been associated with patient survival in different cancers. Although these findings were incidental and molecular mechanisms were not addressed, they suggested a potential utility of Teneurin transcript levels as biomarkers for disease prognosis. Mutations and chromosomal alterations affecting Teneurin genes have been found occasionally in tumors, but literature remains scarce. The analysis of open-access molecular and clinical datasets derived from large oncologic cohorts provides an invaluable resource for the identification of additional somatic mutations. However, Teneurin variants have not been classified in terms of pathogenic risk and their phenotypic impact remains unknown. On this basis, is it plausible to hypothesize that Teneurins play a role in carcinogenesis? Does current evidence support a tumor suppressive or rather oncogenic function for these proteins? Here, we comprehensively discuss available literature with integration of molecular evidence retrieved from open-access databases. We show that Teneurins undergo somatic changes comparable to those of well-established cancer genes, and discuss their involvement in cancer-related signaling pathways. Current data strongly suggest a functional contribution of Teneurins to human carcinogenesis.

Establishment and characterization of a novel vincristine-resistant diffuse large B-cell lymphoma cell line containing the 8q24 homogeneously staining region

Chromosome band 8q24 is the most frequently amplified locus in various types of cancers. MYC has been identified as the primary oncogene at the 8q24 locus, whereas a long noncoding gene, PVT1, which lies adjacent to MYC, has recently emerged as another potential oncogenic regulator at this position. In this study, we established and characterized a novel cell line, AMU‐ML2, from a patient with diffuse large B‐cell lymphoma (DLBCL), displaying homogeneously staining regions at the 8q24 locus. Fluorescence in situ hybridization clearly detected an elevation in MYC copy numbers corresponding to the homogenously staining region. In addition, a comparative genomic hybridization analysis using high‐resolution arrays revealed that the 8q24 amplicon size was 1.4 Mb, containing the entire MYC and PVT1 regions. We also demonstrated a loss of heterozygosity for TP53 at 17p13 in conjunction with a TP53 frameshift mutation. Notably, AMU‐ML2 cells exhibited resistance to vincristine, and cell proliferation was markedly inhibited by MYC‐shRNA‐mediated knockdown. Furthermore, genes involved in cyclin D, mTOR, and Ras signaling were downregulated following MYC knockdown, suggesting that MYC expression was closely associated with tumor cell growth. In conclusion, AMU‐ML2 cells are uniquely characterized by homogenously staining regions at the 8q24 locus, thus providing useful insights into the pathogenesis of DLBCL with 8q24 abnormalities.

PATRI, a Genomics Data Integration Tool for Biomarker Discovery

The availability of genomic datasets in association with clinical, phenotypic, and drug sensitivity information represents an invaluable source for potential therapeutic applications, supporting the identification of new drug sensitivity biomarkers and pharmacological targets. Drug discovery and precision oncology can largely benefit from the integration of treatment molecular discriminants obtained from cell line models and clinical tumor samples; however this task demands comprehensive analysis approaches for the discovery of underlying data connections. Here we introduce PATRI (Platform for the Analysis of TRanslational Integrated data), a standalone tool accessible through a user-friendly graphical interface, conceived for the identification of treatment sensitivity biomarkers from user-provided genomics data, associated with information on sample characteristics. PATRI streamlines a translational analysis workflow: first, baseline genomics signatures are statistically identified, differentiating treatment sensitive from resistant preclinical models; then, these signatures are used for the prediction of treatment sensitivity in clinical samples, via random forest categorization of clinical genomics datasets and statistical evaluation of the relative phenotypic features. The same workflow can also be applied across distinct clinical datasets. The ease of use of the PATRI tool is illustrated with validation analysis examples, performed with sensitivity data for drug treatments with known molecular discriminants.

Analysis of high-throughput biological data using their rank values

High-throughput biological technologies are routinely used to generate gene expression profiling or cytogenetics data. To achieve high performance, methods available in the literature become more specialized and often require high computational resources. Here, we propose a new versatile method based on the data-ordering rank values. We use linear algebra, the Perron-Frobenius theorem and also extend a method presented earlier for searching differentially expressed genes for the detection of recurrent copy number aberration. A result derived from the proposed method is a one-sample Student's t-test based on rank values. The proposed method is to our knowledge the only that applies to gene expression profiling and to cytogenetics data sets. This new method is fast, deterministic, and requires a low computational load. Probabilities are associated with genes to allow a statistically significant subset selection in the data set. Stability scores are also introduced as quality parameters. The performance and comparative analyses were carried out using real data sets. The proposed method can be accessed through an R package available from the CRAN (Comprehensive R Archive Network) website: https://cran.r-project.org/web/packages/fcros .

Targeted NGS, array-CGH, and patient-derived tumor xenografts for precision medicine in advanced breast cancer: a single-center prospective study

Background

Routine feasibility and clinical impact of genomics-based tumor profiling in advanced breast cancer (aBC) remains to be determined. We conducted a pilot study to evaluate whether precision medicine could be prospectively implemented for aBC patients in a single center and to examine whether patient-derived tumor xenografts (PDX) could be obtained in this population.

Results

Thirty-four aBC patients were included. Actionable targets were found in 28 patients (82%). A targeted therapy could be proposed to 22 patients (64%), either through a clinical trial (n=15) and/or using already registered drugs (n=21). Ten patients (29%) eventually received targeted treatment, 2 of them deriving clinical benefit. Of 22 patients subjected to mouse implantation, 10 had successful xenografting (45%), mostly in triple-negative aBC.

Methods

aBC patients accessible to tumor biopsy were prospectively enrolled at the Institut Paoli-Calmettes in the BC-BIO study (ClinicalTrials.gov, NCT01521676). Genomic profiling was established by whole-genome array comparative genomic hybridization (aCGH) and targeted next-generation sequencing (NGS) of 365 candidate cancer genes. For a subset of patients, a sample of fresh tumor was orthotopically implanted in humanized cleared fat pads of NSG mice for establishing PDX.

Conclusions

Precision medicine can be implemented in a single center in the context of clinical practice and may allow genomic-driven treatment in approximately 30% of aBC patients. PDX may be obtained in a significant fraction of cases.

Competing endogenous RNA network analysis identifies critical genes among the different breast cancer subtypes

Although competing endogenous RNAs (ceRNAs) have been implicated in many solid tumors, their roles in breast cancer subtypes are not well understood. We therefore generated a ceRNA network for each subtype based on the significance of both, positive co-expression and the shared miRNAs, in the corresponding subtype miRNA dys-regulatory network, which was constructed based on negative regulations between differentially expressed miRNAs and targets. All four subtype ceRNA networks exhibited scale-free architecture and showed that the common ceRNAs were at the core of the networks. Furthermore, the common ceRNA hubs had greater connectivity than the subtype-specific hubs. Functional analysis of the common subtype ceRNA hubs highlighted factors involved in proliferation, MAPK signaling pathways and tube morphogenesis. Subtype-specific ceRNA hubs highlighted unique subtype-specific pathways, like the estrogen response and inflammatory pathways in the luminal subtypes or the factors involved in the coagulation process that participates in the basal-like subtype. Ultimately, we identified 29 critical subtype-specific ceRNA hubs that characterized the different breast cancer subtypes. Our study thus provides new insight into the common and specific subtype ceRNA interactions that define the different categories of breast cancer and enhances our understanding of the pathology underlying the different breast cancer subtypes, which can have prognostic and therapeutic implications in the future.

Evaluation of CDK12 Protein Expression as a Potential Novel Biomarker for DNA Damage Response-Targeted Therapies in Breast Cancer

Disruption of Cyclin-Dependent Kinase 12 (CDK12) is known to lead to defects in DNA repair and sensitivity to platinum salts and PARP1/2 inhibitors. However, CDK12 has also been proposed as an oncogene in breast cancer. We therefore aimed to assess the frequency and distribution of CDK12 protein expression by IHC in independent cohorts of breast cancer and correlate this with outcome and genomic status. We found that 21% of primary unselected breast cancers were CDK12 high, and 10.5% were absent, by IHC. CDK12 positivity correlated with HER2 positivity but was not an independent predictor of breast cancer-specific survival taking HER2 status into account; however, absent CDK12 protein expression significantly correlated with a triple-negative phenotype. Interestingly, CDK12 protein absence was associated with reduced expression of a number of DDR proteins including ATR, Ku70/Ku80, PARP1, DNA-PK, and γH2AX, suggesting a novel mechanism of CDK12-associated DDR dysregulation in breast cancer. Our data suggest that diagnostic IHC quantification of CDK12 in breast cancer is feasible, with CDK12 absence possibly signifying defective DDR function. This may have important therapeutic implications, particularly for triple-negative breast cancers. Mol Cancer Ther; 17(1); 306-15. ©2017 AACR.

Gene modules associated with breast cancer distant metastasis-free survival in the PAM50 molecular subtypes

To identify PAM50 subtype–specific associations between distant metastasis-free survival (DMFS) in breast cancer (BC) patients and gene modules describing potentially targetable oncogenic pathways, a comprehensive analysis evaluating the prognostic efficacy of published gene signatures in 2027 BC patients from 13 studies was conducted. We calculated 21 gene modules and computed hazard ratios (HRs) for DMFS for one-unit increases in module score, with and without adjustment for clinical characteristics. By comparing gene expression to survival outcomes, we derived four subtype-specific prognostic signatures for BC. Univariate and multivariate analyses showed that in the luminal A subgroup, E2F3, PTEN and GGI gene module scores were associated with clinical outcome. In the luminal B tumors, RAS was associated with DMFS and in the basal-like tumors, ER was associated with DMFS. Our defined gene modules predicted high-risk patients in multivariate analyses for the basal-like (HR: 2.19, p=2.5×10⁻⁴), luminal A (HR: 3.03, p=7.2×10⁻⁵), luminal B (HR: 3.00, p=2.4×10⁻¹⁰) and HER2+ (HR: 5.49, p=9.7×10⁻¹⁰) subgroups. We found that different modules are associated with DMFS in different BC subtypes. The results of this study could help to identify new therapeutic strategies for specific molecular subgroups of BC, and could enhance efforts to improve patient-specific therapy options.

The emerging roles of CDK12 in tumorigenesis

Cyclin-dependent kinases (CDKs) are key regulators of both cell cycle progression and transcription. Since dysregulation of CDKs is a frequently occurring event driving tumorigenesis, CDKs have been tested extensively as targets for cancer therapy. Cyclin-dependent kinase 12 (CDK12) is a transcription-associated kinase which participates in various cellular processes, including DNA damage response, development and cellular differentiation, as well as splicing and pre-mRNA processing. CDK12 mutations and amplification have been recently reported in different types of malignancies, including loss-of-function mutations in high-grade serous ovarian carcinomas, and that has led to assumption that CDK12 is a tumor suppressor. On the contrary, CDK12 overexpression in other tumors suggests the possibility that CDK12 has oncogenic properties, similarly to other transcription-associated kinases. In this review, we discuss current knowledge concerning the role of CDK12 in ovarian and breast tumorigenesis and the potential for chemical inhibitors of CDK12 in future cancer treatment.

DACH1 suppresses breast cancer as a negative regulator of CD44

Dachshund homolog 1 (DACH1), a key cell fate determination factor, contributes to tumorigenesis, invasion, metastasis of human breast neoplasm. However, the exact molecular mechanisms for the anti-tumor roles of DACH1 in breast carcinoma are still lack of extensive understanding. Herein, we utilized immunohistochemistry (IHC) staining and public microarray data analysis showing that DACH1 was higher in normal breast, low-grade and luminal-type cancer in comparison with breast carcinoma, high-grade and basal-like tumors respectively. Additionally, both correlation analysis of public databases of human breast carcinoma and IHC analysis of mice xenograft tumors demonstrated that DACH1 inversely related to cancer stem cells (CSCs) markers, epithelial-mesenchymal transition (EMT) inducers and basal-enriched molecules, while cluster of differentiation 44 (CD44) behaved in an opposite manner. Furthermore, mice transplanted tumor model indicated that breast cancer cells Met-1 with up-regulation of DACH1 were endowed with remarkably reduced potential of tumorigenesis. Importantly, meta-analysis of 19 Gene Expression Omnibus (GEO) databases of breast cancer implicated that patients with higher DACH1 expression had prolonged time to death, recurrence and metastasis, while CD44 was a promising biomarker predicting worse overall survival (OS) and metastasis-free survival (MFS). Collectively, our study indicated that CD44 might be a novel target of DACH1 in breast carcinoma.

Identifying subtype-specific associations between gene expression and DNA methylation profiles in breast cancer

BACKGROUND

Breast cancer is a complex disease in which different genomic patterns exists depending on different subtypes. Recent researches present that multiple subtypes of breast cancer occur at different rates, and play a crucial role in planning treatment. To better understand underlying biological mechanisms on breast cancer subtypes, investigating the specific gene regulatory system via different subtypes is desirable.

METHODS

Gene expression, as an intermediate phenotype, is estimated based on methylation profiles to identify the impact of epigenomic features on transcriptomic changes in breast cancer. We propose a kernel weighted l1-regularized regression model to incorporate tumor subtype information and further reveal gene regulations affected by different breast cancer subtypes. For the proper control of subtype-specific estimation, samples from different breast cancer subtype are learned at different rate based on target estimates. Kolmogorov Smirnov test is conducted to determine learning rate of each sample from different subtype.

RESULTS

It is observed that genes that might be sensitive to breast cancer subtype show prediction improvement when estimated using our proposed method. Comparing to a standard method, overall performance is also enhanced by incorporating tumor subtypes. In addition, we identified subtype-specific network structures based on the associations between gene expression and DNA methylation.

CONCLUSIONS

In this study, kernel weighted lasso model is proposed for identifying subtype-specific associations between gene expressions and DNA methylation profiles. Identification of subtype-specific gene expression associated with epigenomic changes might be helpful for better planning treatment and developing new therapies.

A 3q gene signature associated with triple negative breast cancer organ specific metastasis and response to neoadjuvant chemotherapy

Triple negative breast cancers (TNBC) are aggressive tumors, with high rates of metastatic spread and targeted therapies are critically needed. We aimed to assess the prognostic and predictive value of a 3q 19-gene signature identified previously from lung cancer in a collection of 4,801 breast tumor gene expression data. The 3q gene signature had a strong association with features of aggressiveness such as high grade, hormone receptor negativity, presence of a basal-like or TNBC phenotype and reduced distant metastasis free survival. The 3q gene signature was strongly associated with lung metastasis only in TNBC (P < 0.0001, Hazard ratio (HR) 1.44, 95% confidence interval (CI), 1.31-1.60), significantly associated with brain but not bone metastasis regardless of TNBC status. The association of one 3q driver gene FXR1 with distant metastasis in TNBC (P = 0.01) was further validated by immunohistochemistry. In addition, the 3q gene signature was associated with better response to neoadjuvant chemotherapy in TNBC (P < 0.0001) but not in non-TNBC patients. Our study suggests that the 3q gene signature is a novel prognostic marker for lung and/or brain metastasis and a predictive marker for the response to neoadjuvant chemotherapy in TNBC, implying a potential role for 3q genes in the mechanism of organ-specific metastasis.

The expression pattern of long non-coding RNA PVT1 in tumor tissues and in extracellular vesicles of colorectal cancer correlates with cancer progression

The plasmacytoma variant translocation 1 gene (PVT1) is a large non-coding locus at adjacent of c-Myc, and long non-coding RNA PVT1 is now recognized as a cancerous gene co-amplified with c-Myc in various cancers. But the expression and functional role of PVT1 in colorectal cancer are still unelucidated. In addition, all the reported long non-coding RNAs so far are discovered in either cells or tissues, but no research about long non-coding RNAs detection in extracellular vesicles has been reported yet. In the present study, we firstly investigated the expression of PVT1 in colorectal cancer specimens and its correlation with the expression of c-Myc and other related genes by real-time polymerase chain reaction. Then, we isolated the extracellular vesicles from colorectal cancer cells culturing medium by differential centrifugation and detected the PVT1 expression in extracellular vesicles by using real-time polymerase chain reaction. The PVT1 targeting siRNA was transfected into SW480 and SW620 cells, and 3-(4, 5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium assay and flow cytometry were used to evaluate the cell proliferation and apoptosis. The results showed that the PVT1 expression in tumor tissues was higher than that in normal tissues, which was significantly correlated with the expression of c-Myc and three c-Myc regulating genes FUBP1, EZH2, and NPM1 and also correlated with the expression of two other PVT1-associated transcript factors nuclear factor-κB and myocyte-specific enhancer factor 2A. Here, we reported for the first time that PVT1 as a long non-coding RNA was successfully detected in extracellular vesicles excluded from SW620 and SW480 cells, and the expression level of PVT1 was higher in extracellular vesicles from the more aggressive cell SW620 than from SW480. The results also showed that by down-regulating the PVT1 expression, the c-Myc expression was suppressed, the cell proliferation was inhibited, and cell apoptosis was increased. Taken together, these findings implicated that PVT1 may be a new oncogene co-amplified with c-Myc in colorectal cancer tissues and extracellular vesicles and functionally correlated with the proliferation and apoptosis of colorectal cancer cells.

Next-Generation Assessment of Human Epidermal Growth Factor Receptor 2 (ERBB2) Amplification Status: Clinical Validation in the Context of a Hybrid Capture-Based, Comprehensive Solid Tumor Genomic Profiling Assay

Establishing ERBB2 [human epidermal growth factor receptor 2 (HER2)] amplification status in breast and gastric carcinomas is essential to treatment selection. Immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) constitute the current standard for assessment. With further advancements in genomic medicine, new clinically relevant biomarkers are rapidly emerging and options for targeted therapy are increasing in patients with advanced disease, driving the need for comprehensive molecular profiling. Next-generation sequencing (NGS) is an attractive approach for up-front comprehensive assessment, including ERBB2 status, but the concordance with traditional methods of HER2 assessment is not well established. The Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT) assay, a hybrid capture-based NGS assay interrogating the coding regions of 410 cancer-related genes, was performed on manually macrodissected unstained sections from formalin-fixed, paraffin-embedded breast (n = 213) and gastroesophageal (n = 39) tumors submitted for clinical mutation profiling. ERBB2 status was assessed using a custom bioinformatics pipeline, and NGS results were compared to IHC and FISH. NGS ERBB2 amplification calls had an overall concordance of 98.4% (248/252) with the combined IHC/FISH results in this validation set. Discrepancies occurred in the context of low tumor content and HER2 heterogeneity. ERBB2 amplification status can be reliably determined by hybridization capture-based NGS methods, allowing efficient concurrent testing for other potentially actionable genomic alterations, particularly in limited material.

Double-edged role of G protein-coupled estrogen receptor 1 in breast cancer prognosis: an analysis of 167 breast cancer samples and online data sets

G protein-coupled estrogen receptor 1 (GPER1) is widely expressed in breast cancer; however, its prognostic significance in breast cancer patients remains controversial. In this study, expression levels of GPER1 were analyzed by using real-time polymerase chain reaction in 167 primary breast cancer samples, and overall survival (OS), recurrence-free survival (RFS), distant metastasis-free survival (DMFS), and disease-free survival (DFS) were analyzed by using Kaplan-Meier curves and multivariable Cox regression. In addition, a meta-analysis was conducted with all available online data sets found in the Web sites kmplot.com and www.prognoscan.org. The results showed that there was no significant correlation between GPER1 expression and OS, RFS, DMFS, and DFS in the total breast cancer patient population. In contrast, the meta-analysis of online data sets found that expression levels of GPER1 were slightly associated with better RFS in the total breast cancer population (P=0.021). Interestingly, higher expression of GPER1 was associated with poorer DFS in HER2-positive subtype of breast cancer (P=0.047) but with better DMFS (P=0.040) and DFS (P=0.035) in HER2-negative subtype of breast cancer. In addition, it was found that HER2 overexpression in MDA-MB-231 cell increased GPER1, which may help explain protumor effect of GPER1 in HER2-overexpressed patients. The overall results suggested that the expression of GPER1 has distinct prognostic values in HER2-positive and HER2-negative breast cancer patients.