New drugs for breast cancer subtypes: Targeting driver pathways to overcome resistance

Prediction of anti-cancer drug synergy based on cross-matching network and cancer molecular subtypes

At present, anti-cancer drug synergy therapy is one of the most important methods to overcome drug resistance and reduce drug toxicity in cancer treatment. High-throughput screening through deep learning can effectively improve the efficiency of discovering synergistic drugs. Nowadays, most of the existing deep learning algorithms for anti-cancer drug synergy prediction use deep neural networks and can only implicitly perform feature interaction. This study proposes a deep learning algorithm, named MolCross, which combines implicit feature interaction with explicit features to improve the accuracy of prediction of the anti-cancer drug synergy score. MolCross uses a deep autoencoder to extract features from high-dimensional input, uses the drug-specific subnetworks and cross-network to perform implicit feature interaction and explicit feature interaction respectively, and finally uses a synergy prediction network to combine the two feature interaction methods to obtain the final prediction results. We adopted a five-fold cross validation and compared MolCross with other four anti-cancer drug synergy prediction models. The results show that MolCross has better prediction performance than other models. MolCross also has good performance in terms of cross-cell line and cross-tissue type. Existing studies have demonstrated that cancer molecular subtypes have different sensitivities to targeted therapy. In this study, the features of cancer molecular subtype were introduced in the model using an embedding layer in MolCross to explore the effect of cancer molecular subtype on anti-cancer drug synergy. We also found that the cancer molecular subtype is one of the main factors affecting the synergy between drugs.

Genome-wide analyses reveal the regulatory roles of DNA methylation-regulated alternative promoter transcripts in breast cancer

A certain proportion of genes are regulated by multiple, distinct promoters, revealing a dynamic landscape of the cancer transcriptome. However, the contribution of alternative promoters (APs) in breast cancer (BRCA) remains largely unexplored. Here, we identified 3654 genes with multiple promoters in BRCA patients, and 53 of them could generate distinct AP transcripts that are dysregulated and prognosis-related in BRCA, namely prognosis-related dysregulated AP (prdeAP) transcripts. Interestingly, when we searched for the genomic signatures of these prdeAP genes, we found that the promoter regions of 92% of the prdeAP genes were enriched with abundant DNA methylation signals. Through further bioinformatic analysis and experimental validation, we showed that AP selections of TANK, UNKL, CCL28, and MAP1LC3A were regulated by DNA methylation upon their corresponding promoter regions. Functionally, by overexpressing AP variants of TANK, we found that TANK|55731 could dramatically suppress MDA-MB-231 cell proliferation and migration. Meanwhile, pan-cancer survival analyses suggested that AP variants of TANK provided more accurate prognostic predictive ability than TANK gene in a variety of tumor types, including BRCA. Together, by uncovering the DNA methylation-regulated AP transcripts with tumor prognostic features, our work revealed a novel layer of regulators in BRCA progression and provided potential targets that served as effective biomarkers for anti-BRCA treatment.

CRISPR/Cas9 system in breast cancer therapy: advancement, limitations and future scope

Cancer is one of the major causes of mortality worldwide, therefore it is considered a major health concern. Breast cancer is the most frequent type of cancer which affects women on a global scale. Various current treatment strategies have been implicated for breast cancer therapy that includes surgical removal, radiation therapy, hormonal therapy, chemotherapy, and targeted biological therapy. However, constant effort is being made to introduce novel therapies with minimal toxicity. Gene therapy is one of the promising tools, to rectify defective genes and cure various cancers. In recent years, a novel genome engineering technology, namely the clustered regularly interspaced short palindromic repeat (CRISPR)-associated protein-9 (Cas9) has emerged as a gene-editing tool and transformed genome-editing techniques in a wide range of biological domains including human cancer research and gene therapy. This could be attributed to its versatile characteristics such as high specificity, precision, time-saving and cost-effective methodologies with minimal risk. In the present review, we highlight the role of CRISPR/Cas9 as a targeted therapy to tackle drug resistance, improve immunotherapy for breast cancer.

Use of Extrapolation in New Drug Approvals by the US Food and Drug Administration

IMPORTANCE

The US Food and Drug Administration (FDA)-approved indications can be factors in prescribing practices and insurance coverage, yet the frequency with which the extrapolation of clinical characteristics from pivotal trial data to the final approved indication occurs is not well understood.

OBJECTIVES

To evaluate the frequency of extrapolation beyond pivotal trial data into approved indications in relation to disease severity, disease subtype, and concomitant medication use.

DESIGN, SETTING, AND PARTICIPANTS

In a cross-sectional study, the characteristics of patients in pivotal trials of 105 novel drug approvals from 2015 to 2017 were identified and compared with the FDA-approved indications for the drugs. Main sources analyzed included FDA reviews, published material describing the pivotal trials, and the original drug labeling. The study was conducted from July 4, 2019, to June 1, 2021.

EXPOSURES

Clinical characteristics of pivotal trials used in FDA approval.

MAIN OUTCOMES AND MEASURES

Main outcomes included the nature and frequency of extrapolation from study populations to the final indications. Extrapolation was defined as the granting of an indication for use in a broader population than was included in the pivotal trials on the basis of disease severity, disease subtype, or concomitant medication use.

RESULTS

Among the 105 novel FDA drug approvals studied, 23 extrapolations of trial population characteristics to the approved indication were identified in 21 drugs (20%): 12 times (29%) in 2015, 3 times (15%) in 2016, and 6 times (14%) in 2017. Extrapolation of trial findings to patients with greater disease severity was most common (n = 14 drugs), followed by differences in disease subtype (n = 6) and concomitant medication use (n = 3).

CONCLUSIONS AND RELEVANCE

The findings of this study suggest that extrapolation from pivotal trial data to FDA-approved indications is common. Although extrapolations may be grounded in reasonable clinical predictions, they can limit the generalizability of such indications to specific prescribing decisions; these findings suggest a greater need for close postapproval monitoring to determine whether new safety issues arise, or effectiveness differs from expectations when these medications are used in broader real-world populations.

An integrated computational approach to screening of alkaloids inhibitors of TBX3 in breast cancer cell lines

TBX3 is an ancient and evolutionarily conserved family member of T-box transcription factors that acts as a key regulator in embryonic development and organogenesis. It is often overexpressed in various epithelial and mesenchymal malignancies which has a significant impact on various hallmarks of cancer, which mainly includes senescence shunt, apoptosis, anoikis, angiogenesis, and promoting metastatic and expansion of cancer stem cells. In addition to the role of TBX3 in early breast development, a number of studies have also confirmed the amplification of TBX3 in the occurrence and development of breast cancer. To overcome a major challenge in breast cancer treatment, resistance to current anti-cancer drug, it is important to develop new drug pipeline. In this study of different alkaloid molecules, to identify potential alkaloid inhibitors of TBX3, a structure based virtual screening was done involving molecular docking, ADME, toxicity analysis, molecular dynamics simulation. From our study 5 ligands named Jervine, Diflomotecan, Camptothecin, Vincamine, and Anoniane were primarily confirmed as potential inhibitors. The followed screening manner funnels out five potential compounds that have a high scoring function that emphasizes their high binding ability along with no toxicity effects. The molecular mechanics-generalized born surface area (MM-GBSA) and molecular dynamics (MD) simulation showed that Jervine along with Diflomotecan formed the stable complexes with TBX3 which makes it obvious that these two alkaloids can be introduced into the drug development pipeline and used as a new leader to develop new effective drugs against breast cancer.Communicated by Ramaswamy H. Sarma.

Application of the CRISPR/Cas9 System to Drug Resistance in Breast Cancer

Clinical evidence indicates that drug resistance is a great obstacle in breast cancer therapy. It renders the disease uncontrollable and causes high mortality. Multiple mechanisms contribute to the development of drug resistance, but the underlying cause is usually a shift in the genetic composition of tumor cells. It is increasingly feasible to engineer the genome with the clustered regularly interspaced short palindromic repeats (CRISPR)/associated (Cas)9 technology recently developed, which might be advantageous in overcoming drug resistance. This article discusses how the CRISPR/Cas9 system might revert resistance gene mutations and identify potential resistance targets in drug-resistant breast cancer. In addition, the challenges that impede the clinical applicability of this technology and highlight the CRISPR/Cas9 systems are presented. The CRISPR/Cas9 system is poised to play an important role in preventing drug resistance in breast cancer therapy and will become an essential tool for personalized medicine.

RNAi screens identify CHD4 as an essential gene in breast cancer growth

Epigenetic regulation plays an essential role in tumor development and epigenetic modifiers are considered optimal potential druggable candidates. In order to identify new breast cancer vulnerabilities and improve therapeutic chances for patients, we performed in vivo and in vitro shRNA screens in a human breast cancer cell model (MCF10DCIS.com cell line) using epigenetic libraries. Among the genes identified in our screening, we deeply investigated the role of Chromodomain Helicase DNA binding Protein 4 (CHD4) in breast cancer tumorigenesis. CHD4 silencing significantly reduced tumor growth in vivo and proliferation in vitro of MCF10DCIS.com cells. Similarly, in vivo breast cancer growth was decreased in a spontaneous mouse model of breast carcinoma (MMTV-NeuT system) and in metastatic patient-derived xenograft models. Conversely, no reduction in proliferative ability of non-transformed mammary epithelial cells (MCF10A) was detected. Moreover, we showed that CHD4 depletion arrests proliferation by inducing a G0/G1 block of cell cycle associated with up-regulation of CDKN1A (p21). These results highlight the relevance of genetic screens in the identification of tumor frailties and the role of CHD4 as a potential pharmacological target to inhibit breast cancer growth.

CHD4-mediated loss of E-cadherin determines metastatic ability in triple-negative breast cancer cells

Triple-negative breast cancer (TNBC) is a subtype of cancer with aggressive behaviors (high recurrence and metastasis rate) and poor prognosis. Therefore, studying the determining factors that lead to malignant TNBCs is necessary to develop personalized therapy and improve survival rates. In this study, we first analyzed levels of chromodomain helicase DNA binding protein 4 (CHD4) in 60 TNBC patients by immunohistochemical staining. We then clarified the role of CHD4 in TNBC and non-TNBC cell lines. Our clinical data indicated that higher CHD4 expression is positively correlated with metastatic stage, tumor recurrence, and survival status. Consistent with the clinical analytical data, our in vitro data also indicated that high level of CHD4 is positively correlated with malignant behaviors in TNBC cells, such as cell motility and mortality. For further analyses, we found that E-cadherin, N-cadherin and fibronetin are involved in CHD4-mediated epithelial-mesenchymal transition (EMT). Silencing of CHD4 also increased drug sensitivity to cisplatin and PARP1 inhibitor, especially in TNBC cells. Altogether, our findings showed that CHD4 is not only a potential prognostic biomarker for TNBC patient survival, but is also a powerful candidate in the development of new anti-cancer agents in TNBC.

Biomarkers and Imaging of Breast Cancer

OBJECTIVE

The goals of this review are to provide background information on the definitions and applications of the general term "biomarker" and to highlight the specific roles of breast imaging biomarkers in research and clinical breast cancer care. A search was conducted of the main electronic biomedical databases (PubMed, Cochrane, Embase, MEDLINE [Ovid], Scopus, and Web of Science). The search was focused on review literature in general radiology and biomedical sciences and on reviews and primary research articles on biomarkers in breast imaging over the 15 years ending in June 2017. The keywords included "biomarker," "trial endpoints," "breast imaging," "breast cancer," "radiomics," and "precision medicine" in the titles and abstracts of the papers.

CONCLUSION

Clinical breast care and breast cancer-related research rely on imaging biomarkers for decision support. In the era of precision medicine and big data, the practice of radiology is likely to change. A closer integration of breast imaging with related biomedical fields and the creation of large integrated and shareable databases of clinical, molecular, and imaging biomarkers should allow the field to continue guiding breast cancer care and research.

A Cross-Sectional Comparison of Druggable Mutations in Primary Tumors, Metastatic Tissue, Circulating Tumor Cells, and Cell-Free Circulating DNA in Patients with Metastatic Breast Cancer: The MIRROR Study Protocol

BACKGROUND

Characterization of the driver mutations in an individual metastatic breast cancer (MBC) patient is critical to selecting effective targeted therapies. Currently, it is believed that the limited efficacy of many targeted drugs may be due to the expansion of drug resistant clones with different genotypes that were already present in the primary tumor. Identifying the genomic alterations of these clones, and introducing combined or sequential targeted drug regimens, could lead to a significant increase in the efficacy of currently available targeted therapies.

OBJECTIVE

The primary objective of this study is to assess the concordance/discordance of mutations between the primary tumor and metastatic tissue in MBC patients. Secondary objectives include comparing the genomic profiles of circulating tumor cells (CTCs) and circulating free DNA (cfDNA) from peripheral blood with those of the primary tumor and metastatic tissue for each patient, evaluating these mutations in the signaling pathways that are relevant to the disease, and testing the feasibility of introducing liquid biopsy as a translational laboratory tool in clinical practice.

METHODS

The multicenter, transversal, observational MIRROR study is currently ongoing in three participating hospitals. All consecutive patients with MBC confirmed by radiologic findings will be screened for eligibility, either at first relapse or if tumor regrowth occurs while on treatment for metastatic disease.

RESULTS

Patient recruitment is currently ongoing. To date, 41 patients have a complete set of tissue samples available (plasma, CTCs, and formalin-fixed, paraffin-embedded primary tumor and metastatic tumor). However, none of these samples have undergone nucleic acids extraction or targeted deep sequencing.

CONCLUSIONS

The results of this study may have a significant influence on the practical management of patients with MBC, and may provide clues to clinicians that lead towards a better stratification of patients, resulting in more selective and less toxic treatments. Additionally, if genomic mutations found in metastatic tissues are similar to those detected in CTCs and/or cfDNA, liquid biopsies could prove to be a more convenient, non-invasive, and easily accessible source of genomic material for the analysis of mutations and other genomic aberrations in MBC.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02626039; https://clinicaltrials.gov/ct2/show/NCT02626039 (Archived by WebCite at http://www.webcitation.org/6jlneVyoz).

Dillenia suffruticosa dichloromethane root extract induced apoptosis towards MDA-MB-231 triple-negative breast cancer cells

ETHNOPHARMACOLOGICAL RELEVANCE

Dillenia suffruticosa is traditionally used for treatment of cancerous growth including breast cancer in Malaysia.

AIM OF THE STUDY

Dillenia suffruticosa is a well-known medicinal plant in Malaysia for the treatment of cancer. Nevertheless, no study has been reported the cytotoxicity of this plant towards MDA-MB-231 triple-negative breast cancer cells. The present study was designed to investigate the mode of cell death and signalling pathways of MDA-MB-231 cells treated with dichloromethane Dillenia suffruticosa root extract (DCM-DS).

METHODS

Extraction of Dillenia suffruticosa root was performed by the use of sequential solvent procedure. The cytotoxicity of DCM-DS was determined by using MTT assay. The mode of cell death was evaluated by using an inverted light microscope and flow cytometry analysis using Annexin-V/PI. Cell cycle analysis and measurement of reactive oxygen species level were performed by using flow cytometry. The cells were treated with DCM-DS and antioxidants α-tocopherol or ascorbic acid to evaluate the involvement of ROS in the cytotoxicity of DCM-DS. Effect of DCM-DS on the expression of antioxidant, apoptotic, growth, survival genes and proteins were analysed by using GeXP-based multiplex system and Western blot, respectively. The cytotoxicity of compounds isolated from DCM-DS was evaluated towards MDA-MB-231 cells using MTT assay.

RESULTS

DCM-DS induced apoptosis, G2/M phase cell cycle arrest and oxidative stress in MDA-MB-231 cells. The induction of apoptosis in MDA-MB-231 cells by DCM-DS is possibly due to the activation of pro-apoptotic JNK1 and down-regulation of anti-apoptotic ERK1, which in turn down-regulates anti-apoptotic BCL-2 to increase the BAX/BCL-2 ratio to initiate the mitochondrial apoptotic pathway. The cell cycle arrest in DCM-DS-treated MDA-MB-231 cells is possibly via p53-independent but p21-dependent pathway. A total of 3 triterpene compounds were isolated from DCM-DS. Betulinic acid appears to be the most major and most cytotoxic compound in DCM-DS.

CONCLUSION

The data suggest the potential application of DCM-DS in the treatment of triple-negative breast cancer.

Genomic profiling of murine mammary tumors identifies potential personalized drug targets for p53-deficient mammary cancers

Targeted therapies against basal-like breast tumors, which are typically 'triple-negative breast cancers (TNBCs)', remain an important unmet clinical need. Somatic TP53 mutations are the most common genetic event in basal-like breast tumors and TNBC. To identify additional drivers and possible drug targets of this subtype, a comparative study between human and murine tumors was performed by utilizing a murine Trp53-null mammary transplant tumor model. We show that two subsets of murine Trp53-null mammary transplant tumors resemble aspects of the human basal-like subtype. DNA-microarray, whole-genome and exome-based sequencing approaches were used to interrogate the secondary genetic aberrations of these tumors, which were then compared to human basal-like tumors to identify conserved somatic genetic features. DNA copy-number variation produced the largest number of conserved candidate personalized drug targets. These candidates were filtered using a DNA-RNA Pearson correlation cut-off and a requirement that the gene was deemed essential in at least 5% of human breast cancer cell lines from an RNA-mediated interference screen database. Five potential personalized drug target genes, which were spontaneously amplified loci in both murine and human basal-like tumors, were identified: Cul4a, Lamp1, Met, Pnpla6 and Tubgcp3 As a proof of concept, inhibition of Met using crizotinib caused Met-amplified murine tumors to initially undergo complete regression. This study identifies Met as a promising drug target in a subset of murine Trp53-null tumors, thus identifying a potential shared driver with a subset of human basal-like breast cancers. Our results also highlight the importance of comparative genomic studies for discovering personalized drug targets and for providing a preclinical model for further investigations of key tumor signaling pathways.

Tumor microenvironment and cancer therapy resistance

Innate resistance to various therapeutic interventions is a hallmark of cancer. In recent years, however, acquired resistance has emerged as a daunting challenge to anticancer treatments including chemotherapy, radiation and targeted therapy, which abolishes the efficacy of otherwise successful regimens. Cancer cells gain resistance through a variety of mechanisms in both primary and metastatic sites, involving cell intrinsic and extrinsic factors, but the latter often remains overlooked. Mounting evidence suggests critical roles played by the tumor microenvironment (TME) in multiple aspects of cancer progression particularly therapeutic resistance. The TME decreases drug penetration, confers proliferative and antiapoptotic advantages to surviving cells, facilitates resistance without causing genetic mutations and epigenetic changes, collectively modifying disease modality and distorting clinical indices. Recent studies have set the baseline for future investigation on the intricate relationship between cancer resistance and the TME in pathological backgrounds. This review provides an updated outline of research advances in TME biology and highlights the prospect of targeting the TME as an essential strategy to overcome cancer resistance and improve therapeutic outcomes through precise intervention. In the long run, continued inputs into translational medicine remain highly desired to achieve durable responses in the current era of personalized clinical oncology.

Number of negative lymph nodes can predict survival after postmastectomy radiotherapy according to different breast cancer subtypes

Purpose: To assess the prognostic value of the number of negative lymph nodes (NLNs) in breast cancer patients with positive axillary lymph nodes after mastectomy and its predictive value for radiotherapy efficacy of different breast cancer subtypes (BCS).

Methods: The records of 1,260 breast cancer patients with positive axillary lymph nodes who received mastectomy between January 1998 and December 2007 were reviewed. The prognostic impact and predictive value of the number of NLNs with respect to locoregional recurrence-free survival (LRFS), disease-free survival (DFS), and overall survival (OS) were analyzed.

Results: The median follow-up time was 58 months, and 444 patients (35.2%) received postmastectomy radiotherapy (PMRT). Univariate and multivariate Cox survival analysis indicated the number of NLNs was an independent prognostic factor of LRFS, DFS, and OS. Patients with a higher number of NLNs had better survival. PMRT improved the LRFS of patients with ≤ 8 NLNs ( p < 0.001), while failing to improve the LRFS of patients with > 8 NLNs (p = 0.075). In patients with luminal A subtype, PMRT improved the LRFS, DFS, and OS of patients with ≤ 8 NLNs, but in patients with > 8 NLNs only the LRFS was improved. For patients with luminal B subtype, PMRT only improved the LRFS of patients with ≤ 8 NLNs. The number of NLNs had no predictive value for the efficacy with PMRT in Her2+ and triple-negative subtypes.

Conclusions: The number of NLNs is a prognostic indicator in patients with node-positive breast cancer, and it can predict the efficacy of PMRT according to different BCS.

From precision medicine to cancer care through the immunome: highlights from the European Society of Medical Oncology Congress, Madrid, 26-30th September 2014

The recognition that cancer is a 'spectrum' of diseases, and that medical oncologists should achieve 'convergence' from 'divergence' to treat cancer patients was the main theme of the 2014 European Society of Medical Oncology (ESMO) Congress. The meeting assembled 19,859 participants from nearly 134 countries worldwide. The educational content was centered on precision medicine in cancer care, from mutational burden to the immunome, through the epigenome and the proteome. Precision medicine has been defined as the tailoring of medical treatment to the characteristics of an individual patient. Knowing an individual's genomics has created a remarkable and unprecedented opportunity to improve medical treatment and develop preventative strategies to preserve health. Clinical oncologists across the range of diseases recognise that for precision medicine to take hold, it will require intensive, rigorous validation that these new approaches do indeed improve patient outcomes. Not all molecular alterations are predictive of response to a specific targeted treatment nor are they all druggable, raising issues of cost-benefit, validation of specific biomarkers, and of managing patient expectations. Addressing all these issues will be essential for the medical community to embrace any given opportunities. Along with it, it will also require educational programmes that squarely address the knowledge chasm that currently exists for practicing physicians. The promise of genomic and precision medicine has created greater demands for both those providing the scientific expertise-bioinformatics, statisticians, molecular biologists-and those delivering clinical care-physicians, nurses, psychologists-to the patients. This ESMO 2014 report will highlight the major findings of this outstanding meeting.

Induction of cell cycle arrest and apoptosis in caspase-3 deficient MCF-7 cells by Dillenia suffruticosa root extract via multiple signalling pathways

BACKGROUND

Dillenia suffruticosa root dichloromethane extract (DCM-DS) has been reported to exhibit strong cytotoxicity towards breast cancer cells. The present study was designed to investigate the cell cycle profile, mode of cell death and signalling pathways of DCM-DS-treated human caspase-3 deficient MCF-7 breast cancer cells.

METHODS

Dillenia suffruticosa root was extracted by sequential solvent extraction. The anti-proliferative activity of DCM-DS was determined by using MTT assay. The mode of cell death was evaluated by using inverted light microscope and Annexin-V/PI-flow cytometry analysis. Cell cycle analysis and measurement of intracellular reactive oxygen species (ROS) were performed by using flow cytometry. MCF-7 cells were co-treated with antioxidants α-tocopherol and ascorbic acid to evaluate whether the cell death was mainly due to oxidative stress. GeXP-based multiplex system was employed to investigate the expression of apoptotic, growth and survival genes in MCF-7 cells. Western blot analysis was performed to confirm the expression of the genes.

RESULTS

DCM-DS was cytotoxic to the MCF-7 cells in a time-and dose-dependent manner. The IC50 values of DCM-DS at 24, 48 and 72 hours were 20.3 ± 2.8, 17.8 ± 1.5 and 15.5 ± 0.5 μg/mL, respectively. Cell cycle analysis revealed that DCM-DS induced G0/G1 and G2/M phase cell cycle arrest in MCF-7 cells at low concentration (12.5 and 25 μg/mL) and high concentration (50 μg/mL), respectively. Although Annexin-V/PI-flow cytometry analysis has confirmed that DCM-DS induced apoptosis in MCF-7 cells, the distinct characteristics of apoptosis such as membrane blebbing, chromatin condensation, nuclear fragmentation and formation of apoptotic bodies were not observed under microscope. DCM-DS induced formation of ROS in MCF-7 cells. Nevertheless, co-treatment with antioxidants did not attenuate the cell death at low concentration of DCM-DS. The pro-apoptotic gene JNK was up-regulated whereby anti-apoptotic genes AKT1 and ERK1/2 were down-regulated in a dose-dependent manner. Western blot analysis has confirmed that DCM-DS significantly up-regulated the expression of pro-apoptotic JNK1, pJNK and down-regulated anti-apoptotic AKT1, ERK1 in MCF-7 cells.

CONCLUSION

DCM-DS induced cell cycle arrest and apoptosis in MCF-7 cells via multiple signalling pathways. It shows the potential of DCM-DS to be developed to target the cancer cells with mutant caspase-3.

Primary and secondary distant metastatic breast cancer: two sides of the same coin

OBJECTIVES

This study evaluated the differences between breast cancer (BC) patients who present with primary distant metastatic disease (PMD) and those who develop distant metastases during the course of their illness (secondary metastatic disease [SMD]) with regard to clinicopathological characteristics, patterns of metastatic sites, palliative therapy and survival.

PATIENTS & METHODS

Based on a cohort of patients with newly diagnosed BC (n = 1459), we analyzed all patients who had PMD (n = 92, 6.3%) and those who developed SMD (n = 277, 20.3%).

RESULTS

There were no significant differences with regard to the patient's age in which metastatic disease had been diagnosed (PMD/SMD: 64 years/66 years, p = 0.19). The SMD group had more often triple-negative carcinomas (25.5%/7.3%, p = 0.019); there were no significant differences with regard to grading (p = 0.61), HER2 status (p = 0.67) and hormonal receptor status (p = 1.00). The mean number of metastatic locations was similar (2.3/2.3, p = 0.91). While patients with PMD usually initiated systemic therapy, patients with SMD received systemic therapy after diagnosis of metastatic disease less often (16.4%/2.6%, p < 0.001). Both groups received palliative chemotherapy similarly often (PMD/SMD: 62.8%/63.3%, p = 1.00). The mean number of palliative therapy lines was similar (PMD/SMD: 2.8/3.2, p = 0.39). Compared to patients with SMD, patients who had PMD had a significantly improved metastatic disease survival (p < 0.001). The one-year, two-year and five-year survival rates were as follows: 76.9%/60.3%, 58.2%/43.0%, 23.1%/10.6%. The median survival times were 18.5 months and 32 months.

CONCLUSION

The poorer prognosis of patients with SMD may be explained by differences in clinicopathological features of the tumor, metastatic patterns, the use palliative therapy and drug resistance of the tumor cells which occurs in therapy-naïve PMD patients at a later phase of the disease course.

Dissecting cancer heterogeneity--an unsupervised classification approach

Gene-expression-based classification studies have changed the way cancer is traditionally perceived. It is becoming increasingly clear that many cancer types are in fact not single diseases but rather consist of multiple molecular distinct subtypes. In this review, we discuss unsupervised classification studies of common malignancies during the recent years. We found that the bioinformatic workflow of many of these studies follows a common main stream, although different statistical tools may be preferred from case to case. Here we summarize the employed methods, with a special focus on consensus clustering and classification. For each critical step of the bioinformatic analysis, we explain the biological relevance and implications of the technical principles. We think that a better understanding of these ever more frequently used methods to study cancer heterogeneity by the biomedical community is relevant as these type of studies will have an important impact on patient stratification and cancer subtype-specific drug development in the future.

Characterization of aberrant pathways across human cancers

BACKGROUND

Cancer is a broad group of genetic diseases which account for millions of deaths worldwide each year. Cancers are classified by various clinical, pathological and molecular methods, but even within a well-characterized disease, there is a significant inter-patient variability in survival, response to treatment, and other parameters. Especially in molecular level, tumours of the same category can appear significantly dissimilar due to complex combinations of genetic aberrations leading to a similar malignancy. We extended the current classification methods by studying tumour heterogeneity at pathway level.

METHODS

We computed the rate of alterations in 1994 pathways and 2210 tumours consisting of eight different cancers. Using gene set enrichment analysis, each sample was computed a pathway aberration profile that reflected its molecular state. The profiles were analysed together to infer the characteristic aberration rates for each pathway within each cancer. Subgroups of tumours defined by similar pathway aberrations were identified using clustering analyses. The pathway aberration and gene expression profiles of the subgroups were consecutively compared across all eight cancer types to search for similar tumours crossing the standard classification.

RESULTS

We identified pathways and processes that were common to all cancers as well as traits that are unique to a cancer type or closely related cancers. Studying the gene expression patterns within the pathway context suggested potential alteration mechanisms. Clustering analysis revealed five clinically relevant subgroups of tumours in four cancers that exhibited significant differences in survival compared to others. The cross-cancer analysis of the subgroups resulted in the identification of tumours that shared potentially significant alterations.

CONCLUSIONS

This study represents the first effort to extend the molecular characterizations towards pathway level descriptions across the family of cancers. In addition to providing a proof-of-concept for single sample pathway aberration analysis in this context, we present a comprehensive pathway aberration dataset that can be used to study pathway aberration patterns within or across cancers. Significant similarities between subgroups of different cancers on pathway and gene expression levels provide interesting hypotheses for understanding variable drug response, or transferring treatments across diseases by identifying common druggable pathways or genes, for example.

The role of tumour-stromal interactions in modifying drug response: challenges and opportunities

The role of stromal cells and the tumour microenvironment in general in modulating tumour sensitivity is increasingly becoming a key consideration for the development of active anticancer therapeutics. Here, we discuss how these tumour-stromal interactions affect tumour cell signalling, survival, proliferation and drug sensitivity. Particular emphasis is placed on the ability of stromal cells to confer - to tumour cells - resistance or sensitization to different classes of therapeutics, depending on the specific microenvironmental context. The mechanistic understanding of these microenvironmental interactions can influence the evaluation and selection of candidate agents for various cancers, in both the primary site as well as the metastatic setting. Progress in in vitro screening platforms as well as orthotopic and 'orthometastatic' xenograft mouse models has enabled comprehensive characterization of the impact of the tumour microenvironment on therapeutic efficacy. These recent advances can hopefully bridge the gap between preclinical studies and clinical trials of anticancer agents.