Targeted mutation detection in breast cancer using MammaSeq™

Integration of exome-seq and mRNA-seq using DawnRank, identified genes involved in innate immunity as drivers of breast cancer in the Indian cohort

Genetic heterogeneity influences the prognosis and therapy of breast cancer. The cause of disease progression varies and can be addressed individually. To identify the mutations and their impact on disease progression at an individual level, we sequenced exome and transcriptome from matched normal-tumor samples. We utilised DawnRank to prioritise driver genes and identify specific mutations in Indian patients. Mutations in the C3 and HLA genes were identified as drivers of disease progression, indicating the involvement of the innate immune system. We performed immune profiling on 16 matched normal/tumor samples using CIBERSORTx. We identified CD8+ve T cells, M2 macrophages, and neutrophils to be enriched in luminal A and T cells CD4+naïve, natural killer (NK) cells activated, T follicular helper (Tfh) cells, dendritic cells activated, and neutrophils in triple-negative breast cancer (TNBC) subtypes. Weighted gene co-expression network analysis (WGCNA) revealed activation of T cell-mediated response in ER positive samples and Interleukin and Interferons in ER negative samples. WGCNA analysis also identified unique pathways for each individual, suggesting that rare mutations/expression signatures can be used to design personalised treatment.

WCRC-25: A novel luminal Invasive Lobular Carcinoma cell line model

Breast cancer is categorized by the molecular and histologic presentation of the tumor, with the major histologic subtypes being No Special Type (NST) and Invasive Lobular Carcinoma (ILC). ILC are characterized by growth in a single file discohesive manner with stromal infiltration attributed to their hallmark pathognomonic loss of E-cadherin ( CDH1 ). Few ILC cell line models are available to researchers. Here we report the successful establishment and characterization of a novel ILC cell line, WCRC-25, from a metastatic pleural effusion from a postmenopausal Caucasian woman with metastatic ILC. WCRC-25 is an ER-negative luminal epithelial ILC cell line with both luminal and Her2-like features. It exhibits anchorage independent growth and haptotactic migration towards Collagen I. Sequencing revealed a CDH1 Q706* truncating mutation, together with mutations in FOXA1, CTCF, BRCA2 and TP53 , which were also seen in a series of metastatic lesions from the patient. Copy number analyses revealed amplification and deletion of genes frequently altered in ILC while optical genome mapping revealed novel structural rearrangements. RNA-seq analysis comparing the primary tumor, metastases and the cell line revealed signatures for cell cycle progression and receptor tyrosine kinase signaling. To assess targetability, we treated WCRC-25 with AZD5363 and Alpelisib confirming WCRC-25 as susceptible to PI3K/AKT signaling inhibition as predicted by our RNA sequencing analysis. In conclusion, we report WCRC-25 as a novel ILC cell line with promise as a valuable research tool to advance our understanding of ILC and its therapeutic vulnerabilities.

Financial support

The work was in part supported by a Susan G Komen Leadership Grant to SO (SAC160073) and NCI R01 CA252378 (SO/AVL). AVL and SO are Komen Scholars, Hillman Foundation Fellows and supported by BCRF. This project used the UPMC Hillman Cancer Center and Tissue and Research Pathology/Pitt Biospecimen Core shared resource which is supported in part by award P30CA047904. This research was also supported in part by the University of Pittsburgh Center for Research Computing, RRID:SCR_022735, through the resources provided. Specifically, this work used the HTC cluster, which is supported by NIH award number S10OD028483. Finally, partial support was provided by the Magee-Womens Research Institute and Foundation, The Shear Family Foundation, and The Metastatic Breast Cancer Network.

Association of Pathway Mutations With Survival in Taiwanese Breast Cancers

Breast cancer is the most common invasive cancer in women worldwide. Next-generation sequencing (NGS) provides a high-resolution profile of cancer genome. Our study ultimately gives the insight for genetic screening to identify the minority of patients with breast cancer with a poor prognosis, who might benefit from the most intensive possible treatment. The detection of mutations can polish the traditional method to detect high-risk patients who experience poor prognosis, recurrence and death early. In total, 147 breast cancer tumors were sequenced with targeted sequencing using a RainDance Cancer Hotspot Panel. The average age of all 147 breast cancer patients in the study was 51.7 years, with a range of 21-77 years. The average sequencing depth was 5,222x (range 2,900x-8,633x), and the coverage was approximately 100%. A total of 235 variants in 43 genes were detected in 147 patients by high-depth Illumina sequencing. A total of 219 single nucleotide variations were found in 42 genes from 147 patients, and 16 indel mutations were found in 13 genes from 84 patients. After filtering with the 1000 Genomes database and for synonymous SNPs, we focused on 54 somatic functional point mutations. The functional point mutations contained 54 missense mutations in 22 genes. Additionally, mutation of genes within the RET, PTEN, CDH1, MAP2K4, NF1, ERBB2, RUNX1, PIK3CA, FGFR3, KIT, KDR, APC, SMO, NOTCH1, and FBXW7 in breast cancer patients were with poor prognosis. Moreover, TP53 and APC mutations were enriched in triple-negative breast cancer. APC mutations were associated with a poor prognosis in human breast cancer (log-rank P<0.001). Our study identified tumor mutation hotspot profiles in Taiwanese breast cancer patients, revealing new targetable gene mutations in Asian breast cancer patients.

Comprehensive comparison of theranostic nanoparticles in breast cancer

Breast cancer is the most frequently happening cancer and the most typical cancer death among females. Despite the crucial progress in breast cancer therapy by using Chemotherapeutic agents, most anti-tumor drugs are insufficient to destroy exactly the breast cancer cells. The noble method of drug delivery using nanoparticles presents a great promise in treating breast cancer most sufficiently and with the least harm to the patient. Nanoparticles, with their spectacular characteristics, help overcome problems of this kind. Unique features of nanoparticles such as biocompatibility, bioavailability, biodegradability, sustained release, and, most importantly, site-specific targeting enables the Chemotherapeutic agents loaded in nanocarriers to differentiate between healthy tissue and cancer cells, leading to low toxicity and fewer side effects. This review focuses on evaluating and comprehending nanoparticles utilized in breast cancer treatment, including the most recent data related to the drugs they can carry. Also, this review covers all information related to each nanocarrier, such as their significant characteristics, subtypes, advantages, disadvantages, and chemical modification methods with recently published studies. This article discusses over 21 nanoparticles used in breast cancer treatment with possible chemical ligands such as monoclonal antibodies and chemotherapeutic agents binding to these carriers. These different nanoparticles and the unique features of each nanocarrier give the researchers all the data and insight to develop and use the brand-new drug delivery system.

Detection of genetic mutations in patients with breast cancer from Saudi Arabia using Ion AmpliSeq™ Cancer Hotspot Panel v.2.0

Next-Generation Sequencing allows for quick and precise sequencing of multiple genes concurrently. Recently, this technology has been employed for the identification of novel gene mutations responsible for disease manifestation among breast cancer (BC) patients, the most common type of cancer amongst Arabian women, and the major cause of disease-associated death in women worldwide. Genomic DNA was extracted from the peripheral blood of 32 Saudi Arabian BC patients with histologically confirmed invasive BC stages I-III and IV, as well from 32 healthy Saudi Arabian women using a QIAamp^® DNA Mini Kit. The isolated DNA was quantified using a Qubit™ dsDNA BR Assay Kit with a Qubit 2.0 Fluorometer. Ion semiconductor sequencing technology with an Ion S5 System and AmpliSeq™ Cancer Hotspot Panel v2 were utilized to analyze ~2,800 mutations described in the Catalogue of Somatic Mutations in Cancer from 50 oncogenes and tumor suppressor genes. Ion Reporter Software v.5.6 was used to evaluate the genomic alterations in all the samples after alignment to the hg19 human reference genome. The results showed that out of the 50 genes, 26 mutations, including 17 (65%) missense point mutations (single nucleotide variants), and 9 (35%) frameshift (insertion/deletion) mutations, were identified in 11 genes across the cohort in 61 samples (95%). Mutations were predominantly focused on two genes, PIK3CA and TP53, in the BC genomes of the sample set. PIK3CA mutation, c.1173A>G located in exon 9, was identified in 15 patients (46.9%). The TP53 mutations detected were a missense mutation (c.215C>G) in 26 patients (86.70%) and 1 frameshift mutation (c.215_216insG) in 1 patient (3.33%), located within exon 3 and 5, respectively. This study revealed specific mutation profiles for every BC patient, Thus, the results showed that Ion Torrent DNA Sequencing technology may be a possible diagnostic and prognostic method for developing personalized therapy based on the patient's individual BC genome.

A human breast cancer-derived xenograft and organoid platform for drug discovery and precision oncology

Models that recapitulate the complexity of human tumors are urgently needed to develop more effective cancer therapies. We report a bank of human patient-derived xenografts (PDXs) and matched organoid cultures from tumors that represent the greatest unmet need: endocrine-resistant, treatment-refractory and metastatic breast cancers. We leverage matched PDXs and PDX-derived organoids (PDxO) for drug screening that is feasible and cost-effective with in vivo validation. Moreover, we demonstrate the feasibility of using these models for precision oncology in real time with clinical care in a case of triple-negative breast cancer (TNBC) with early metastatic recurrence. Our results uncovered a Food and Drug Administration (FDA)-approved drug with high efficacy against the models. Treatment with this therapy resulted in a complete response for the individual and a progression-free survival (PFS) period more than three times longer than their previous therapies. This work provides valuable methods and resources for functional precision medicine and drug development for human breast cancer.

The Utility of Next-Generation Sequencing in Advanced Breast and Gynecologic Cancers

OBJECTIVES

Next-generation sequencing (NGS) has the potential to identify genetic alterations that are actionable with targeted therapy. Our objective was to identify the impact of NGS testing on advanced breast and gynecologic malignancies.

METHODS

A retrospective review of 108 patients who underwent NGS testing between 2015 and 2019 was performed. The NGS clinical action rate was calculated based on documentation of positive clinical action taken in cases with an actionable NGS result.

RESULTS

The 108 specimens tested included 35 breast cancers and 73 gynecologic malignancies, with most of the testing performed at Foundation Medicine (90%). Actionable mutation(s) were identified in 79 (73%) of 108 cases. The overall clinical action rate of NGS testing was 38% (30 of 79 cases). Overall, 47 (44%) of 108 patients died, all succumbing to disease. The average survival was 10.9 months. The survival difference between patients with actionable NGS result and targeted treatment, actionable NGS result but no targeted treatment, and patients with nonactionable NGS result was not significant (log-rank test, P = .5160).

CONCLUSIONS

NGS testing for advanced breast and gynecologic cancers at our institution has a 38% clinical action rate. However, the increased clinical action rate over the years did not translate into improved survival.

Multi-Gene Testing Overview with a Clinical Perspective in Metastatic Triple-Negative Breast Cancer

Next-generation sequencing (NGS) is the technology of choice for the routine screening of tumor samples in clinical practice. In this setting, the targeted sequencing of a restricted number of clinically relevant genes represents the most practical option when looking for genetic variants associated with cancer, as well as for the choice of targeted treatments. In this review, we analyze available NGS platforms and clinical applications of multi-gene testing in breast cancer, with a focus on metastatic triple-negative breast cancer (mTNBC). We make an overview of the clinical utility of multi-gene testing in mTNBC, and then, as immunotherapy is emerging as a possible targeted therapy for mTNBC, we also briefly report on the results of the latest clinical trials involving immune checkpoint inhibitors (ICIs) and TNBC, where NGS could play a role for the potential predictive utility of homologous recombination repair deficiency (HRD) and tumor mutational burden (TMB).

Identifying Genomic Alterations in Patients With Stage IV Breast Cancer Using MammaSeq: An International Collaborative Study

BACKGROUND

Identification of genomic alterations present in cancer patients may aid in cancer diagnosis, prognosis and therapeutic target discovery. In this study, we aimed to identify clinically actionable variants present in stage IV breast cancer (BC) samples.

MATERIALS AND METHODS

DNA was extracted from formalin-fixed paraffin-embedded samples of BC (n = 41). DNA was sequenced using MammaSeq, a BC-specific next-generation sequencing panel targeting 79 genes and 1369 mutations. Ion Torrent Suite 4.0 was used to make variant calls on the raw data, and the resulting single nucleotide variants were annotated using the CRAVAT toolkit. Single nucleotide variations (SNVs) were filtered to remove common polymorphisms and germline variants. CNVkit was employed to identify copy number variations (CNVs). The Precision Medicine Knowledgebase (PMKB) and OncoKB Precision Oncology Database were used to associate clinical significance with the identified variants.

RESULTS

A total of 41 samples from Turkish patients with BC were sequenced (read depth of 94-13,340; median of 1529). These patients were diagnosed with various BC subtypes including invasive ductal carcinoma, invasive lobular carcinoma, apocrine BC, and micropapillary BC. In total, 59 different alterations (49 SNVs and 10 CNVs) were identified. From these, 8 alterations (3 CNVs - ERBB2, FGFR1, and AR copy number gains and 5 SNVs - IDH1.R132H, TP53.E204∗, PI3KCA.E545K, PI3KCA.H1047R, and PI3KCA.R88Q) were identified to have some clinical significance by PMKB and OncoKB. Moreover, the top 5 genes with the most SNVs included PIK3CA, TP53, MAP3K1, ATM, and NCOR1. Additionally, copy number gains and losses were found in ERBB2, GRB7, IGFR1, AR, FGFR1, MYC, and IKBKB, and BRCA2, RUNX1, and RB1, respectively.

CONCLUSION

We identified 59 unique alterations in 38 genes in 41 stage IV BC tissue samples using MammaSeqTM. Eight of these alterations were found to have some clinical significance by OncoKB and PKMB. This study highlights the potential use of cancer specific next-generation sequencing panels in clinic to get better insight into the patient-specific genomic alterations.

EARN: an ensemble machine learning algorithm to predict driver genes in metastatic breast cancer

BACKGROUND

Today, there are a lot of markers on the prognosis and diagnosis of complex diseases such as primary breast cancer. However, our understanding of the drivers that influence cancer aggression is limited.

METHODS

In this work, we study somatic mutation data consists of 450 metastatic breast tumor samples from cBio Cancer Genomics Portal. We use four software tools to extract features from this data. Then, an ensemble classifier (EC) learning algorithm called EARN (Ensemble of Artificial Neural Network, Random Forest, and non-linear Support Vector Machine) is proposed to evaluate plausible driver genes for metastatic breast cancer (MBCA). The decision-making strategy for the proposed ensemble machine is based on the aggregation of the predicted scores obtained from individual learning classifiers to be prioritized homo sapiens genes annotated as protein-coding from NCBI.

RESULTS

This study is an attempt to focus on the findings in several aspects of MBCA prognosis and diagnosis. First, drivers and passengers predicted by SVM, ANN, RF, and EARN are introduced. Second, biological inferences of predictions are discussed based on gene set enrichment analysis. Third, statistical validation and comparison of all learning methods are performed by some evaluation metrics. Finally, the pathway enrichment analysis (PEA) using ReactomeFIVIz tool (FDR < 0.03) for the top 100 genes predicted by EARN leads us to propose a new gene set panel for MBCA. It includes HDAC3, ABAT, GRIN1, PLCB1, and KPNA2 as well as NCOR1, TBL1XR1, SIRT4, KRAS, CACNA1E, PRKCG, GPS2, SIN3A, ACTB, KDM6B, and PRMT1. Furthermore, we compare results for MBCA to other outputs regarding 983 primary tumor samples of breast invasive carcinoma (BRCA) obtained from the Cancer Genome Atlas (TCGA). The comparison between outputs shows that ROC-AUC reaches 99.24% using EARN for MBCA and 99.79% for BRCA. This statistical result is better than three individual classifiers in each case.

CONCLUSIONS

This research using an integrative approach assists precision oncologists to design compact targeted panels that eliminate the need for whole-genome/exome sequencing. The schematic representation of the proposed model is presented as the Graphic abstract.

Targeted sequencing reveals the somatic mutation landscape in a Swedish breast cancer cohort

Breast cancer (BC) is a genetically heterogeneous disease with high prevalence in Northern Europe. However, there has been no detailed investigation into the Scandinavian somatic landscape. Here, in a homogeneous Swedish cohort, we describe the somatic events underlying BC, leveraging a targeted next-generation sequencing approach. We designed a 20.5 Mb array targeting coding and regulatory regions of genes with a known role in BC (n = 765). The selected genes were either from human BC studies (n = 294) or from within canine mammary tumor associated regions (n = 471). A set of predominantly estrogen receptor positive tumors (ER +  85%) and their normal tissue counterparts (n= 61) were sequenced to ~ 140 × and 85 × mean target coverage, respectively. MuTect2 and VarScan2 were employed to detect single nucleotide variants (SNVs) and copy number aberrations (CNAs), while MutSigCV (SNVs) and GISTIC (CNAs) algorithms estimated the significance of recurrent somatic events. The significantly mutated genes (q ≤ 0.01) were PIK3CA (28% of patients), TP53 (21%) and CDH1 (11%). However, histone modifying genes contained the largest number of variants (KMT2C and ARID1A, together 28%). Mutations in KMT2C were mutually exclusive with PI3KCA mutations (p ≤ 0. 001) and half of these affect the formation of a functional PHD domain. The tumor suppressor CDK10 was deleted in 80% of the cohort while the oncogene MDM4 was amplified. Mutational signature analyses pointed towards APOBEC deaminase activity (COSMIC signature 2) and DNA mismatch repair (COSMIC signature 6). We noticed two significantly distinct patterns related to patient age; TP53 being more mutated in the younger group (29% vs 9% of patients) and CDH23 mutations were absent from the older group. The increased somatic mutation prevalence in the histone modifying genes KMT2C and ARID1A distinguishes the Swedish cohort from previous studies. KMT2C regulates enhancer activation and assists tumor proliferation in a hormone-rich environment, possibly pointing to a role in ER + BC, especially in older cases. Finally, age of onset appears to affect the mutational landscape suggesting that a larger age-diverse population incorporating more molecular subtypes should be studied to elucidate the underlying mechanisms.

Targeted next generation sequencing identifies somatic mutations in a cohort of Egyptian breast cancer patients

Breast cancer (BC) incidence is progressively increasing in Egypt. However, there is insufficient knowledge of the acquired somatic mutations in Egyptian BC patients which limit our understanding of its progression. To the best of our knowledge, this is the first Egyptian cohort to sequence a multiple-gene panel of cancer related genes on BC patients. Four hundred and nine cancer related genes were sequenced in 46 fresh breast tumors of Egyptian BC patients to identify somatic mutations and their frequencies. TP53 and PIK3CA were the most top two frequently mutated genes. We detected 15 different somatic mutations in TP53 and 8 different ones in PIK3CA, each in 27 samples (58.7%). According to Clinvar database; we found 19 pathogenic somatic mutations: 7 in Tp53, 5 in PIK3CA, and single variants of VHL, STK11, AKT1, KRAS, IDH2, PTEN and ERBB2. We also identified 5 variants with uncertain significance (4 in TP53 and 1 in CEBPA) and 4 variants with conflicting interpretations of pathogenicity (2 in TP53 and 1 in each of APC and JAK3). Moreover, one drug response variant (p.P72R) in TP53 was detected in 8 samples. Furthermore, four novel variants were identified in JAK2, MTOR, KIT and EPHB. Further analysis, by Ingenuity Variant Analysis software (IVA), showed that PI3K/AKT signaling is altered in greater than 50% of Egyptian BC patients which implicates PI3K/AKT signaling as a therapeutic target. In this cohort, we shed the light on the most frequently detected somatic mutations and the most altered pathway in Egyptian BC patients.

Plasma DNA as a "liquid biopsy" incompletely complements tumor biopsy for identification of mutations in a case series of four patients with oligometastatic breast cancer

PURPOSE

Circulating tumor DNA in plasma may present a minimally invasive opportunity to identify tumor-derived mutations to inform selection of targeted therapies for individual patients, particularly in cases of oligometastatic disease where biopsy of multiple tumors is impractical. To assess the utility of plasma DNA as a "liquid biopsy" for precision oncology, we tested whether sequencing of plasma DNA is a reliable surrogate for sequencing of tumor DNA to identify targetable genetic alterations.

METHODS

Blood and biopsies of 1-3 tumors were obtained from 4 evaluable patients with advanced breast cancer. One patient provided samples from an additional 7 tumors post-mortem. DNA extracted from plasma, tumor tissues, and buffy coat of blood were used for probe-directed capture of all exons in 149 cancer-related genes and massively parallel sequencing. Somatic mutations in DNA from plasma and tumors were identified by comparison to buffy coat DNA.

RESULTS

Sequencing of plasma DNA identified 27.94 ± 11.81% (mean ± SD) of mutations detected in a tumor(s) from the same patient; such mutations tended to be present at high allelic frequency. The majority of mutations found in plasma DNA were not found in tumor samples. Mutations were also found in plasma that matched clinically undetectable tumors found post-mortem.

CONCLUSIONS

The incomplete overlap of genetic alteration profiles of plasma and tumors warrants caution in the sole reliance of plasma DNA to identify therapeutically targetable alterations in patients and indicates that analysis of plasma DNA complements, but does not replace, tumor DNA profiling.

TRIAL REGISTRATION

Subjects were prospectively enrolled in trial NCT01836640 (registered April 22, 2013).

Cell free DNA biology and its involvement in breast carcinogenesis

Liquid biopsy represents a procedure for minimally invasive analysis of non-solid tissue, blood and other body fluids. It comprises a set of analytes that includes circulating tumor cells (CTCs) and circulating free DNA (cfDNA), RNA, long noncoding RNA (lncRNA) and micro RNA (miRNA), as well as extracellular vesicles. These novel analytes represent an alternative tool to complement diagnosis and monitor and predict response to treatment of the tumoral process and may be used for other disease processes such viral and parasitic infection. This review focuses on the biologic and molecular characteristics of cfDNA in general and the molecular changes (mutational and epigenetic) proven useful in oncologic practice for diagnosis, monitoring and treatment of breast cancer specifically.

Advances in the Detection Technologies and Clinical Applications of Circulating Tumor DNA in Metastatic Breast Cancer

Breast cancer (BC) represents the most commonly diagnosed cancer among females worldwide. Although targeted therapy has greatly improved the efficacy of treating BC, a large proportion of BC patients eventually develop recurrence or metastasis. Traditional invasive tumor tissue biopsy is short of comprehensiveness in tumor assessment due to heterogeneity. Liquid biopsy, an attractive non-invasive approach mainly including circulating tumor cell and circulating tumor DNA (ctDNA), has been widely utilized in a variety of cancers with the advances of sequencing technologies in recent years. The ctDNA that is found circulating in body fluids refers to DNA released from tumor cells and has shown clinical utility in metastatic breast cancer (MBC). With the results of genomic variants detection, ctDNA could be used to predict clinical outcomes, monitor disease progression, and guide treatment for patients with MBC. Moreover, the drug resistance problem may be addressed by ctDNA detection. In this review, we summarized the technological developments and clinical applications of ctDNA in MBC.

TarPan: an easily adaptable targeted sequencing panel viewer for research and clinical use

BACKGROUND

The study of cancer genomics continually matures as the number of patient samples sequenced increases. As more data is generated, oncogenic drivers for specific cancer types are discovered along with their associated risks. This in turn leads to potential treatment strategies that pave the way to precision medicine. However, significant financial and analytical barriers make it infeasible to sequence the entire genome of every patient. In contrast, targeted sequencing panels give reliable information on relevant portions of the genome at a fiscally responsible cost. Therefore, we have created the Targeted Panel (TarPan) Viewer, a software tool, to investigate this type of data.

RESULTS

TarPan Viewer helps investigators understand data from targeted sequencing data by displaying the information through a web browser interface. Through this interface, investigators can easily observe copy number changes, mutations, and structural events in cancer samples. The viewer runs in R Shiny with a robust SQLite backend and its input is generated from bioinformatic algorithms reliably described in the literature. Here we show the results from using TarPan Viewer on publicly available follicular lymphoma, breast cancer, and multiple myeloma data. In addition, we have tested and utilized the viewer internally, and this data has been used in high-impact peer-reviewed publications.

CONCLUSIONS

We have designed a flexible, simple to setup viewer that is easily adaptable to any type of cancer targeted sequencing, and has already proven its use in a research laboratory environment. Further, we believe with deeper sequencing and/or more targeted application it could be of use in the clinic in conjunction with an appropriate targeted sequencing panel as a cost-effective diagnostic test, especially in cancers such as acute leukemia or diffuse large B-cell lymphoma that require rapid interventions.

Immuno-Oncology Biomarkers for Personalized Immunotherapy in Breast Cancer

The immune checkpoint blockade therapy has drastically advanced treatment of different types of cancer over the past few years. Female breast cancer is the second leading cause of death in the overall burden of cancers worldwide that is encouraging healthcare professionals to improve cancer care management. The checkpoint blockade therapies combined with novel agents become the recent focus of various clinical trials in breast cancer. However, identification of the patients who are responsive to these therapeutic strategies remained as a major issue for enhancing the efficacy of these treatments. This highlights the unmet need in discovery and development of novel biomarkers to add predictive values for prosperous personalized medicine. In this review we summarize the advances done in the era of biomarker studies and highlight their link in supporting breast cancer immunotherapy.

A Research Roadmap: Connected Health as an Enabler of Cancer Patient Support

The evidence that quality of life is a positive variable for the survival of cancer patients has prompted the interest of the health and pharmaceutical industry in considering that variable as a final clinical outcome. Sustained improvements in cancer care in recent years have resulted in increased numbers of people living with and beyond cancer, with increased attention being placed on improving quality of life for those individuals. Connected Health provides the foundations for the transformation of cancer care into a patient-centric model, focused on providing fully connected, personalized support and therapy for the unique needs of each patient. Connected Health creates an opportunity to overcome barriers to health care support among patients diagnosed with chronic conditions. This paper provides an overview of important areas for the foundations of the creation of a new Connected Health paradigm in cancer care. Here we discuss the capabilities of mobile and wearable technologies; we also discuss pervasive and persuasive strategies and device systems to provide multidisciplinary and inclusive approaches for cancer patients for mental well-being, physical activity promotion, and rehabilitation. Several examples already show that there is enthusiasm in strengthening the possibilities offered by Connected Health in persuasive and pervasive technology in cancer care. Developments harnessing the Internet of Things, personalization, patient-centered design, and artificial intelligence help to monitor and assess the health status of cancer patients. Furthermore, this paper analyses the data infrastructure ecosystem for Connected Health and its semantic interoperability with the Connected Health economy ecosystem and its associated barriers. Interoperability is essential when developing Connected Health solutions that integrate with health systems and electronic health records. Given the exponential business growth of the Connected Health economy, there is an urgent need to develop mHealth (mobile health) exponentially, making it both an attractive and challenging market. In conclusion, there is a need for user-centered and multidisciplinary standards of practice to the design, development, evaluation, and implementation of Connected Health interventions in cancer care to ensure their acceptability, practicality, feasibility, effectiveness, affordability, safety, and equity.

Whole genome amplification of cell-free DNA enables detection of circulating tumor DNA mutations from fingerstick capillary blood

The ability to measure mutations in plasma cell-free DNA (cfDNA) has the potential to revolutionize cancer surveillance and treatment by enabling longitudinal monitoring not possible with solid tumor biopsies. However, obtaining sufficient quantities of cfDNA remains a challenge for assay development and clinical translation; consequently, large volumes of venous blood are typically required. Here, we test proof-of-concept for using smaller volumes via fingerstick collection. Matched venous and fingerstick blood were obtained from seven patients with metastatic breast cancer. Fingerstick blood was separated at point-of-care using a novel paper-based concept to isolate plasma centrifuge-free. Patient cfDNA was then analyzed with or without a new method for whole genome amplification via rolling-circle amplification (WG-RCA). We identified somatic mutations by targeted sequencing and compared the concordance of mutation detection from venous and amplified capillary samples by droplet-digital PCR. Patient mutations were detected with 100% concordance after WG-RCA, although in some samples, allele frequencies showed greater variation likely due to differential amplification or primer inaccessibility. These pilot findings provide physiological evidence that circulating tumor DNA is accessible by fingerstick and sustains presence/absence of mutation detection after whole-genome amplification. Further refinement may enable simpler and less-invasive methods for longitudinal or theranostic surveillance of metastatic cancer.