The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.

Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal

Over the past decade, comprehensive sequencing efforts have revealed the genomic landscapes of common forms of human cancer. For most cancer types, this landscape consists of a small number of “mountains” (genes altered in a high percentage of tumors) and a much larger number of “hills” (genes altered infrequently). To date, these studies have revealed ~140 genes that, when altered by intragenic mutations, can promote or “drive” tumorigenesis. A typical tumor contains two to eight of these “driver gene” mutations; the remaining mutations are passengers that confer no selective growth advantage. Driver genes can be classified into 12 signaling pathways that regulate three core cellular processes: cell fate, cell survival, and genome maintenance. A better understanding of these pathways is one of the most pressing needs in basic cancer research. Even now, however, our knowledge of cancer genomes is sufficient to guide the development of more effective approaches for reducing cancer morbidity and mortality.

/pdf/cancer-genome-landscapes-qmge4i5y2h.pdf

Cancer Genome Landscapes

Comprehensive molecular portraits of human breast tumours

Immune checkpoint inhibition represents a major recent breakthrough in the treatment of malignant diseases including breast cancer. Blocking the programmed death receptor-1 (PD-1) and its ligand, PD-L1, has shown impressive antitumor activity and may lead to durable long-term disease control, especially in the triple-negative subtypes of breast cancer (TNBC). Although immune checkpoint blockade is generally well tolerated, specific immune-related adverse events (irAEs) may occur. This review summarizes the clinical efficacy, perspectives, and future challenges of using PD-1/PD-L1-directed antibodies in the treatment of breast cancer.

/pdf/pd-1-and-pd-l1-immune-checkpoint-blockade-to-treat-breast-2u575m0pog.pdf

PD-1 and PD-L1 Immune Checkpoint Blockade to Treat Breast Cancer

The number of cancer survivors continues to increase because of both advances in early detection and treatment and the aging and growth of the population. For the public health community to better serve these survivors, the American Cancer Society and the National Cancer Institute collaborate to estimate the number of current and future cancer survivors using data from the Surveillance, Epidemiology, and End Results cancer registries. In addition, current treatment patterns for the most prevalent cancer types are presented based on information in the National Cancer Data Base and treatment-related side effects are briefly described. More than 15.5 million Americans with a history of cancer were alive on January 1, 2016, and this number is projected to reach more than 20 million by January 1, 2026. The 3 most prevalent cancers are prostate (3,306,760), colon and rectum (724,690), and melanoma (614,460) among males and breast (3,560,570), uterine corpus (757,190), and colon and rectum (727,350) among females. More than one-half (56%) of survivors were diagnosed within the past 10 years, and almost one-half (47%) are aged 70 years or older. People with a history of cancer have unique medical and psychosocial needs that require proactive assessment and management by primary care providers. Although there are a growing number of tools that can assist patients, caregivers, and clinicians in navigating the various phases of cancer survivorship, further evidence-based resources are needed to optimize care. CA Cancer J Clin 2016;66:271-289. © 2016 American Cancer Society.

https://onlinelibrary.wiley.com/doi/pdf/10.3322/caac.21349

Cancer treatment and survivorship statistics, 2016.

Purpose: Patient-derived xenografts (PDX) are a research tool for studying cancer biology and drug response phenotypes. While engraftment rates are higher for tumors with more aggressive characteristics, it is uncertain whether engraftment is prognostic for cancer recurrence. Patients and Methods: In a prospective study of patients with breast cancer treated with neoadjuvant chemotherapy (NAC) with taxane ± trastuzumab followed by anthracycline-based chemotherapy, we report the association between breast cancer events and PDX engraftment using tumors derived from treatment naive (pre-NAC biopsies from 113 patients) and treatment resistant (post-NAC at surgery from 34 patients). Gray test was used to assess whether the cumulative incidence of a breast cancer event differs with respect to either pre-NAC PDX engraftment or post-NAC PDX engraftment. Results: With a median follow-up of 5.7 years, the cumulative incidence of breast cancer relapse did not differ significantly according to pre-NAC PDX engraftment (5-year rate: 13.6% vs. 13.4%; P = 0.89). However, the incidence of a breast event was greater for patients with post-NAC PDX engraftment (5-year rate: 50.0% vs. 19.6%), but this did not achieve significance (P = 0.11). Conclusions: In treatment-naive breast cancer receiving standard NAC, PDX engraftment was not prognostic for breast cancer recurrence. Further study is needed to establish whether PDX engraftment in the treatment-resistant setting is prognostic for cancer recurrence.

Patient-Derived Xenograft Engraftment and Breast Cancer Outcomes in a Prospective Neoadjuvant Study (BEAUTY).

Phase II study of the combination of dianhydrogalactitol, doxorubicin, and cisplatin (DAP) in patients with advanced squamous cell lung cancer.

Extending Adjuvant Aromatase-Inhibitor Therapy to 10 Years.

e13501 Background: Loss of estrogen receptor alpha gene expression has been associated with insensitivity to endocrine therapy in human breast cancer patients. Histone deacetylase (HDAC) inhibitors...

Phase I study of panobinostat (LBH589) and letrozole in post-menopausal women with metastatic breast cancer.

The majority of cancer patients receive treatments that are minimally informed by omics data. Our goal was to develop a precision medicine computational framework (PANOPLY: Precision cancer genomic report: single sample inventory) to identify and prioritize drug targets and cancer therapy regimens. The PANOPLY approach integrates clinical data with germline and somatic features obtained from multi-omics platforms, and apply machine learning, and network analysis approaches in the context of the individual patient and matched controls. The PANOPLY employs multiple steps including i) selection of matched controls, ii) preprocessing of data and identification of driver mutations and altered genes in the patient, iii) identification of suitable drugs using the driver-gene network and random forest analysis, and iv) a multi-omics case report of the patient with prioritization of anti-cancer drugs. The PANOPLY framework can be executed on a stand-alone virtual machine and is also available for download as an R package. We applied PANOPLY to multiple publicly accessible multi-omics tumor datasets with survival data available. We also applied the method to an institutional breast cancer neoadjuvant chemotherapy study which collected clinical and genomic data as well as patient-derived xenografts (PDXs) to investigate the prioritization offered by PANOPLY. We found that that the prioritized drug, olaparib, was more effective than placebo at treating the tumor in the chemotherapy resistant PDX model (P < 0.05). Further studies are ongoing to determine the efficacy of PANOPLY using additional PDXs. In summary, PANOPLY prioritizes drugs based on both clinical and multi-omics data, and it can aid oncologists in their decision-making for therapy in the individual patient.

https://www.biorxiv.org/content/biorxiv/early/2017/08/15/176396.full.pdf

James N. Ingle

Papers

Patient-Derived Xenograft Engraftment and Breast Cancer Outcomes in a Prospective Neoadjuvant Study (BEAUTY).

Phase II study of the combination of dianhydrogalactitol, doxorubicin, and cisplatin (DAP) in patients with advanced squamous cell lung cancer.

Extending Adjuvant Aromatase-Inhibitor Therapy to 10 Years.

Phase I study of panobinostat (LBH589) and letrozole in post-menopausal women with metastatic breast cancer.

PANOPLY: A computational method for identification of promising drugs for a patient based on multidimensional data