Durvalumab with olaparib and paclitaxel for high-risk HER2-negative stage II/III breast cancer: Results from the adaptively randomized I-SPY2 trial.

The combination of PD-L1 inhibitor durvalumab and PARP inhibitor olaparib added to standard paclitaxel neoadjuvant chemotherapy (durvalumab/olaparib/paclitaxel [DOP]) was investigated in the phase II I-SPY2 trial of stage II/III HER2-negative breast cancer. Seventy-three participants were randomized to DOP and 299 to standard of care (paclitaxel) control. DOP increased pathologic complete response (pCR) rates in all HER2-negative (20%-37%), hormone receptor (HR)-positive/HER2-negative (14%-28%), and triple-negative breast cancer (TNBC) (27%-47%). In HR-positive/HER2-negative cancers, MammaPrint ultra-high (MP2) cases benefited selectively from DOP (pCR 64% versus 22%), no benefit was seen in MP1 cancers (pCR 9% versus 10%). Overall, 12.3% of patients in the DOP arm experienced immune-related grade 3 adverse events versus 1.3% in control. Gene expression signatures associated with immune response were positively associated with pCR in both arms, while a mast cell signature was associated with non-pCR. DOP has superior efficacy over standard neoadjuvant chemotherapy in HER2-negative breast cancer, particularly in a highly sensitive subset of high-risk HR-positive/HER2-negative patients.

Network proteomics of human dermal wound healing.

OBJECTIVE: The healing of wounds is critical in protecting the human body against environmental factors. The mechanisms involving protein expression during this complex physiological process have not been fully elucidated. APPROACH: Here, we use reverse-phase protein microarrays (RPPA) involving 94 phosphoproteins to study tissue samples from tubes implanted in healing dermal wounds in seven human subjects tracked over two weeks. We compare the proteomic profiles to proteomes of controls obtained from skin biopsies from the same subjects. MAIN RESULTS: Compared to previous proteomic studies of wound healing, our approach focuses on wound tissue instead of wound fluid, and has the sensitivity to go beyond measuring only highly abundant proteins. To study the temporal dynamics of networks involved in wound healing, we applied two network analysis methods that integrate the experimental results with prior knowledge about protein-protein physical and regulatory interactions, as well as higher-level biological processes and associated pathways. SIGNIFICANCE: We uncovered densely connected networks of proteins that are up- or down-regulated during human wound healing, as well as their relationships to microRNAs and to proteins outside of our set of targets that we measured with proteomic microarrays.

National Academy of Clinical Biochemistry Laboratory Medicine Practice Guidelines for use of tumor markers in clinical practice: quality requirements.

BACKGROUND: This report presents updated National Academy of Clinical Biochemistry Laboratory Medicine Practice Guidelines summarizing quality requirements for the use of tumor markers. METHODS: One subcommittee developed guidelines for analytical quality relevant to serum and tissue-based tumor markers in current clinical practice. Two other subcommittees formulated recommendations particularly relevant to the developing technologies of microarrays and mass spectrometry. RESULTS: Prerequisites for optimal use of tumor markers in routine practice include formulation of the correct clinical questions to ensure selection of the appropriate test, adherence to good clinical and laboratory practices (e.g., minimization of the risk of incorrect patient and/or specimen identification, tube type, or timing), use of internationally standardized and well-characterized methods, careful adherence to manufacturer instructions, and proactive and timely reactions to information derived from both internal QC and proficiency-testing specimens. Highly desirable procedures include those designed to minimize the risk of the reporting of erroneous results attributable to interferences such as heterophilic antibodies or hook effects, to facilitate the provision of informative clinical reports (e.g., cumulative and/or graphical reports, appropriately derived reference intervals, and interpretative comments), and when possible to integrate these reports with other patient information through electronic health records. Also mandatory is extensive validation encompassing all stages of analysis before introduction of new technologies such as microarrays and mass spectrometry. Provision of high-quality tumor marker services is facilitated by dialogue involving researchers, diagnostic companies, clinical and laboratory users, and regulatory agencies. CONCLUSIONS: Implementation of these recommendations, adapted to local practice, should encourage optimization of the clinical use of tumor markers.

Cancer proteomics: many technologies, one goal.

A major goal of the National Cancer Institute is to alleviate patient pain, suffering and death associated with cancer by the year 2015. This goal does not insinuate a cure for cancer, but rather the development of diagnostics and therapeutics that will eventually decrease cancer morbidity and mortality. A part of meeting this goal is to leverage the enormous data-gathering capabilities of proteomic technologies to discover disease-specific biomarkers in serum, plasma, urine, tissues and other biologic samples. The rapid advance in available technologies that have been spurred by the -omics era, has enabled biologic samples to be surveyed for biomarkers in ways never before possible. However, it is not yet clear which specific technologies will be the most successful. Therefore, proteomic laboratories within the National Cancer Institute are taking a multipronged approach to identify disease-specific biomarkers. This review discusses some of these approaches in their context of meeting the National Cancer Institute's 2015 goal.

Proteomic analysis of human breast cancer tissue with laser-capture microdissection and reverse-phase protein microarrays.

Despite recent advances in breast cancer therapy, women with similar types of breast cancers may respond very differently to standard treatments. The emerging field of clinical proteomics has the potential to revolutionize breast cancer therapy. The ultimate goal of clinical proteomics is to characterize information flow through protein cascades for individual patients. After the protein networks have been elucidated, drug therapies may be specially designed for each patient. The following review describes the proteomic technologies of laser-capture microdissection (LCM) and reverse-phase protein arrays (RPPAs). These technologies allow scientists to analyze relative abundances of key cellular signaling proteins from pure cell populations. Cell survival and apoptotic protein pathways are currently being monitored with LCM and RPPAs at the National Institutes of Health, in phase II clinical trials of metastatic breast and ovarian cancers. Ultimately, proteomics will become an integral component of tracking and managing individualized breast cancer therapy.

Molecular profiling of cancer.

The objective of molecular profiling of cancer is to determine the differential expression of genes and proteins from human tissue in the progression from normal precursor tissue to preneoplastic tissue to cancer in order to discover diagnostic, prognostic, and therapeutic markers. With the development of high-throughput analytical techniques such as microarrays and 2-D PAGE as well as the development of tools for cell procurement from histological sections such as laser capture microdissection (LCM), it is now possible to perform molecular analyses on specific cell populations from tissue. Since recognition of specific cell populations is critical, there is a need to optimize fixation and embedding not only to improve preservation of biomolecules, but also to maintain excellent histology. We have shown that 70% ethanol fixation of prostate tissue improves the recovery of DNA, RNA, and proteins over routine formalin fixation and maintains histological quality comparable to formalin. There is also a need to develop new technologies in order to expand the range of tissue types that can be analyzed. The development and applications of Layered Expression Scanning (LES) for the molecular analysis of whole tissue sections are discussed.

Proteomics to diagnose human tumors and provide prognostic information.

Proteomics is a rapidly emerging scientific discipline that holds great promise in identifying novel diagnostic and prognostic biomarkers for human cancer. Technologic improvements have made it possible to profile and compare the protein composition within defined populations of cells. Laser capture microdissection is a tool for procuring pure populations of cells from human tissue sections to be used for downstream proteomic analysis. Two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) has been used traditionally to separate complex mixtures of proteins. Improvements in this technology have greatly enhanced resolution and sensitivity providing a more reproducible and comprehensive survey. Image analysis software and robotic instrumentation have been developed to facilitate comparisons of complex protein expression patterns and isolation of differentially expressed proteins spots. Differential in-gel electrophoresis (DIGE) facilitates protein expression by labeling different populations of proteins with fluorescent dyes. Isotope-coded affinity tagging (ICAT) uses mass spectroscopy for protein separation and different isotope tags for distinguishing populations of proteins. Although in the past proteomics has been primarily used for discovery, significant efforts are being made to develop proteomic technologies into clinical tools. Reverse-phase protein arrays offer a robust new method of quantitatively assessing expression levels and the activation status of a panel of proteins. Surface-enhanced laser-desorption/ionization time-of-flight (SELDI-TOF) mass spectroscopy rapidly assesses complex protein mixtures in tissue or serum. Combined with artificial intelligence-based pattern recognition algorithms, this emerging technology can generate highly accurate diagnostic information. It is likely that mass spectroscopy-based serum proteomics will evolve into useful clinical tools for the detection and treatment of human cancers.

Diagnostic markers that distinguish colon and ovarian adenocarcinomas: identification by genomic, proteomic, and tissue array profiling.

Colon and ovarian cancers can be difficult to distinguish in the abdomen, and the distinction is important because it determines which drugs will be used for therapy. To identify molecular markers for that differential diagnosis, we developed a multistep protocol starting with the 60 human cancer cell lines used by the National Cancer Institute to screen for new anticancer agents. The steps included: (a) identification of candidate markers using cDNA microarrays; (b) verification of clone identities by resequencing; (c) corroboration of transcript levels using Affymetrix oligonucleotide chips; (d) quantitation of protein expression by "reverse-phase" protein microarray; and (e) prospective validation of candidate markers on clinical tumor sections in tissue microarrays. The two best candidates identified were villin for colon cancer cells and moesin for ovarian cancer cells. Because moesin stained stromal elements in both types of cancer, it would probably not have been identified as a marker if we had started with mRNA or protein profiling of bulk tumors. Villin appears at least as useful as the currently used colon cancer marker cytokeratin 20, and moesin also appears to have utility. The multistep process introduced here has the potential to produce additional markers for cancer diagnosis, prognosis, and therapy.

Cancer diagnosis using proteomic patterns.

The advent of proteomics has brought with it the hope of discovering novel biomarkers that can be used to diagnose diseases, predict susceptibility and monitor progression. Much of this effort has focused upon the mass spectral identification of the thousands of proteins that populate complex biosystems such as serum and tissues. A revolutionary approach in proteomic pattern analysis has emerged as an effective method for the early diagnosis of diseases such as ovarian cancer. Proteomic pattern analysis relies on the pattern of proteins observed and does not rely on the identification of a traceable biomarker. Hundreds of clinical samples per day can be analyzed utilizing this technology, which has the potential to be a novel, highly sensitive diagnostic tool for the early detection of cancer.

Proteomic evaluation of archival cytologic material using SELDI affinity mass spectrometry: potential for diagnostic applications.

Proteomic studies of cells via surface-enhanced laser desorption/ionization spectrometry (SELDI) analysis have enabled rapid, reproducible protein profiling directly from crude samples. We applied this technique to archival cytology material to determine whether distinct, reproducible protein fingerprints could be identifiedfor potential diagnostic purposes in blinded specimens. Rapid Romanowsky-stained cytocentrifuged specimens from fine-needle aspirates of metastatic malignant melanoma (with both known cutaneous primary and unknown primary sites), clear cell sarcoma, and renal cell carcinoma and reactive effusions were examined using the SELDI technology. A unique characteristic fingerprint was identified for each disease entity. Fifteen "blinded" unknown samples then were analyzed. When the protein profilefingerprints were plotted against the known fingerprints for the aforementioned diagnoses, the appropriate match or diagnosis was obtained in 13 (87%) of 15 cases. These preliminary findings suggest a substantial potential for SELDI applications to specific pathologic diagnoses.

Genomics and proteomics: application of novel technology to early detection and prevention of cancer.

Advances in molecular biology over the past decade have helped to enhance our understanding of the complex interplay between genetic, transcriptional and translational alterations in human cancers. These molecular changes are the basis for an evolving field of high-throughput cancer discovery techniques using microscopic amounts of patient-based materials. Laser capture microdissection allows pure populations of cells to be isolated from both the tumor and stroma in order to identify subtle differences in RNA and protein expression. Comparative analysis of these alterations between normal, pre-invasive, and invasive tissue using powerful bioinformatics programs has allowed us to identify novel tumor markers, profile complex protein pathways, and develop new molecular-based therapies. Continued refinement of such high-throughput microtechnologies will enable us to rapidly query patient specimens to identify novel methods for early detection, treatment, and follow-up of a wide array of human cancers.

Evaluation of non-formalin tissue fixation for molecular profiling studies.

Using a general strategy for evaluating clinical tissue specimens, we found that 70% ethanol fixation and paraffin embedding is a useful method for molecular profiling studies. Human prostate and kidney were used as test tissues. The protein content of the samples was analyzed by one-dimensional gel electrophoresis, immunoblot, two-dimensional gel electrophoresis, and layered expression scanning. In each case, the fixed and embedded tissues produced results similar to that obtained from snap-frozen specimens, although the protein quantity was somewhat decreased. Recovery of mRNA was reduced in both quantity and quality in the ethanol-fixed samples, but was superior to that obtained from formalin-fixed samples and sufficient to perform reverse transcription polymerase chain reactions. Recovery of DNA from ethanol-fixed specimens was superior to formalin-fixed samples as determined by one-dimensional gel electrophoresis and polymerase chain reaction. In conclusion, specimens fixed in 70% ethanol and embedded in paraffin produce good histology and permit recovery of DNA, mRNA, and proteins sufficient for several downstream molecular analyses. Complete protocols and additional discussion of relevant issues are available on an accompanying website (http://cgap-mf.nih.gov/).

Proteomic analysis and identification of new biomarkers and therapeutic targets for invasive ovarian cancer.

Epithelial ovarian cancer kills almost 16 000 women each year in part due to late stage of presentation and lack of reliable biomarkers for disease detection. CA-125, the currently accepted serum marker, alone lacks the sensitivity for early stage diagnosis, as only 50% of early stage cases are detected with this marker. Although more early stage cases may be detected by lysophosphatidic acid, this marker is also elevated in other cancers. One major objective of the NCI-FDA Tissue Proteomics Initiative has been to combine the technique of laser capture microdissection (LCM) of epithelial tumor cells in human tissue specimens with two-dimensional gel electrophoresis (2-D PAGE) to identify proteins that may serve as invasive ovarian cancer-specific biomarkers for early detection and/or new therapeutic targets. We performed 2-D PAGE on lysates from five microdissected ovarian tumors (three invasive ovarian cancers and two noninvasive, low malignant potential (LMP) ovarian tumors). We then compared silver stained 2-D gels created from microdissected lysates with SYPRO-Ruby stained 2-D PAGE profiles of the patient-matched undissected bulk tumor lysates from all five patients. Twenty-three proteins were consistently differentially expressed between both the LMP and three invasive ovarian tumors in the limited study set. Thirteen were uniquely present in all three of the invasive ovarian cancer cases and absent or underexpressed in the two LMP cases. Ten were uniquely present in the LMP cases but absent or underexpressed in all invasive ovarian cancer cases. Credentialing and preliminary target validation of the mass spectrometry identified proteins cut from the Ruby-red stained gels was performed by LCM coupled Western blot and reverse-phase array technology in a study set of six cases (the aforementioned five cases used in the 2-D PAGE profiling component of the study plus one additional LMP case). The analysis revealed that the 52 kDa FK506 binding protein, Rho G-protein dissociation inhibitor (RhoGDI), and glyoxalase I are found to be uniquely overexpressed in invasive human ovarian cancer when compared to the LMP form of this cancer. The direct comparison of LCM generated proteomic profiles of invasive vs. LMP ovarian cancer may more directly generate important markers for early detection and/or therapeutic targets unique to the invasive phenotype.