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Immunohistochemical (IHC) staining is an established technique for visualizing proteins in tissue sections for research studies and clinical applications. IHC is increasingly used as a targeting strategy for procurement of labeled cells via tissue microdissection, including immunodissection, computer-aided laser dissection (CALD), expression microdissection (xMD), and other techniques. The initial antigen retrieval (AR) process increases epitope availability and improves staining characteristics; however, the procedure can damage DNA. To better understand the effects of AR on DNA quality and quantity in immunodissected samples, both clinical specimens ( KRAS gene mutation positive cases) and model system samples (lung cancer patient-derived xenograft tissue) were subjected to commonly employed AR methods (heat induced epitope retrieval [HIER], protease digestion) and the effects on DNA were assessed by Qubit, fragment analysis, quantitative PCR, digital droplet PCR (ddPCR), library preparation, and targeted sequencing. The data showed that HIER resulted in optimal IHC staining characteristics, but induced significant damage to DNA, producing extensive fragmentation and decreased overall yields. However, neither of the AR methods combined with IHC prevented ddPCR amplification of small amplicons and gene mutations were successfully identified from immunodissected clinical samples. The results indicate for the first time that DNA recovered from immunostained slides after standard AR and IHC processing can be successfully employed for genomic mutation analysis via ddPCR and next-generation sequencing (NGS) short-read methods.

Synopsis of the 20 top-scored pathways associated with WLT-unique genes identified in the three tumors.

Unabridged List of Genes Differentially Expressed Between AD and AI Prostate Cancer

Purpose: After an initial response to androgen ablation, most prostate tumors recur, ultimately progressing to highly aggressive androgen-independent cancer. The molecular mechanisms underlying progression are not well known in part due to the rarity of androgen-independent samples from primary and metastatic sites.Experimental Design: We compared the gene expression profiles of 10 androgen-independent primary prostate tumor biopsies with 10 primary, untreated androgen-dependent tumors. Samples were laser capture microdissected, the RNA was amplified, and gene expression was assessed using Affymetrix Human Genome U133A GeneChip. Differential expression was examined with principal component analysis, hierarchical clustering, and Student's t testing. Analysis of gene ontology was done with Expression Analysis Systematic Explorer and gene expression data were integrated with genomic alterations with Differential Gene Locus Mapping.Results: Unsupervised principal component analysis showed that the androgen-dependent and androgen-independent tumors segregated from one another. After filtering the data, 239 differentially expressed genes were identified. Two main gene ontologies were found discordant between androgen-independent and androgen-dependent tumors: macromolecule biosynthesis was down-regulated and cell adhesion was up-regulated in androgen-independent tumors. Other differentially expressed genes were related to interleukin-6 signaling as well as angiogenesis, cell adhesion, apoptosis, oxidative stress, and hormone response. The Differential Gene Locus Mapping analysis identified nine regions of potential chromosomal deletion in the androgen-independent tumors, including 1p36, 3p21, 6p21, 8p21, 11p15, 11q12, 12q23, 16q12, and 16q21.Conclusions: Taken together, these data identify several unique characteristics of androgen-independent prostate cancer that may hold potential for the development of targeted therapeutic intervention.

Supplementary Figure 1 from Large-Scale Profiling of Archival Lymph Nodes Reveals Pervasive Remodeling of the Follicular Lymphoma Methylome

Supplementary Table 3 from Large-Scale Profiling of Archival Lymph Nodes Reveals Pervasive Remodeling of the Follicular Lymphoma Methylome

Supplementary Figure Legend from Large-Scale Profiling of Archival Lymph Nodes Reveals Pervasive Remodeling of the Follicular Lymphoma Methylome

Supplementary Table 2 from Large-Scale Profiling of Archival Lymph Nodes Reveals Pervasive Remodeling of the Follicular Lymphoma Methylome

Supplementary Table 1 from Large-Scale Profiling of Archival Lymph Nodes Reveals Pervasive Remodeling of the Follicular Lymphoma Methylome

Supplementary Table 5 from Large-Scale Profiling of Archival Lymph Nodes Reveals Pervasive Remodeling of the Follicular Lymphoma Methylome

Supplementary Table 4 from Large-Scale Profiling of Archival Lymph Nodes Reveals Pervasive Remodeling of the Follicular Lymphoma Methylome

Emerging technologies allow broad profiling of the cancer genome for differential DNA methylation relative to benign cells. Herein, bisulfite-modified DNA from lymph nodes with either reactive hyperplasia or follicular lymphoma (FL) were analyzed using a commercial C/UpG genotyping assay. Two hundred fifty-nine differentially methylated targets (DMT) distributed among 183 unique genes were identified in FL. Comparison of matched formalin-fixed, paraffin-embedded and frozen surgical pathology replicates showed the complete preservation of the cancer methylome among differently archived tissue specimens. Analysis of the DMT profile is consistent with a pervasive epigenomic remodeling process in FL that affects predominantly nonlymphoid genes. [Cancer Res 2009;69(3):758–64]

Supplementary Table 6 from Large-Scale Profiling of Archival Lymph Nodes Reveals Pervasive Remodeling of the Follicular Lymphoma Methylome

Improving the utilization of tumor tissue from diagnostic biopsies is an unmet medical need. This is especially relevant today in the rapidly evolving precision oncology field where tumor genotyping is often essential for the indication of many advanced and targeted therapies. National Comprehensive Cancer Network (NCCN) guidelines now mandate molecular testing for clinically actionable targets in certain malignancies. Utilizing advanced stage lung cancer as an example, an improved genotyping approach for solid tumors is possible. The strategy involves optimization of the microdissection process and analysis of a large number of identical target cells from formalin-fixed paraffin-embedded (FFPE) specimens sharing similar characteristics, in other words, single-cell subtype analysis. The shared characteristics can include immunostaining status, cell phenotype, and/or spatial location within a histological section. Synergy between microdissection and droplet digital PCR (ddPCR) enhances the molecular analysis. We demonstrate here a methodology that illustrates genotyping of a solid tumor from a small tissue biopsy sample in a time- and cost-efficient manner, using immunostain targeting as an example.

The evolutionary progression from primary to metastatic prostate cancer is largely uncharted, and the implications for liquid biopsy are unexplored. We infer detailed reconstructions of tumor phylogenies in ten prostate cancer patients with fatal disease, and investigate them in conjunction with histopathology and tumor DNA extracted from blood and cerebrospinal fluid. Substantial evolution occurs within the prostate, resulting in branching into multiple spatially intermixed lineages. One dominant lineage emerges that initiates and drives systemic metastasis, where polyclonal seeding between sites is common. Routes to metastasis differ between patients, and likely genetic drivers of metastasis distinguish the metastatic lineage from the lineage that remains confined to the prostate within each patient. Body fluids capture features of the dominant lineage, and subclonal expansions that occur in the metastatic phase are non-uniformly represented. Cerebrospinal fluid analysis reveals lineages not detected in blood-borne DNA, suggesting possible clinical utility., The evolutionary progression from primary to metastatic prostate cancer is largely uncharted, and the implications for liquid biopsy are unexplored. Here, the authors use deep genomic sequencing and histopathological information to trace tumor evolution both within the prostate and during metastasis in ten men.

In the Supplementary Information of this Article, some errors were made in compiling the Supplementary Data file called ‘Supplementary Variant Lists’. In the first worksheet (entitled ‘subs’) the clusters to which some single nucleotide variants (SNVs) were assigned were not reported and were replaced with ‘NA’ for ‘not available’. The correct cluster numbers have now been inserted. Three mutations occurring in tumour A32 were incorrectly assigned to cluster 3 and have now been correctly assigned to cluster 2. Duplicate entries were present for some mutations in A32. These duplicate entries have now been removed. In the fourth worksheet (entitled ‘copy_number’) incorrect copy number information was reported for sample A31-c. The previous information, implying that A31-c was primarily diploid, has now been replaced with the copy number call used within the Article, which indicates that A31-c is primarily tetraploid. The Supplementary Information to this Amendment contains the corrected Excel file ‘Supplementary Variant Lists’. These corrections do not change the authors’ interpretation of the findings. The original Article has not been corrected.

There is limited data on the molecular mechanisms whereby hepatitis D virus (HDV) promotes liver cancer. Therefore, serum and liver specimens obtained at the time of liver transplantation from well-characterized patients with HDV-HCC (n = 5) and with non-HCC HDV cirrhosis (n = 7) were studied using an integrated genomic approach. Transcriptomic profiling was performed using laser capture–microdissected (LCM) malignant and nonmalignant hepatocytes, tumorous and nontumorous liver tissue from patients with HDV-HCC, and liver tissue from patients with non-HCC HDV cirrhosis. HDV-HCC was also compared with hepatitis B virus (HBV) HBV-HCC alone, and hepatitis C virus (HCV) HCV-HCC. HDV malignant hepatocytes were characterized by an enrichment of upregulated transcripts associated with pathways involved in cell-cycle/DNA replication, damage, and repair (Sonic Hedgehog, GADD45, DNA-damage-induced 14-3-3σ, cyclins and cell-cycle regulation, cell cycle: G2–M DNA-damage checkpoint regulation, and hereditary breast cancer). Moreover, a large network of genes identified functionally relate to DNA repair, cell cycle, mitotic apparatus, and cell division, including 4 cancer testis antigen genes, attesting to the critical role of genetic instability in this tumor. Besides being overexpressed, these genes were also strongly coregulated. Gene coregulation was high not only when compared with nonmalignant hepatocytes, but also to malignant hepatocytes from HBV-HCC alone or HCV-HCC. Activation and coregulation of genes critically associated with DNA replication, damage, and repair point to genetic instability as an important mechanism of HDV hepatocarcinogenesis. This specific HDV-HCC trait emerged also from the comparison of the molecular pathways identified for each hepatitis virus–associated HCC. Despite the dependence of HDV on HBV, these findings suggest that HDV and HBV promote carcinogenesis by distinct molecular mechanisms. Implications: This study identifies a molecular signature of HDV-associated hepatocellular carcinoma and suggests the potential for new biomarkers for early diagnostics. Mol Cancer Res; 16(9); 1406–19. ©2018 AACR.

Background - The domain of precision oncology includes improving patient treatment outcomes based on the application of advanced molecular profiling methodologies to pathological specimens. To this end, optimal utilization of tumor tissue from diagnostic biopsies is an unmet medical need. This is especially relevant today since precision oncology is a rapidly evolving field where timely tumor genotyping is essential for the indication of many advanced and targeted therapies. National Comprehensive Cancer Network (NCCN) guidelines now mandate molecular testing for clinically actionable targets in certain malignancies. Patients diagnosed with advanced non-small cell lung cancer (NSCLC) are commonly of an older age and have significant co-morbidities. This frequently causes clinical dilemmas regarding the ability to obtain adequate amounts of tissue for tumor genotyping. In these cases, the tumor tissue may have been obtained by an image-guided biopsy, and the diagnosis of NSCLC proper determined via cytology. In certain instances, adequate tissue for tumor genotyping and/or a more advanced mutational analysis to identify oncogenic drivers may not be available. Methods - Formalin fixed paraffin embedded (FFPE) specimens were examined using advanced immuno-based laser capture microdissection (LCM), following a formal pathology review. In preparation for droplet digital PCR (ddPCR), DNA was extracted from samples and run with a series of positive and negative controls. Results - Utilizing lung cancer as an example, an improved genotyping approach for NSCLC solid tumors was developed and tested. The strategy involves optimization of the microdissection process and analysis of a large number of identical target cells from FFPE specimens sharing similar characteristics, in other words, single-cell subtype analysis. Immunostaining status, cell phenotype, and spatial location within a histological section are examples of shared characteristics that can guide cell procurement. Conclusions - Synergy between microdissection and ddPCR enhances molecular analysis. Demonstrated is a methodology that illustrates genotyping of a solid tumor from a small tissue biopsy sample in a time and cost-efficient manner, using immunohistochemistry directed LCM and ddPCR detection. Citation Format: Donald J. Johann, Ikjae Shin, Erich Peterson, Mathew Steliga, Jason Muesse, Katy Marino, Sarah Laun, Adam Roberge, Robert Weigman, Michael Emmert-Buck, Michael Tangrea. Advancing precision oncology by synergizing ddPCR with microdissection [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 373.

The increasing availability of large institutional and public histopathology image datasets is enabling the searching of these datasets for diagnosis, research, and education. Though these datasets typically have associated metadata such as diagnosis or clinical notes, even carefully curated datasets rarely contain annotations of the location of regions of interest on each image. Because pathology images are extremely large (up to 100,000 pixels in each dimension), further laborious visual search of each image may be needed to find the feature of interest. In this paper, we introduce a deep learning based reverse image search tool for histopathology images: Similar Medical Images Like Yours (SMILY). We assessed SMILY's ability to retrieve search results in two ways: using pathologist-provided annotations, and via prospective studies where pathologists evaluated the quality of SMILY search results. As a negative control in the second evaluation, pathologists were blinded to whether search results were retrieved by SMILY or randomly. In both types of assessments, SMILY was able to retrieve search results with similar histologic features, organ site, and prostate cancer Gleason grade compared with the original query. SMILY may be a useful general-purpose tool in the pathologist's arsenal, to improve the efficiency of searching large archives of histopathology images, without the need to develop and implement specific tools for each application., 23 Pages with 6 figures and 3 tables. The file also has 6 pages of supplemental material. Improved figure resolution, edited metadata

e15083 Background: Improving patient treatment outcomes based on the application of advanced molecular profiling methodologies applied to pathological specimens is the purview of precision oncology. Optimal utilization of tumor tissue from diagnostic biopsies remains an unmet medical need. This is especially relevant today since precision oncology is a rapidly evolving field where timely tumor genotyping is essential for the indication of many advanced and targeted therapies. National Comprehensive Cancer Network (NCCN) guidelines now mandate molecular testing for clinically actionable targets in certain malignancies. Patients diagnosed with advanced non-small cell lung cancer (NSCLC) are commonly of an older age and have significant co-morbidities. Clinical dilemmas regarding the ability to obtain adequate amounts of tissue for tumor genotyping frequently occur. In these cases, the tumor tissue may have been obtained by an image-guided biopsy, and the diagnosis of NSCLC proper determined via cytology. Adequate tissue for tumor genotyping and/or a more advanced mutational analysis to identify oncogenic drivers may not be available, and the opportunity to explore more optimal therapy options (eg, TKI in lieu of chemotherapy) is lost. Methods: Following a formal pathology review formalin fixed paraffin embedded (FFPE) specimens were examined using advanced immuno-based laser capture microdissection (LCM). In preparation for droplet digital PCR (ddPCR), nucleic acids were extracted from samples and run with a series of positive and negative controls. Results: Utilizing lung cancer as an example, an improved genotyping approach for NSCLC solid tumors was developed and tested. The strategy involves optimization of the microdissection process and analysis of a large number of identical target cells from FFPE specimens sharing similar characteristics, in other words, single-cell subtype analysis. Immunostaining status, cell phenotype, and spatial location within a histological section are examples of shared characteristics that can guide cell procurement. Conclusions: With this approach, tumor molecular analysis is enhanced through the synergy between microdissection and ddPCR. Here we demonstrate a methodology that illustrates genotyping of a solid tumor from a small tissue biopsy sample in a time and cost-efficient manner, using immunohistochemistry-directed LCM along with the detection and absolute quantitation of mutations by ddPCR.

Introduction: Precision medicine promises to improve patient treatment outcomes based on the application of molecular profiling methodologies to pathological specimens. This approach enables the development of rationally derived therapy assignments for each individual patient's tumor (versus categorical treatment assignments). Since tumors are composed of heterogeneous cells forming clusters of subtypes, dissimilar molecular profiles may emerge depending on which region is sampled and analyzed. Additionally, a manual slide scrape may result in a reduced or nearly absent molecular signal (i.e. key driver). Clearly, for cancer there is a need for an efficient, upfront enrichment method to specifically isolate specific tumor cell populations. Immuno-Laser Capture Microdissection (immuno-LCM) is a technology based on immunohistochemistry (IHC) that can isolate specific cell types from a heterogeneous cellular population. We sought to determine the impact of various IHC chromogens on the efficacy of microdissection and downstream molecular analysis from immuno-LCM samples. Methods: Histological tissue specimens (clinical colorectal and lung cancer PDX) were processed using traditional IHC methods with a variety of chromogens, including: Vector Black, Impact Vector Red, 3-amino-9-ethylcarbazole (AEC), and 3,3'-diaminobenzidine (DAB). These chromogens were evaluated for staining quality, microdissection efficiency, biomolecular extraction, and evaluation of specific molecular targets. Results: Interestingly, DAB, the most commonly used chromogen, demonstrated a negative impact on the retrieval of biomolecules from immuno-LCM samples. However, chromogens such as Vector Black and Impact Vector Red showed much improved biomolecule extraction compared to DAB even though the yield of microdissected material was comparable. While other chromogens, such as AEC, demonstrated a greater efficiency of biomolecule extraction but showed incomplete immuno-LCM of specific IHC-stained cells. Conclusions: The data indicate that traditional IHC chromogens should be carefully considered when using immuno-LCM to analyze biomolecules. Citation Format: Sarah Laun, Adam Roberge, Robert Weigman, Aubrey Lewis, Valarie Greisman, Meeiyueh Liu, Owen Stephens, Erich Peterson, Ikjae Shin, Michael Emmert-Buck, Michael Tangrea, Donald J. Johann. Towards advanced precision oncology assays - Selection of immunohistochemistry chromogen impacts microdissection and downstream molecular analysis of archival specimens [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2947.

e15571 Background: Improving the utilization of tumor tissue from diagnostic biopsies is an unmet medical need. This is especially relevant today in the rapidly evolving precision oncology field where tumor genotyping is essential for the indication of many advanced and targeted therapies. National Comprehensive Cancer Network (NCCN) guidelines now mandate molecular testing for clinically actionable targets in certain malignancies. Patients diagnosed with advanced non-small cell lung cancer (NSCLC) are commonly of an older age and have significant co-morbidities. This frequently causes clinical dilemmas regarding the ability to obtain adequate amounts of tissue for tumor genotyping. In these cases, the tumor tissue may have been obtained by an image-guided biopsy, and the diagnosis of NSCLC proper determined via cytology. In certain instances, adequate tissue for tumor genotyping and/or a more advanced mutational analysis to identify oncogenic drivers may not be available. Methods: Following pathology review, formalin fixed paraffin embedded (FFPE) specimens were subjected to advanced immuno-based laser capture microdissection (LCM), DNA was extracted and prepped for droplet digital PCR (ddPCR) and run with a series of positive and negative controls. Results: Utilizing advanced stage lung cancer as an example, an improved genotyping approach for solid tumors is possible. The strategy involves optimization of the microdissection process and analysis of a large number of identical target cells from FFPE specimens sharing similar characteristics, in other words, single-cell subtype analysis. The shared characteristics can include immunostaining status, cell phenotype, and/or spatial location within a histological section. Conclusions: Synergy between microdissection and ddPCR enhances the molecular analysis. We demonstrate a methodology that illustrates genotyping of a solid tumor from a small tissue biopsy sample in a time and cost-efficient manner, using immunostain targeting as an example.

Cancers emerge from an on-going Darwinian evolutionary process, often leading to multiple competing subclones within a single primary tumour1-4. This evolutionary process culminates in the formation of metastases, which is the cause of 90% of cancer-related deaths5. However, despite its clinical importance, little is known about the principles governing the dissemination of cancer cells to distant organs. Although the hypothesis that each metastasis originates from a single tumour cell is generally supported6-8, recent studies using mouse models of cancer demonstrated the existence of polyclonal seeding from and inter-clonal cooperation between multiple subclones9,10. In this study, we sought definitive evidence for the existence of polyclonal seeding in human malignancy and to establish the clonal relationship among different metastases in the context of androgen-deprived metastatic prostate cancer. Using whole genome sequencing, we characterised multiple metastases arising from prostate tumours in ten patients. Integrated analyses of subclonal architecture revealed the patterns of metastatic spread in unprecedented detail. Metastasis-to-metastasis spread was found to be common, either through de novo monoclonal seeding of daughter metastases or, in five cases, through the transfer of multiple tumour clones between metastatic sites. Lesions affecting tumour suppressor genes usually occur as single events, whereas mutations in genes involved in androgen receptor signalling commonly involve multiple, convergent events in different metastases. Our results elucidate in detail the complex patterns of metastatic spread and further our understanding of the development of resistance to androgen deprivation therapy in prostate cancer.

Advances in biology are occurring at a breathtaking pace today, from genetic insights facilitated by the Human Genome Project and next generation DNA sequencing technologies, to global nucleic acid and proteomic expression measurement using new high-throughput methods. Less publicized in recent years, yet still the central driver of progress, are the steadily proceeding biological insights gained through tried and true hypothesis-driven investigation into the complex worlds of metabolism, growth, development, and regulation. Certainly, the basic science ecosystem is productive and this portends well for the myriad new applications that will benefit mankind; drugs, vaccines, devices, and related economic growth—or perhaps not—in stark contrast to the generation of fundamental biological knowledge are inefficiencies in applying this information to real-world problems, especially those of the clinic. While investigation hums along at light speed, translation often does not. The good news is that obstacles to progress are tractable. The bad news, however, is that these problems are difficult. The present paper examines translational research from multiple perspectives, beginning with a historical account and proceeding to the current state of the art. Included are descriptions of successes and challenges, along with conjecture on how the field may need to evolve in the future.

Introduction: Clinical applications and research studies routinely utilize immunohistochemistry (IHC) approaches on tissue sections. The aim is to selectively target antigens (proteins) in the cells of a tissue section by exploiting the principle of antibody binding, thus enabling target specificity. The antigen retrieval (AR) process employed at the beginning of most IHC protocols increases epitope availability and improves staining characteristics; however, the procedure can damage nucleic acids, in this case RNA, to an unknown extent. Experimental Procedures: To better understand the effects of AR on RNA quality and quantity, model system samples (lung cancer patient derived xenograft tissue) were subjected to a commonly employed AR method [heat induced epitope retrieval (HIER)] and the effects on RNA were assessed by Qubit, Fragment Analyzer, and digital droplet PCR (ddPCR). The ddPCR experiments were performed following reverse transcriptase (RT) product generation and construction of cDNA, which then served as input to the ddPCR assay. Absolute quantitation of gene expression levels and expressed mutations were evaluated by ddPCR. Data Summary: The results showed that HIER resulted in optimal staining characteristics, but induced significant damage to RNA, producing extensive fragmentation and decreased yields. In general, fragmentation showed an inflection point at ~200 nt transcript length. Variation in the HIER protocol mitigated but did not eliminate the negative effects. Apart from the AR procedure, the IHC process itself also resulted in a significant decreased yield of RNA. Of note, in these experiments DAB chromogen was used exclusively in the IHC process. However, in spite of the observed deleterious effects on RNA, none of the AR methods combined with IHC negatively affected RT product generation and PCR amplification of small amplicons. Regarding the detection of RT product under different conditions, the size of the amplicon was found to make a difference, with the detection of longer amplicons being more difficult. In addition to a number of successful human and mouse gene expression measurements, KRAS gene mutations were successfully identified in the clinical cases under all conditions. Conclusions: The data indicate that RNA recovered from histology slides after standard AR and IHC processing can be successfully employed for genomic applications utilizing RT product formation (cDNA) for gene expression and detection of expressed mutations, especially if the detection methods are based on relatively short length nucleic acids. Studies that require larger RNA fragments such as long-read sequencing should avoid the use of HIER. Citation Format: Donald J. Johann, Meeiyueh Liu, Adam Roberge, Sarah Laun, Michael Emmert-Buck, Michael Tangrea. Effect of antigen retrieval on immuno-based RNA microdissection methods [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1243.

The olfactomedin 4 (OLFM4) gene is located on chromosome 13q14.3, which frequently is deleted in human prostate cancer. However, direct genetic evidence of OLFM4 gene alteration in human prostate cancer has not yet been obtained. In this study, we investigated the genetics, protein expression, and functions of the OLFM4 gene in human prostate cancer. We found overall 25% deletions within the OLFM4 gene in cancerous epithelial cells compared with adjacent normal epithelial cells that were microdissected from 31 prostate cancer specimens using laser-capture microdissection and genomic DNA sequencing. We found 28% to 45% hemizygous and 15% to 57% homozygous deletions of the OLFM4 gene via fluorescence in situ hybridization analysis from 44 different prostate cancer patient samples. Moreover, homozygous deletion of the OLFM4 gene significantly correlated with advanced prostate cancer. By using immunohistochemical analysis of 162 prostate cancer tissue array samples representing a range of Gleason scores, we found that OLFM4 protein expression correlated inversely with advanced prostate cancer, consistent with the genetic results. We also showed that a truncated mutant of OLFM4 that lacks the olfactomedin domain eliminated suppression of PC-3 prostate cancer cell growth. Together, our findings indicate that OLFM4 is a novel candidate tumor-suppressor gene for chromosome 13q and may shed new light on strategies that could be used for the diagnosis, prognosis, and treatment of prostate cancer patients.

Precision medicine promises to enhance patient treatment through the use of emerging molecular technologies, including genomics, transcriptomics, and proteomics. However, current tools in surgical pathology lack the capability to efficiently isolate specific cell populations in complex tissues/tumors, which can confound molecular results. Expression microdissection (xMD) is an immuno-based cell/subcellular isolation tool that procures targets of interest from a cytological or histological specimen. In this study, we demonstrate the accuracy and precision of xMD by rapidly isolating immunostained targets, including cytokeratin AE1/AE3, p53, and estrogen receptor (ER) positive cells and nuclei from tissue sections. Other targets procured included green fluorescent protein (GFP) expressing fibroblasts, in situ hybridization positive Epstein-Barr virus nuclei, and silver stained fungi. In order to assess the effect on molecular data, xMD was utilized to isolate specific targets from a mixed population of cells where the targets constituted only 5% of the sample. Target enrichment from this admixed cell population prior to next-generation sequencing (NGS) produced a minimum 13-fold increase in mutation allele frequency detection. These data suggest a role for xMD in a wide range of molecular pathology studies, as well as in the clinical workflow for samples where tumor cell enrichment is needed, or for those with a relative paucity of target cells.

Previous studies of esophageal squamous cell carcinoma (ESCC) suggested chromosome region 13q12-14 harbors a familial ESCC gene. DNA sequencing of the BRCA2 gene, located on 13q12, showed evidence of both germline and tumor specific alterations but the frequency of changes was low and did not fit the classic Knudsen two-hit gene inactivation model. To further investigate chromosome 13q12-14 in ESCC, quantitative expression measurements were performed on BRCA2 and 11 neighboring genes in matched normal epithelium and tumor from 17 cases. Transcript analysis showed normal levels of five genes, tumor down-regulation of two genes (TNFRS19 and TPT1), and tumor up- regulation of five genes, including BRCA2. No evidence of BRCA2 loss-of-function was detected based on reduced mRNA in tumor cells. Between 13q12.3 (KATNAL1) and 13q12.3-q13 (CCNA1) five adjacent genes showed increased mRNA expression raising the possibility of a DNA amplicon; however, qPCR analysis showed normal DNA amounts in this region. CCNA1 transcript was significantly up-regulated in tumors and was thus further interrogated at the protein level by immunohistochemistry. CCNA1 staining was restricted to normal basal epithelium and was not expressed in more superficial, differentiated regions. In contrast, the CCNA1 protein was ubiquitously and highly expressed throughout tumor foci. Overall, these data from a relatively small number of cases (17) suggest that TNFRS19 and TPT1 deserve further investigation as candidate tumor suppressor genes in esophageal cancer in a larger patient series; BRCA2 mRNA is increased in the tumors, likely as a compensatory response to the marked DNA damage that is present in these lesions; and, CCNA1 was identified as a novel up-regulated gene in ESCC.

This article describes a range of results, from passive magnet design to optimal feedback control of a distributed ferrofluid. Representing magnetic forces as the gradient of a magnetic energy allowed design and demonstration, in animal experiments, of a simple open-loop two-magnet system to inject nanoparticles into the inner ear. Then a petri-dish test bed was used to develop and test optimal closed-loop manipulation of a single ferrofluid droplet.The demonstrated algorithms exploited the quadratic dependence of the magnetic forces on control inputs while accounting for magnet time delays and spatial discontinuities in the optimal control. All dimensional parameters were reduced to three essential nondimensional numbers, and ferrofluid behavior was mapped across the entire feasible drug delivery parameter space.

Objective: In the past decade molecular diagnostics has changed the clinical management of lung adenocarcinoma patients. Molecular diagnostics, however, is largely dependent on the quantity and quality of the tumor DNA that is retrieved from the tissue or cytology samples. Frequently, patients are diagnosed on cytology specimens where the tumor cells are scattered within the cell block, making selecting for tumor enrichment difficult. In the past we have used laser capture microdissection (LCM) to select for pure populations of tumor cells to increase the sensitivity of molecular assays. This study explores several methods for semiautomated computer-guided LCM. Study Design: Hematoxylin and eosin- or TTF-1-immunostained slides from a pleural effusion cell block with metastatic lung adenocarcinoma were used for LCM with either AutoScan or a recently described pattern-matching algorithm, spatially invariant vector quantization (SIVQ), to define morphologic predicates (vectors) to select cells of interest. Results: We retrieved pure populations of tumor cells using both algorithm-guided LCM approaches with slight variations in cellular retrievals. Both methods were semiautomated, requiring minimum technical supervision. Conclusion: In this study we demonstrate the first semiautomated, computer-guided LCM of a cytology specimen using SIVQ and AutoScan, a first step towards the long-term goal of integrating LCM into the clinical cytology-molecular workflow.

Measurement of mRNA levels across tissue samples facilitates an understanding of how genes function and what their roles are in disease. Quantifying low-abundance mRNA requires a workflow that preserves spatial information, isolates RNA, and performs reverse-transcriptase quantitative polymerase chain reaction (RT-qPCR). This is complex because these steps are typically performed in three separate platforms. In the present study, we describe two-dimensional RT-qPCR (2D-RT-qPCR), a method that quantifies RNA across tissues sections in a single integrated platform. The method uses the grid format of a multi-well plate to macrodissect tissue sections and preserve the spatial location of the RNA; this also eliminates the need for physical homogenization of the tissue. A new lysis and nucleic acid purification protocol is performed in the same multi-well plate, followed by RT-qPCR. The feasibility 2D-RT-qPCR was demonstrated on a variety of tissue types. Potential applications of the technology as a high-throughput tissue analysis platform are discussed.