Genomic aberrations in normal tissue adjacent to HER2-amplified breast cancers: field cancerization or contaminating tumor cells?

Field cancerization effects as well as isolated tumor cell foci extending well beyond the invasive tumor margin have been described previously to account for local recurrence rates following breast conserving surgery despite adequate surgical margins and breast radiotherapy. To look for evidence of possible tumor cell contamination or field cancerization by genetic effects, a pilot study (Study 1: 12 sample pairs) followed by a verification study (Study 2: 20 sample pairs) were performed on DNA extracted from HER2-positive breast tumors and matching normal adjacent mammary tissue samples excised 1-3 cm beyond the invasive tumor margin. High-resolution molecular inversion probe (MIP) arrays were used to compare genomic copy number variations, including increased HER2 gene copies, between the paired samples; as well, a detailed histologic and immunohistochemical (IHC) re-evaluation of all Study 2 samples was performed blinded to the genomic results to characterize the adjacent normal tissue composition bracketing the DNA-extracted samples. Overall, 14/32 (44 %) sample pairs from both studies produced genome-wide evidence of genetic aberrations including HER2 copy number gains within the adjacent normal tissue samples. The observed single-parental origin of monoallelic HER2 amplicon haplotypes shared by informative tumor-normal pairs, as well as commonly gained loci elsewhere on 17q, suggested the presence of contaminating tumor cells in the genomically aberrant normal samples. Histologic and IHC analyses identified occult 25-200 μm tumor cell clusters overexpressing HER2 scattered in more than half, but not all, of the genomically aberrant normal samples re-evaluated, but in none of the genomically normal samples. These genomic and microscopic findings support the conclusion that tumor cell contamination rather than genetic field cancerization represents the likeliest cause of local clinical recurrence rates following breast conserving surgery, and mandate caution in assuming the genomic normalcy of histologically benign appearing peritumor breast tissue

Evaluating the miR-302b and miR-145 expression in formalin-fixed paraffin-embedded samples of esophageal squamous cell carcinoma

Background: MicroRNAs are involved in key cellular processes regulating, and their misregulation is linked to cancer. The miR-302-367 cluster is exclusively expressed in embryonic stem and carcinoma cells. This cluster also promotes cell reprogramming and stemness process. In contrast, miR-145 is mostly regarded as a tumor suppressor, where it regulates cellular functions such as cell division, differentiation, and apoptosis. By suppressing the main pluripotency factors (OCT4, SOX2, MYC and KLF4), miR-145 silences the self-renewal program in ESCs. Therefore, the main aim of this study is to find a potential link between the expression level of hsa-miR-302b and hsa-miR-145 with tumor vs. non-tumor as well as high-grade vs. low-grade states of the esophageal tissue samples. Methods: A total number of 40 formalin-fixed, paraffin-embedded (FFPE) samples of esophageal squamous-cell carcinoma (ESCC) were obtained, and the tumor and marginal non-tumor areas delineated and punched off by an expert pathologist. Total RNA was extracted with Trizol, and cDNA synthesized using the miRCURY LNA™ Universal RT microRNA PCR Kit. Real-time reverse transcription polymerase chain reaction (RT-PCR) assays were performed using specific LNA-primers and SYBR Green master mix. Results: The expression level of miR-302b failed to show any significant difference, neither between tumor and their non-tumor counterparts, nor among tumors with different grades of malignancies (P > 0.05). In contrast, miR-145 was significantly down regulated in all grades of tumor samples (P 0.05). CONCLUSION: Our data revealed a significant down-regulation of miR-145 in ESCC tissue samples. Based on our ROC curve analysis data (AUC = 0.74, P < 0.001) miR-145 could be regarded as a potential tumor marker for diagnosis of esophageal cancer. © 2015, Academy of Medical Sciences of I.R. Iran. All rights reserved

Use of archival versus newly collected tumor samples for assessing PD-L1 expression and overall survival : an updated analysis of KEYNOTE-010 trial

Background: In KEYNOTE-010, pembrolizumab versus docetaxel improved overall survival (OS) in patients with programmed death-1 protein (PD)-L1-positive advanced non-small-cell lung cancer (NSCLC). A prespecified exploratory analysis compared outcomes in patients based on PD-L1 expression in archival versus newly collected tumor samples using recently updated survival data. Patients and methods: PD-L1 was assessed centrally by immunohistochemistry (22C3 antibody) in archival or newly collected tumor samples. Patients received pembrolizumab 2 or 10 mg/kg Q3W or docetaxel 75 mg/m2 Q3W for 24 months or until progression/intolerable toxicity/other reason. Response was assessed by RECIST v1.1 every 9 weeks, survival every 2 months. Primary end points were OS and progression-free survival (PFS) in tumor proportion score (TPS) 50% and 1%; pembrolizumab doses were pooled in this analysis. Results: At date cut-off of 24 March 2017, median follow-up was 31 months (range 23-41) representing 18 additional months of follow-up from the primary analysis. Pembrolizumab versus docetaxel continued to improve OS in patients with previously treated, PD-L1-expressing advanced NSCLC; hazard ratio (HR) was 0.66 [95% confidence interval (CI): 0.57, 0.77]. Of 1033 patients analyzed, 455(44%) were enrolled based on archival samples and 578 (56%) on newly collected tumor samples. Approximately 40% of archival samples and 45% of newly collected tumor samples were PD-L1 TPS 50%. For TPS 50%, the OS HRs were 0.64 (95% CI: 0.45, 0.91) and 0.40 (95% CI: 0.28, 0.56) for archival and newly collected samples, respectively. In patients with TPS 1%, OS HRs were 0.74 (95% CI: 0.59, 0.93) and 0.59 (95% CI: 0.48, 0.73) for archival and newly collected samples, respectively. In TPS 50%, PFS HRs were similar across archival [0.63 (95% CI: 0.45, 0.89)] and newly collected samples [0.53 (95% CI: 0.38, 0.72)]. In patients with TPS 1%, PFS HRs were similar across archival [0.82 (95% CI: 0.66, 1.02)] and newly collected samples [0.83 (95% CI: 0.68, 1.02)]. Conclusion: Pembrolizumab continued to improve OS over docetaxel in intention to treat population and in subsets of patients with newly collected and archival samples

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

The Molecular In Silico Dissection of Cancer using TCLASS and its Application in the Identification of the Tissue of Origin of &#xb;Cancers of Unknown Primary Site&#xb;

Traditional cancer diagnosis relies on a combination of clinical and histo-pathological data. In many cases, however, the morphology of in particular metastatic cancer is not discriminative enough for correct diagnosis. In addition, the morphology of tumor cells do not provide information on aberrant molecular pathways that may be used to specifically target the tumor like the application of Herceptin to breast cancers with amplification in the ERBB2 gene. With the completion of the human genome project, molecular pathology has dramatically increased its arsenal of novel molecular biomarkers that can be used to determine the phenotype of tumors. Gene expression profiling using high-density microarray technology is an extremely powerful tool to comprehensively characterize the tumor phenotype. We have developed TCLASS&#xae; a multi-class tumor classifier that interprets gene expression microarray data and allows the identification of the primary site of Cancers of Unknown Promary site (CUP). The classifier is implemented as a web-based tool and is an extremely simple and straightforward approach for molecular characterization of tumor samples. We are currently looking for collaborations with clinicians with access to fresh frozen CUP samples to further validate the tool in a clinical context. Alternatively, CEL files of CUP samples analyzed with Affynetrix 133 Plus 2.0 arrays can also be directly analyzed using TCLASS.&#xd;&#xa

Bortezomib Augments Natural Killer Cell Targeting of Stem-Like Tumor Cells.

Tumor cells harboring stem-like/cancer stem cell (CSC) properties have been identified and isolated from numerous hematological and solid malignancies. These stem-like tumor cells can persist following conventional cytoreductive therapies, such as chemotherapy and radiotherapy, thereby repopulating the tumor and seeding relapse and/or metastasis. We have previously shown that natural killer (NK) cells preferentially target stem-like tumor cells via non- major histocompatibility complex (MHC) restricted mechanisms. Here, we demonstrated that the proteasome inhibitor, bortezomib, augments NK cell targeting of stem cell-like tumor cells against multiple solid human tumor-derived cancer lines and primary tissue samples. Mechanistically, this was mediated by the upregulation of cell surface NK ligands MHC class I chain-related protein A and B (MICA and MICB) on aldehyde dehydrogenases (ALDH)-positive CSCs. The increased expression of MICA and MICB on CSC targets thereby enhanced NK cell mediated killing in vitro and ex vivo from both human primary tumor and patient-derived xenograft samples. In vivo, the combination of bortezomib and allogeneic NK cell adoptive transfer in immunodeficient mice led to increased elimination of CSCs as well as tumor growth delay of orthotopic glioblastoma tumors. Taken together, our data support the combination bortezomib and NK transfer as a strategy for both CSC targeting and potentially improved outcomes in clinical cancer patients

The importance of circulating tumor products as „liquid biopsies” in colorectal cancer

Liquid biopsies represent an array of plasma analysis tests that are studied to evaluate and identify circulating tumor products, especially circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA). Examining such biomarkers in the plasma of colorectal cancer patients has attracted attention due to its clinical significance in the treatment of malignant diseases. Given that tissue samples are sometimes challenging to procure or unsatisfactory for genomic profiling from patients with colorectal cancer, trustworthy biomarkers are mandatory for guiding treatment, monitoring therapeutic response, and detecting recurrence. This review considers the relevance of flowing tumor products like circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), circulating messenger RNA (mRNA), circulating micro RNA (miRNA), circulating exosomes, and tumor educated platelets (TEPs) for patients with colorectal cancer

Pathway relevance ranking for tumor samples through network-based data integration

The study of cancer, a highly heterogeneous disease with different causes and clinical outcomes, requires a multi-angle approach and the collection of large multi-omics datasets that, ideally, should be analyzed simultaneously. We present a new pathway relevance ranking method that is able to prioritize pathways according to the information contained in any combination of tumor related omics datasets. Key to the method is the conversion of all available data into a single comprehensive network representation containing not only genes but also individual patient samples. Additionally, all data are linked through a network of previously identified molecular interactions. We demonstrate the performance of the new method by applying it to breast and ovarian cancer datasets from The Cancer Genome Atlas. By integrating gene expression, copy number, mutation and methylation data, the method's potential to identify key pathways involved in breast cancer development shared by different molecular subtypes is illustrated. Interestingly, certain pathways were ranked equally important for different subtypes, even when the underlying (epi)-genetic disturbances were diverse. Next to prioritizing universally high-scoring pathways, the pathway ranking method was able to identify subtype-specific pathways. Often the score of a pathway could not be motivated by a single mutation, copy number or methylation alteration, but rather by a combination of genetic and epi-genetic disturbances, stressing the need for a network-based data integration approach. The analysis of ovarian tumors, as a function of survival-based subtypes, demonstrated the method's ability to correctly identify key pathways, irrespective of tumor subtype. A differential analysis of survival-based subtypes revealed several pathways with higher importance for the bad-outcome patient group than for the good-outcome patient group. Many of the pathways exhibiting higher importance for the bad-outcome patient group could be related to ovarian tumor proliferation and survival