Use of formalin-fixed paraffin-embedded samples for gene expression studies in breast cancer patients

A combination of extracellular matrix- and interferon-associated signatures identifies high-grade breast cancers with poor prognosis

Breast cancer (BC) is a heterogeneous disease in which the tumor microenvironment (TME) seems to impact the clinical outcome. Here, we investigated whether a combination of gene expression signatures relating to both the structural and immune TME aspects can help predict prognosis in women with high‐grade BC (HGBC). Thus, we focused on a combined molecular biomarker variable that involved extracellular matrix (ECM)‐associated gene expression (ECM3 signature) and interferon (IFN)‐associated metagene (IFN metagene) expression. In 97 chemo‐naive HGBCs from the METABRIC dataset, the dichotomous ECM3/IFN (dECIF) variable identified a group of high‐risk patients (ECM3⁺/IFN⁻ vs other; hazard ratio = 3.2, 95% confidence interval: 1.5–6.7). Notably, ECM3⁺/IFN⁻ tumors showed low tumor‐infiltrating lymphocytes, high levels of CD33‐positive cells, absence of PD‐1 expression, or low expression of PD‐L1, as suggested by immune profiles and immune‐histochemical analysis on an independent cohort of 131 HGBCs. To make our results transferable to clinical use, we refined the dECIF biomarker using reduced ECM3 and IFN signatures; notably, the prognostic value of this reduced dECIF was comparable to that of the original dECIF. After validation in a new BC cohort, reduced dECIF was translated into a robust qPCR classifier for real‐world clinical use.

OMICS insights into cancer histology; Metabolomics and proteomics approach

Metabolomics as a post-genomic research area comprising different analytical methods for small molecules analysis. One of the underlying applications of metabolomics technology for better disease diagnosis and prognosis is discovering the metabolic pathway differences between healthy individuals and patients. On the other hand, the other noteworthy applications of metabolomics include its effective role in biomarker screening for cancer detection, monitoring, and prediction. In other words, emerging of the metabolomics field can be hopeful to provide a suitable alternative for the common current cancer diagnostic methods especially histopathological tests. Indeed, cancer as a major global issue places a substantial burden on the health care system. Hence, proper management can be beneficial. In this respect, formalin-fixed paraffin-embedded tissue specimens (in histopathological tests) are considered as a valuable source for metabolomics investigations. Interestingly, formalin-fixed paraffin-embedded tissue specimens can provide informative data for cancer management. In general, using these specimens, determining the cancer stage, individual response to the different therapies, personalized risk prediction are possible and high-quality clinical services are the promise of OMICS technologies for cancer disease. However, considering all of these beneficial characteristics, there are still some limitations in this area that need to be addressed in order to optimize the metabolomics utilizations and advancement.

Establishment of a novel cancer cell line derived from vulvar carcinoma associated with lichen sclerosus exhibiting a fibroblast-dependent tumorigenic potential

Vulvar squamous cell carcinoma associated with lichen sclerosus (VLS-VSCC) are rare tumors but with higher recurrence and worse prognosis than other types of VSCC. Lack of experimental models has limited the search for better understanding of the biology and development of treatment modalities. In this study, we isolated and characterized primary cells from VSCC (n = 7) and normal vulvar tissue adjacent to tumor (n = 7). Detailed characterization of the novel spontaneously immortalized cell line, VCC1 revealed a characteristic epithelial morphology in vitro and a well-differentiated keratinizing SCC histology in vivo, closely resembling the tumor of origin. VCC1 expressed higher levels of epithelial-mesenchymal transition markers and higher clonogenic properties as compared to other established non VLS-VSCC cell lines. In vitro 3D organotypic assays and in vivo xenografts revealed a prominent role of cancer-associated fibroblasts in VCC1 invasion and tumor formation. In conclusion, VCC1 mirrored several major VLS-VSCC features and provided a robust experimental tool for further elucidation of VLS-related oncogenesis and drug testing.

Biotinylated amplicon sequencing: A method for preserving DNA samples of limited quantity

Background

Genomic testing is often limited by the exhaustible nature of human tissue and blood samples. Here we describe biotinylated amplicon sequencing (BAmSeq), a method that allows for the creation of PCR amplicon based next-generation sequencing (NGS) libraries while retaining the original source DNA.

Design and methods

Biotinylated primers for different loci were designed to create NGS libraries using human genomic DNA from cell lines, plasma, and formalin-fixed paraffin embedded (FFPE) tissues using the BAmSeq protocol. DNA from the original template used for each BAmSeq library was recovered after separation with streptavidin magnetic beads. The recovered DNA was then used for end-point, quantitative and droplet digital PCR (ddPCR) as well as NGS using a cancer gene panel.

Results

Recovered DNA was analyzed and compared to the original DNA after one or two rounds of BAmSeq. Recovered DNA revealed comparable genomic distributions and mutational allelic frequencies when compared to original source DNA. Sufficient quantities of recovered DNA after BAmSeq were obtained, allowing for additional downstream applications.

Conclusions

We demonstrate that BAmSeq allows original DNA template to be recovered with comparable quality and quantity to the source DNA. This recovered DNA is suitable for many downstream applications and may prevent sample exhaustion, especially when DNA quantity or source material is limiting.

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Modification of targeted panel sequencing allows for recovery of original DNA template.

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Protocol provides value in the setting of scarce DNA template.

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Recovered DNA is suitable for NGS, ddPCR and qPCR.

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Recovered DNA shows no loss of genomic regions.

Potential Value of Qiagen and PrepIT•MAX Kits in Extraction of Mycobacterial DNA From Presumptive Tuberculosis Archived Formalin-Fixed Paraffin-Embedded Tissues

BACKGROUND

DNA analysis has potential for screening for and diagnosing a variety of conditions as well as the characterization of various pathogens for many purposes including to identify genetic disorders and mutations, study genetic diversity, and establish evolutional trends.

METHODS

Our study compared the performance of 2 DNA extraction kits: Qiagen and prepIT•MAX. The study tested 160 formalin-fixed paraffin-embedded (FFPE) human tissue samples that had been collected at Muhimbili National Hospital (MNH) between 2010 and 2016. For each sample, DNA extraction was performed using both the Qiagen and prepIT•MAX kits followed by polymerase chain reaction (PCR) tests to target the RNA polymerase gene and gel electrophoresis.

RESULTS

The findings showed that the Qiagen was 3 times superior to the prepIT•MAX kit in successfully extracting mycobacterial DNA from presumptive tuberculosis (TB) FFPE tissues. Of the 160 previously Ziehl-Neelsen stain-negative Mycobacterium tuberculosis suspicious tissue samples, 12 (7.5%) tested positive with the PCR. Of the 12 PCR-detected positive samples, 8 (66.7%) yielded positive results with the Qiagen kit only and 4 (33.3%) yielded positive results with both Qiagen and prepIT•MAX kits. Additionally, 10 (83.3%) came from well-formed granuloma, 1 (8%) from caseous necrosis, and 1 (8.3%) Langhans-type giant cells endorsing their potential for housing infection such as TB adenitis.

CONCLUSIONS

A combination of molecular techniques, microscopy, and pathological features increases detection of M. tuberculosis from FFPE tissues. Both the Qiagen and the prepIT•MAX DNA extraction kits have shown a remarkable capability for extracting DNA from M. tuberculosis, although examination of FFPE tissues is not an intended use for the prepIT MAX, according to the manufacturer. In resource-limited countries, however, these kits may complement each other. We recommend further studies for validation and optimization, which includes the cost effectiveness of prepIT•MAX extraction kit to advocate for its use in extraction of mycobacterial DNA from FFPE tissues.

Brain Metastasis Prediction by Transcriptomic Profiling in Triple-Negative Breast Cancer

BACKGROUND

Triple-negative breast cancer (TNBC) lacks expression of steroid hormone receptors (estrogen receptor α and progesterone) and epidermal growth factor receptor type 2. This phenotype shows high metastatic potential, with particular predilection to lungs and brain. Determination of TNBC transcriptomic profiles associated with high risk of brain metastasis (BM) might identify patients requiring alternative, more aggressive, or specific preventive and therapeutic approaches.

PATIENTS AND METHODS

Using a cDNA-mediated annealing, selection, extension, and ligation assay, we investigated expression of 29,369 gene transcripts in primary TNBC tumor samples from 119 patients-71 in discovery cohort A and 48 in independent cohort B-that included best discriminating genes. Expression of mRNA was correlated with the occurrence of symptomatic BM.

RESULTS

In cohort A, the difference at the noncorrected P < .005 was found for 64 transcripts (P = .23 for global test), but none showed significant difference at a preset level of false-discovery rate of < 10%. Of the 30 transcripts with the largest differences between patients with and without BM in cohort A, none was significantly associated with BM in cohort B.

CONCLUSION

Analysis based on the primary tumor gene transcripts alone is unlikely to predict BM development in advanced TNBC. Despite its negative findings, the study adds to the knowledge on the biology of TNBC and paves the way for future projects using more advanced molecular assays.

Subtype-Specific Metagene-Based Prediction of Outcome after Neoadjuvant and Adjuvant Treatment in Breast Cancer

PURPOSE

In spite of improvements of average benefit from adjuvant/neoadjuvant treatments, there are still individual patients with early breast cancer at high risk of relapse. We explored the association with outcome of robust gene cluster-based metagenes linked to proliferation, ER-related genes, and immune response to identify those high-risk patients.

EXPERIMENTAL DESIGN

A total of 3,847 publicly available gene-expression profiles were analyzed (untreated, N = 826; tamoxifen-treated, N = 685; chemotherapy-treated, N = 1,150). Genes poorly performing in formalin-fixed samples were removed. Outcomes of interest were pathologic-complete response (pCR) and distant metastasis-free survival (DMFS). In ER(+)HER2(-), the proliferation and ER-related metagenes were combined to define three risk groups. In HER2(+) and ER(-)HER2(-) risk groups were defined by tertiles of an immune-related metagene.

RESULTS

The high-proliferation/low-ER group of ER(+)HER2(-) breast cancer had significantly higher pCR rate [OR, 5.01 (1.76-17.99), P = 0.005], but poorer outcome [HR = 3.73 (1.63-8.51), P = 0.0018] than the low-proliferation/high-ER. A similar association with outcome applied to patients with residual disease (RD) after neoadjuvant chemotherapy (P = 0.01). In ER(-)HER2(-) and HER2(+) breast cancer, immune metagene in the high tertile was linked to higher pCR [33.7% vs. 11.6% in high and low tertile, respectively; OR, 3.87 (1.79-8.95); P = 0.0009]. In ER(-)HER2(-), after adjuvant/neoadjuvant chemotherapy, 5-year DMFS was 85.4% for high-tertile immune metagene, and 43.9% for low tertile. The outcome association was similar in patients with RD (P = 0.0055). In HER2(+) breast cancer treated with chemotherapy the association with risk of relapse was not significant.

CONCLUSIONS

We developed metagene-based predictors able to define low and high risk of relapse after adjuvant/neoadjuvant therapy. High-risk patients so defined should be preferably considered for trials with investigational agents.

Genomic signatures for paclitaxel and gemcitabine resistance in breast cancer derived by machine learning

Increasingly, the effectiveness of adjuvant chemotherapy agents for breast cancer has been related to changes in the genomic profile of tumors. We investigated correspondence between growth inhibitory concentrations of paclitaxel and gemcitabine (GI50) and gene copy number, mutation, and expression first in breast cancer cell lines and then in patients. Genes encoding direct targets of these drugs, metabolizing enzymes, transporters, and those previously associated with chemoresistance to paclitaxel (n = 31 genes) or gemcitabine (n = 18) were analyzed. A multi-factorial, principal component analysis (MFA) indicated expression was the strongest indicator of sensitivity for paclitaxel, and copy number and expression were informative for gemcitabine. The factors were combined using support vector machines (SVM). Expression of 15 genes (ABCC10, BCL2, BCL2L1, BIRC5, BMF, FGF2, FN1, MAP4, MAPT, NFKB2, SLCO1B3, TLR6, TMEM243, TWIST1, and CSAG2) predicted cell line sensitivity to paclitaxel with 82% accuracy. Copy number profiles of 3 genes (ABCC10, NT5C, TYMS) together with expression of 7 genes (ABCB1, ABCC10, CMPK1, DCTD, NME1, RRM1, RRM2B), predicted gemcitabine response with 85% accuracy. Expression and copy number studies of two independent sets of patients with known responses were then analyzed with these models. These included tumor blocks from 21 patients that were treated with both paclitaxel and gemcitabine, and 319 patients on paclitaxel and anthracycline therapy. A new paclitaxel SVM was derived from an 11-gene subset since data for 4 of the original genes was unavailable. The accuracy of this SVM was similar in cell lines and tumor blocks (70-71%). The gemcitabine SVM exhibited 62% prediction accuracy for the tumor blocks due to the presence of samples with poor nucleic acid integrity. Nevertheless, the paclitaxel SVM predicted sensitivity in 84% of patients with no or minimal residual disease.