Large scale, robust, and accurate whole transcriptome profiling from clinical formalin-fixed paraffin-embedded samples

RNA Sequencing in Disease Diagnosis

RNA sequencing (RNA-seq) enables the accurate measurement of multiple transcriptomic phenotypes for modeling the impacts of disease variants. Advances in technologies, experimental protocols, and analysis strategies are rapidly expanding the application of RNA-seq to identify disease biomarkers, tissue- and cell-type-specific impacts, and the spatial localization of disease-associated mechanisms. Ongoing international efforts to construct biobank-scale transcriptomic repositories with matched genomic data across diverse population groups are further increasing the utility of RNA-seq approaches by providing large-scale normative reference resources. The availability of these resources, combined with improved computational analysis pipelines, has enabled the detection of aberrant transcriptomic phenotypes underlying rare diseases. Further expansion of these resources, across both somatic and developmental tissues, is expected to soon provide unprecedented insights to resolve disease origin, mechanism of action, and causal gene contributions, suggesting the continued high utility of RNA-seq in disease diagnosis.

LINCATRA: Two-cycle method to amplify RNA for transcriptome analysis from formalin-fixed paraffin-embedded tissue

Whole transcriptome analysis (WTA) using RNA extracted from Formalin Fixed Paraffin Embedded (FFPE) tissue is an invaluable tool to understand the molecular pathology of disease. RNA extracted from FFPE tissue is either degraded and/or in very low quantities hampering gene expression analysis. Earlier studies described protocols applied for cellular RNA using poly-A primer-based linear amplification. The current study describes a method, LINCATRA (LINear amplifiCAtion of RNA for whole TRAnscriptome analysis). It employs random nonamer primer based method which can amplify short, fragmented RNA with high fidelity from as low as 5 ng to obtain enough material for WTA. The two-cycle method significantly amplified RNA at ∼1000 folds (p < 0.0001) improving the mean read lengths (p < 0.05) in WTA. Overall, increased mean read length positively correlated with on-target reads (Pearson's r = 0.71, p < 0.0001) in both amplified and unamplified RNA-seq analysis. Gene expression analysis compared between unamplified and amplified group displayed substantial overlap of the differentially expressed genes (DEGs) (log2 fold change cut-off < -2 and >2, p < 0.05) identified between lung cancer and asthma cohorts validating the method developed. This method is applicable in clinical molecular pathology field for both diagnostics and elucidation of disease mechanisms.

snRNAs from Radical Prostatectomy Specimens Have the Potential to Serve as Prognostic Factors for Clinical Recurrence after Biochemical Recurrence in Patients with High-Risk Prostate Cancer

In patients with high-risk prostate cancer (HRPC) after radical prostatectomy (RP), biochemical recurrence (BCR) increases the risk of distant metastasis. Accordingly, additional prognostic biomarkers are required to identify the subpopulation of patients with HRPC who develop clinical recurrence (CR) after BCR. The objective of this study was to identify biomarkers in formalin-fixed paraffin-embedded (FFPE) RP samples that are prognostic for CR in patients with HRPC who experience BCR after RP (post-RP BCR). First, we performed a preliminary RNA sequencing analysis to comprehensively profile RNA expression in FFPE RP samples obtained from patients with HRPC who developed CR after post-RP BCR and found that many snRNAs were very abundant in preserved FFPE samples. Subsequently, we used quantitative polymerase chain reaction (qPCR) to compare the expression levels of highly abundant snRNAs in FFPE RP samples from patients with HRPC with and without CR after post-RP BCR (21 CR patients and 46 non-CR patients who had more than 5 years of follow-up after BCR). The qPCR analysis revealed that the expression levels of snRNA RNU1-1/1-2 and RNU4-1 were significantly higher in patients with CR than in patients without CR. These snRNAs were significantly correlated with clinical recurrence-free survival (RFS) in patients with HRPC who experienced post-RP BCR. Furthermore, snRNA RNU1-1/1-2 could serve as an independent prognostic factor for clinical RFS in post-RP BCR of HRPC cases where known prognostic factors (e.g., Gleason score) cannot distinguish between CR and non-CR patients. Our findings provide new insights into the involvement of snRNAs in prostate cancer progression.

Procrustes is a machine-learning approach that removes cross-platform batch effects from clinical RNA sequencing data

With the increased use of gene expression profiling for personalized oncology, optimized RNA sequencing (RNA-seq) protocols and algorithms are necessary to provide comparable expression measurements between exome capture (EC)-based and poly-A RNA-seq. Here, we developed and optimized an EC-based protocol for processing formalin-fixed, paraffin-embedded samples and a machine-learning algorithm, Procrustes, to overcome batch effects across RNA-seq data obtained using different sample preparation protocols like EC-based or poly-A RNA-seq protocols. Applying Procrustes to samples processed using EC and poly-A RNA-seq protocols showed the expression of 61% of genes (N = 20,062) to correlate across both protocols (concordance correlation coefficient > 0.8, versus 26% before transformation by Procrustes), including 84% of cancer-specific and cancer microenvironment-related genes (versus 36% before applying Procrustes; N = 1,438). Benchmarking analyses also showed Procrustes to outperform other batch correction methods. Finally, we showed that Procrustes can project RNA-seq data for a single sample to a larger cohort of RNA-seq data. Future application of Procrustes will enable direct gene expression analysis for single tumor samples to support gene expression-based treatment decisions.

Review of Molecular Technologies for Investigating Canine Cancer

Genetic molecular testing is starting to gain traction as part of standard clinical practice for dogs with cancer due to its multi-faceted benefits, such as potentially being able to provide diagnostic, prognostic and/or therapeutic information. However, the benefits and ultimate success of genomic analysis in the clinical setting are reliant on the robustness of the tools used to generate the results, which continually expand as new technologies are developed. To this end, we review the different materials from which tumour cells, DNA, RNA and the relevant proteins can be isolated and what methods are available for interrogating their molecular profile, including analysis of the genetic alterations (both somatic and germline), transcriptional changes and epigenetic modifications (including DNA methylation/acetylation and microRNAs). We also look to the future and the tools that are currently being developed, such as using artificial intelligence (AI) to identify genetic mutations from histomorphological criteria. In summary, we find that the molecular genetic characterisation of canine neoplasms has made a promising start. As we understand more of the genetics underlying these tumours and more targeted therapies become available, it will no doubt become a mainstay in the delivery of precision veterinary care to dogs with cancer.

Archival skin biopsy specimens as a tool for miRNA-based diagnosis: Technical and post-analytical considerations

Archived specimens, taken by standardized procedures in clinical practice, represent a valuable resource in translational medicine. Their use in retrospective molecular-based studies could provide disease and therapy predictors. Microfluidic array is a user-friendly and cost-effective method allowing profiling of hundreds of microRNAs (miRNAs) from a low amount of RNA. However, even though tissue miRNAs may include potentially robust biomarkers, non-uniformed post-analytical pipelines could hinder translation into clinics. In this study, epidermal RNA from archival skin biopsy specimens was isolated from patients with peripheral neuropathy and healthy individuals. Unbiased miRNA profiling was performed using RT-qPCR-based microfluidic array. We demonstrated that RNA obtained from archival tissue is appropriate for miRNA profiling, providing evidence that different practices in threshold selection could significantly influence the final results. We showed the utility of software-based quality control for amplification curves. We revealed that selection of the most stable reference and the calculation of geometric mean are suitable when utilizing microfluidic arrays without known references. By applying appropriate post-analytical settings, we obtained miRNA profile of human epidermis associated with biological processes and a list of suitable references. Our results, which outline technical and post-analytical considerations, support the broad use of archived specimens for miRNA analysis to unravel disease-specific molecular signatures.

A Genomic Analysis of Esophageal Squamous Cell Carcinoma in Eastern Africa

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) comprises 90% of all esophageal cancer cases globally and is the most common histology in low-resource settings. Eastern Africa has a disproportionately high incidence of ESCC.

METHODS

We describe the genomic profiles of 61 ESCC cases from Tanzania and compare them to profiles from an existing cohort of ESCC cases from Malawi. We also provide a comparison to ESCC tumors in The Cancer Genome Atlas (TCGA).

RESULTS

We observed substantial transcriptional overlap with other squamous histologies via comparison with TCGA PanCan dataset. DNA analysis revealed known mutational patterns, both genome-wide as well as in genes known to be commonly mutated in ESCC. TP53 mutations were the most common somatic mutation in tumors from both Tanzania and Malawi but were detected at lower frequencies than previously reported in ESCC cases from other settings. In a combined analysis, two unique transcriptional clusters were identified: a proliferative/epithelial cluster and an invasive/migrative/mesenchymal cluster. Mutational signature analysis of the Tanzanian cohort revealed common signatures associated with aging and cytidine deaminase activity (APOBEC) and an absence of signature 29, which was previously reported in the Malawi cohort.

CONCLUSIONS

This study defines the molecular characteristics of ESCC in Tanzania, and enriches the Eastern African dataset, with findings of overall similarities but also some heterogeneity across two unique sites.

IMPACT

Despite a high burden of ESCC in Eastern Africa, investigations into the genomics in this region are nascent. This represents the largest comprehensive genomic analysis ESCC from sub-Saharan Africa to date.

Cost-Efficient Detection of NTRK1/2/3 Gene Fusions: Single-Center Analysis of 8075 Tumor Samples

The majority of NTRK1, NTRK2, and NTRK3 rearrangements result in increased expression of the kinase portion of the involved gene due to its fusion to an actively transcribed gene partner. Consequently, the analysis of 5'/3'-end expression imbalances is potentially capable of detecting the entire spectrum of NTRK gene fusions. Archival tumor specimens obtained from 8075 patients were subjected to manual dissection of tumor cells, DNA/RNA isolation, and cDNA synthesis. The 5'/3'-end expression imbalances in NTRK genes were analyzed by real-time PCR. Further identification of gene rearrangements was performed by variant-specific PCR for 44 common NTRK fusions, and, whenever necessary, by RNA-based next-generation sequencing (NGS). cDNA of sufficient quality was obtained in 7424/8075 (91.9%) tumors. NTRK rearrangements were detected in 7/6436 (0.1%) lung carcinomas, 11/137 (8.0%) pediatric tumors, and 13/851 (1.5%) adult non-lung malignancies. The highest incidence of NTRK translocations was observed in pediatric sarcomas (7/39, 17.9%). Increased frequency of NTRK fusions was seen in microsatellite-unstable colorectal tumors (6/48, 12.5%), salivary gland carcinomas (5/93, 5.4%), and sarcomas (7/143, 4.9%). None of the 1293 lung carcinomas with driver alterations in EGFR/ALK/ROS1/RET/MET oncogenes had NTRK 5'/3'-end expression imbalances. Variant-specific PCR was performed for 744 tumors with a normal 5'/3'-end expression ratio: there were no rearrangements in 172 EGFR/ALK/ROS1/RET/MET-negative lung cancers and 125 pediatric tumors, while NTRK3 fusions were detected in 2/447 (0.5%) non-lung adult malignancies. In conclusion, this study describes a diagnostic pipeline that can be used as a cost-efficient alternative to conventional methods of NTRK1-3 analysis.

Inferred Immune-Cell Activity Is an Independent Predictor of HER2-Negative Breast Cancer Prognosis and Response to Paclitaxel-Based Therapy in the GeparSepto Trial

PURPOSE

Tumor microenvironment (TME) immune markers have been correlated with both response to neoadjuvant therapy and prognosis in patients with breast cancer. Here, immune-cell activity of breast cancer tumors was inferred by expression-based analysis to determine if it is prognostic and/or predictive of response to neoadjuvant paclitaxel-based therapy in the GeparSepto (G7) trial (NCT01583426).

EXPERIMENTAL DESIGN

Pre-study biopsies from 279 patients with HER2-negative breast cancer in the G7 trial underwent RNA-seq-based profiling of 104 immune-cell-specific genes to assess inferred Immune Cell Activity (iICA) of 23 immune-cell types. Hierarchical clustering was used to classify tumors as iICA "hot," "warm," or "cold" by comparison of iICA in the G7 cohort relative to that of 1,467 samples from a tumor database established by Nantomics LLC. Correlations between iICA cluster, pathology-assessed tumor-infiltrating lymphocytes (TIL), and hormone receptor (HR) status for pathologic complete response (pCR), disease-free survival (DFS), and overall survival (OS) were determined.

RESULTS

iICA cluster correlated with TIL levels. The highest pCR rates were observed in hot cluster tumors, and those with relatively higher TILs. Greater inferred activity of several T-cell types was significantly associated with pCR and survival. DFS and OS were prolonged in patients with hot or warm cluster tumors, the latter particularly for HR negative tumors, even if TILs were relatively low.

CONCLUSIONS

Overall, TIL level better predicted pCR, but iICA cluster better predicted survival. Differences in associations between TILs, cluster, pCR, and survival were observed for HR-positive tumors versus HR-negative tumors, suggesting expanded study of the implication of these findings is warranted.

Test of the FlashFREEZE unit in tissue samples freezing for biobanking purposes

Availability of molecularly intact biospecimens is essential in genetic diagnostics to obtain credible results. Integrity of nucleic acids (particularly RNA) may be compromised at various steps of tissue handling, and affected by factors such as time to freeze, freezing technique and storing temperature. At the same time, freezing and storing of the biological material should be feasible and safe for the operator. Here, we compared quality of DNA and RNA from biospecimens derived from different organs (breast, colon, adrenal glands, testes, rectum and uterus) frozen either using dry ice-cooled isopentane or with FlashFREEZE unit, in order to verify if the latter is suitable for routine use in biobanking. Implementing FlashFREEZE device would enable us to limit the use of isopentane, which is potentially toxic and environmentally harmful, whilst facilitate standardization of sample freezing time. We considered factors such RNA and DNA yield and purity. Furthermore, RNA integrity and RNA/DNA performance in routine analyses, such as qPCR, next generation sequencing or microarray, were also assessed. Our results indicate that freezing of tissue samples either with FlashFREEZE unit or isopentane ensures biological material with comparable expression profiles and DNA mutation status, indicating that RNA and DNA of similar quality can be extracted from both. Therefore, our findings support the use of the FlashFREEZE device in routine use for biobanking purposes.

Reproducible and sensitive micro-tissue RNA sequencing from formalin-fixed paraffin-embedded tissues for spatial gene expression analysis

Spatial transcriptome analysis of formalin-fixed paraffin-embedded (FFPE) tissues using RNA-sequencing (RNA-seq) provides interactive information on morphology and gene expression, which is useful for clinical applications. However, despite the advantages of long-term storage at room temperature, FFPE tissues may be severely damaged by methylene crosslinking and provide less gene information than fresh-frozen tissues. In this study, we proposed a sensitive FFPE micro-tissue RNA-seq method that combines the punching of tissue sections (diameter: 100 μm) and the direct construction of RNA-seq libraries. We evaluated a method using mouse liver tissues at two years after fixation and embedding and detected approximately 7000 genes in micro-punched tissue-spots (thickness: 10 μm), similar to that detected with purified total RNA (2.5 ng) equivalent to the several dozen cells in the spot. We applied this method to clinical FFPE specimens of lung cancer that had been fixed and embedded 6 years prior, and found that it was possible to determine characteristic gene expression in the microenvironment containing tumor and non-tumor cells of different morphologies. This result indicates that spatial gene expression analysis of the tumor microenvironment is feasible using FFPE tissue sections stored for extensive periods in medical facilities.

Precise reconstruction of the TME using bulk RNA-seq and a machine learning algorithm trained on artificial transcriptomes

Cellular deconvolution algorithms virtually reconstruct tissue composition by analyzing the gene expression of complex tissues. We present the decision tree machine learning algorithm, Kassandra, trained on a broad collection of >9,400 tissue and blood sorted cell RNA profiles incorporated into millions of artificial transcriptomes to accurately reconstruct the tumor microenvironment (TME). Bioinformatics correction for technical and biological variability, aberrant cancer cell expression inclusion, and accurate quantification and normalization of transcript expression increased Kassandra stability and robustness. Performance was validated on 4,000 H&E slides and 1,000 tissues by comparison with cytometric, immunohistochemical, or single-cell RNA-seq measurements. Kassandra accurately deconvolved TME elements, showing the role of these populations in tumor pathogenesis and other biological processes. Digital TME reconstruction revealed that the presence of PD-1-positive CD8⁺ T cells strongly correlated with immunotherapy response and increased the predictive potential of established biomarkers, indicating that Kassandra could potentially be utilized in future clinical applications.

Genes expressed at low levels raise false discovery rates in RNA samples contaminated with genomic DNA

Background

RNA preparations contaminated with genomic DNA (gDNA) are frequently disregarded by RNA-seq studies. Such contamination may generate false results; however, their effect on the outcomes of RNA-seq analyses is unknown. To address this gap in our knowledge, here we added different concentrations of gDNA to total RNA preparations and subjected them to RNA-seq analysis.

Results

We found that the contaminating gDNA altered the quantification of transcripts at relatively high concentrations. Differentially expressed genes (DEGs) resulting from gDNA contamination may therefore contribute to higher rates of false enrichment of pathways compared with analogous samples lacking numerous DEGs. A strategy was developed to correct gene expression levels in gDNA-contaminated RNA samples, which assessed the magnitude of contamination to improve the reliability of the results.

Conclusions

Our study indicates that caution must be exercised when interpreting results associated with low-abundance transcripts. The data provided here will likely serve as a valuable resource to evaluate the influence of gDNA contamination on RNA-seq analysis, particularly related to the detection of putative novel gene elements.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08785-1.

Insights into Lichen Planus Pigmentosus Inversus using Minimally Invasive Dermal Patch and Whole Transcriptome Analysis

Lichen Planus Pigmentosus inversus (LPPi) is a rare interface and lichenoid dermatitis (ILD) and supposed variant of lichen planus (LP) that presents as well-demarcated brown to grey macules in flexural and intertriginous areas. LPPi is deemed 'inversus' because its anatomical distribution in skin folds is opposite that seen in lichen planus pigmentosus (LPP) whose pigmented lesions arise on sun-exposed skin. Biopsy is required for the clinical diagnosis of all ILDs. Though multiple clinically-oriented studies have reported differences between LPP, LPPi, and LP, few molecular studies have been performed. In this case study, 3 patients, 2 with LPPi and one with LP, provided samples using minimally invasive whole transcriptome analysis using a dermal biomarker patch. This study confirms the involvement of interferon signaling and T-cell activation in LPPi and suggests an expression profile distinct from LP. Specific genes significantly upregulated in LPPi vs LP include an intergenic splice variant of the primary pigmentation determining receptor in humans and dysregulation of genes essential for ceramide synthesis and construction of the cornified envelope. This work expands upon our knowledge of the pathogenesis of LPPi vs LP, and supports the potential use of this technology in the diagnostic clinical setting to mitigate the need for invasive procedures.

Wholistic approach - transcriptomic analysis and beyond using archival material for molecular diagnosis

Many neoplasms remain unclassified after histopathological examination, which requires further molecular analysis. To this regard, mesenchymal neoplasms are particularly challenging due to the combination of their rarity and the large number of subtypes, and many entities still lack robust diagnostic hallmarks. RNA transcriptomic profiles have proven to be a reliable basis for the classification of previously unclassified tumors and notably for mesenchymal neoplasms. Using exome-based RNA capture sequencing on more than 5000 samples of archival material (FFPE), the combination of expression profiles analyzes (including several clustering methods), fusion genes, and small nucleotide variations has been developed at the Centre Léon Bérard (CLB) in Lyon for the molecular diagnosis of challenging neoplasms and the discovery of new entities. The molecular basis of the technique, the protocol, and the bioinformatics algorithms used are described herein, as well as its advantages and limitations.

Association of Complement and MAPK Activation With SARS-CoV-2-Associated Myocardial Inflammation

Question

What is the cardiac phenotype of patients with SARS-CoV-2 infection compared with viral and immune-mediated myocarditis and noninflammatory cardiomyopathy?

Findings

In this case series of 19 patients undergoing endomyocardial biopsies, cardiac specimens of patients with SARS-CoV-2 infection had a higher abundance of complement-associated factors and serine/threonine protein kinases, with mitogen-activated protein kinase–associated pathways having the highest abundance. Similarities in the cardiac immune signature were found among those with SARS-CoV-2 infection and viral myocarditis.

Meaning

In this study, the exploratory data, which characterized myocardial inflammation by deep phenotyping, have implications for the development of treatment strategies to reduce SARS-CoV-2–mediated tissue injury; these findings require confirmation in a prospective and extended cohort of patients.

Importance

Myocardial injury is a common feature of patients with SARS-CoV-2 infection. However, the cardiac inflammatory processes associated with SARS-CoV-2 infection are not completely understood.

Objective

To investigate the inflammatory cardiac phenotype associated with SARS-CoV-2 infection compared with viral myocarditis, immune-mediated myocarditis, and noninflammatory cardiomyopathy by integrating histologic, transcriptomic, and proteomic profiling.

Design, Setting, and Participants

This case series was a cooperative study between the Ludwig Maximilian University Hospital Munich and the Cardiopathology Referral Center at the University of Tübingen in Germany. A cohort of 19 patients with suspected myocarditis was examined; of those, 5 patients were hospitalized with SARS-CoV-2 infection between March and May 2020. Cardiac tissue specimens from those 5 patients were compared with specimens from 5 patients with immune-mediated myocarditis, 4 patients with non–SARS-CoV-2 viral myocarditis, and 5 patients with noninflammatory cardiomyopathy, collected from January to August 2019.

Exposures

Endomyocardial biopsy.

Main Outcomes and Measures

The inflammatory cardiac phenotypes were measured by immunohistologic analysis, RNA exome capture sequencing, and mass spectrometry–based proteomic analysis of endomyocardial biopsy specimens.

Results

Among 19 participants, the median age was 58 years (range, 37-76 years), and 15 individuals (79%) were male. Data on race and ethnicity were not collected. The abundance of CD163+ macrophages was generally higher in the cardiac tissue of patients with myocarditis, whereas lymphocyte counts were lower in the tissue of patients with SARS-CoV-2 infection vs patients with non–SARS-CoV-2 virus-associated and immune-mediated myocarditis. Among those with SARS-CoV-2 infection, components of the complement cascade, including C1q subunits (transcriptomic analysis: 2.5-fold to 3.6-fold increase; proteomic analysis: 2.0-fold to 3.4-fold increase) and serine/cysteine proteinase inhibitor clade G member 1 (transcriptomic analysis: 1.7-fold increase; proteomic analysis: 2.6-fold increase), belonged to the most commonly upregulated transcripts and differentially abundant proteins. In cardiac macrophages, the abundance of C1q was highest in SARS-CoV-2 infection. Assessment of important signaling cascades identified an upregulation of the serine/threonine mitogen-activated protein kinase pathways.

Conclusions and Relevance

This case series found that the cardiac immune signature varied in inflammatory conditions with different etiologic characteristics. Future studies are needed to examine the role of these immune pathways in myocardial inflammation.

Proteome profiling of formalin-fixed, paraffin-embedded lung adenocarcinoma tissues using a tandem mass tag-based quantitative proteomics approach

Over the past few decades, increasing efforts have been made to improve the understanding of, and treatment options for, lung adenocarcinoma (LUAD). However, considering the heterogeneity of LUAD, precise proteomics-based characterization at the molecular level is an urgent clinical requirement for effective treatment. Formalin-fixed, paraffin-embedded (FFPE) tissue is a good option as the working tool for proteomics studies. The present study aimed to obtain a global protein profile using LUAD FFPE tissue samples. Using a quantitative proteomics approach, the study revealed that 360 proteins were significantly more highly expressed in LUAD than in adjacent nontumor lung tissues. Also, 19 differentially expressed membrane proteins were found to be primarily responsible for immune processes. Epidermal growth factor (EGF)-like domain and laminin EGF domain showed markedly different expression levels between cancer tissues and tumor-adjacent normal tissues. Furthermore, Gene Ontology functional enrichment analysis showed that significantly upregulated proteins were associated with the endoplasmic reticulum lumen, protein disulfide isomerase activity, vitamin binding, cell cycle G₁/S phase transition, to name but a few. Also, numerous kinases and post-translational modification enzymes were significantly upregulated across all eight LUAD samples compared with paracarcinoma tissues. Proteomics analysis revealed that AAA domain containing 3A (ATAD3a), a member of the ATPase family, was highly expressed in LUAD tissues, which was supported by immunohistochemical analysis. Furthermore, the study confirmed that ATAD3a enhanced the cisplatin sensitivity of LUAD cells. Collectively, the findings of the present study provide new potential candidate targets in patients with LUAD, and may aid auxiliary LUAD diagnosis and surveillance in a noninvasive manner.

Reconstructing tumor history in breast cancer: signatures of mutational processes and response to neoadjuvant chemotherapy⋆

BACKGROUND

Different endogenous and exogenous mutational processes act over the evolutionary history of a malignant tumor, driven by abnormal DNA editing, mutagens or age-related DNA alterations, among others, to generate the specific mutational landscape of each individual tumor. The signatures of these mutational processes can be identified in large genomic datasets. We investigated the hypothesis that genomic patterns of mutational signatures are associated with the clinical behavior of breast cancer, in particular chemotherapy response and survival, with a particular focus on therapy-resistant disease.

PATIENTS AND METHODS

Whole exome sequencing was carried out in 405 pretherapeutic samples from the prospective neoadjuvant multicenter GeparSepto study. We analyzed 11 mutational signatures including biological processes such as APOBEC-mutagenesis, homologous recombination deficiency (HRD), mismatch repair deficiency and also age-related or tobacco-induced alterations.

RESULTS

Different subgroups of breast carcinomas were defined mainly by differences in HRD-related and APOBEC-related mutational signatures and significant differences between hormone-receptor (HR)-negative and HR-positive tumors as well as correlations with age, Ki-67 and immunological parameters were observed. We could identify mutational processes that were linked to increased pathological complete response rates to neoadjuvant chemotherapy with high significance. In univariate analyses for HR-positive tumors signatures, S3 (HRD, P < 0.001) and S13 (APOBEC, P = 0.001) as well as exonic mutation rate (P = 0.002) were significantly correlated with increased pathological complete response rates. The signatures S3 (HRD, P = 0.006) and S4 (tobacco, P = 0.011) were prognostic for reduced disease-free survival of patients with chemotherapy-resistant tumors.

CONCLUSION

The results of this investigation suggest that the clinical behavior of a tumor, in particular, response to neoadjuvant chemotherapy and disease-free survival of therapy-resistant tumors, could be predicted by the composition of mutational signatures as an indicator of the individual genomic history of a tumor. After additional validations, mutational signatures might be used to identify tumors with an increased response rate to neoadjuvant chemotherapy and to define therapy-resistant subgroups for future therapeutic interventions.