Identification and clinical impact of potentially actionable somatic oncogenic mutations in solid tumor samples

Clinical Network Systems Biology: Traversing the Cancer Multiverse

In recent decades, cancer biology and medicine have ushered in a new age of precision medicine through high-throughput approaches that led to the development of novel targeted therapies and immunotherapies for different cancers. The availability of multifaceted high-throughput omics data has revealed that cancer, beyond its genomic heterogeneity, is a complex system of microenvironments, sub-clonal tumor populations, and a variety of other cell types that impinge on the genetic and non-genetic mechanisms underlying the disease. Thus, a systems approach to cancer biology has become instrumental in identifying the key components of tumor initiation, progression, and the eventual emergence of drug resistance. Through the union of clinical medicine and basic sciences, there has been a revolution in the development and approval of cancer therapeutic drug options including tyrosine kinase inhibitors, antibody-drug conjugates, and immunotherapy. This 'Team Medicine' approach within the cancer systems biology framework can be further improved upon through the development of high-throughput clinical trial models that utilize machine learning models, rapid sample processing to grow patient tumor cell cultures, test multiple therapeutic options and assign appropriate therapy to individual patients quickly and efficiently. The integration of systems biology into the clinical network would allow for rapid advances in personalized medicine that are often hindered by a lack of drug development and drug testing.

Endometrial cancer diagnostic and prognostic algorithms based on proteomics, metabolomics, and clinical data: a systematic review

Endometrial cancer is the most common gynaecological malignancy in developed countries. Over 382,000 new cases were diagnosed worldwide in 2018, and its incidence and mortality are constantly rising due to longer life expectancy and life style factors including obesity. Two major improvements are needed in the management of patients with endometrial cancer, i.e., the development of non/minimally invasive tools for diagnostics and prognostics, which are currently missing. Diagnostic tools are needed to manage the increasing number of women at risk of developing the disease. Prognostic tools are necessary to stratify patients according to their risk of recurrence pre-preoperatively, to advise and plan the most appropriate treatment and avoid over/under-treatment. Biomarkers derived from proteomics and metabolomics, especially when derived from non/minimally-invasively collected body fluids, can serve to develop such prognostic and diagnostic tools, and the purpose of the present review is to explore the current research in this topic. We first provide a brief description of the technologies, the computational pipelines for data analyses and then we provide a systematic review of all published studies using proteomics and/or metabolomics for diagnostic and prognostic biomarker discovery in endometrial cancer. Finally, conclusions and recommendations for future studies are also given.

Ultra-rapid somatic variant detection via real-time targeted amplicon sequencing

Molecular markers are essential for cancer diagnosis, clinical trial enrollment, and some surgical decision making, motivating ultra-rapid, intraoperative variant detection. Sequencing-based detection is considered the gold standard approach, but typically takes hours to perform due to time-consuming DNA extraction, targeted amplification, and library preparation times. In this work, we present a proof-of-principle approach for sub-1 hour targeted variant detection using real-time DNA sequencers. By modifying existing protocols, optimizing for diagnostic time-to-result, we demonstrate confirmation of a hot-spot mutation from tumor tissue in ~52 minutes. To further reduce time, we explore rapid, targeted Loop-mediated Isothermal Amplification (LAMP) and design a bioinformatics tool-LAMPrey-to process sequenced LAMP product. LAMPrey's concatemer aware alignment algorithm is designed to maximize recovery of diagnostically relevant information leading to a more rapid detection versus standard read alignment approaches. Using LAMPrey, we demonstrate confirmation of a hot-spot mutation (250x support) from tumor tissue in less than 30 minutes.

A Non-Hazardous Deparaffinization Protocol Enables Quantitative Proteomics of Core Needle Biopsy-Sized Formalin-Fixed and Paraffin-Embedded (FFPE) Tissue Specimens

Most human tumor tissues that are obtained for pathology and diagnostic purposes are formalin-fixed and paraffin-embedded (FFPE). To perform quantitative proteomics of FFPE samples, paraffin has to be removed and formalin-induced crosslinks have to be reversed prior to proteolytic digestion. A central component of almost all deparaffinization protocols is xylene, a toxic and highly flammable solvent that has been reported to negatively affect protein extraction and quantitative proteome analysis. Here, we present a 'green' xylene-free protocol for accelerated sample preparation of FFPE tissues based on paraffin-removal with hot water. Combined with tissue homogenization using disposable micropestles and a modified protein aggregation capture (PAC) digestion protocol, our workflow enables streamlined and reproducible quantitative proteomic profiling of FFPE tissue. Label-free quantitation of FFPE cores from human ductal breast carcinoma in situ (DCIS) xenografts with a volume of only 0.79 mm³ showed a high correlation between replicates (r² = 0.992) with a median %CV of 16.9%. Importantly, this small volume is already compatible with tissue micro array (TMA) cores and core needle biopsies, while our results and its ease-of-use indicate that further downsizing is feasible. Finally, our FFPE workflow does not require costly equipment and can be established in every standard clinical laboratory.

Clinical Outcomes of Genotype-Matched Therapy for Recurrent Gynecological Cancers: A Single Institutional Experience

Recent advances in next-generation sequencing and genome medicine have contributed to treatment decisions in patients with cancer. Most advanced gynecological cancers develop resistance to chemotherapy and have a poor prognosis. Therefore, we conducted genomic tests in gynecological tumors to examine the efficacy and clinical feasibility of genotype-matched therapy. Target sequencing was performed in 20 cases of gynecological cancers (cervical cancer, 6; endometrial cancer, 6; and ovarian cancer, 6). Both actionable and druggable genes were identified in 95% (19/20) of the cases. Among them, seven patients (35%) received genotype-matched therapy, which was effective in three patients. Of the three patients, one patient with a PTEN mutation received everolimus, another patient with a TSC2 mutation received everolimus and letrozole, and the patient with a BRIP1 mutation received olaparib. Subsequently, disease control in these three patients lasted for more than half a year. However, all patients relapsed between 9 and 13 months after the initiation of genotype-matched therapy. In this study, the response rate of genotype-matched therapy was 43% (3/7), which may have contributed to improved prognoses. Therefore, genotype-matched therapies may help patients with refractory gynecological cancers achieve better outcomes.

Genomic profiling using the UltraSEEK panel identifies discordancy between paired primary and breast cancer brain metastases and an association with brain metastasis-free survival

PURPOSE

Brain metastases (BM) are an increasing clinical problem. This study aimed to assess paired primary breast cancers (BC) and BM for aberrations within TP53, PIK3CA, ESR1, ERBB2 and AKT utilising the MassARRAY® UltraSEEK® technology (Agena Bioscience, San Diego, USA).

METHODS

DNA isolated from 32 paired primary BCs and BMs was screened using the custom UltraSEEK® Breast Cancer Panel. Data acquisition and analysis was performed by the Agena Bioscience Typer software v4.0.26.74.

RESULTS

Mutations were identified in 91% primary BCs and 88% BM cases. TP53, AKT1, ESR1, PIK3CA and ERBB2 genes were mutated in 68.8%, 37.5%, 31.3%, 28.1% and 3.1% respectively of primary BCs and in 59.4%, 37.5%, 28.1%, 28.1% and 3.1% respectively of BMs. Differences in the mutations within the 5 genes between BC and paired BM were identified in 62.5% of paired cases. In primary BCs, ER-positive/HER2-negative cases harboured the most mutations (70%), followed by ER-positive/HER2-positive (15%) and triple-negatives (13.4%), whereas in BMs, the highest number of mutations was observed in triple-negative (52.5%), followed by ER-positive/HER2-negative (35.6%) and ER-negative/HER2-positive (12%). There was a significant association between the number of mutations in the primary BC and breast-to-brain metastasis-free survival (p = 0.0001) but not with overall survival (p = 0.056).

CONCLUSION

These data demonstrate the discordancy between primary BC and BM, as well as the presence of clinically important, actionable mutations in BCBM. The UltraSEEK® Breast Cancer Panel provides a tool for BCBM that can be utilised to direct more tailored treatment decisions and for clinical studies investigating targeted agents.

Evaluation of Somatic Mutations in Solid Metastatic Pan-Cancer Patients

Metastasis continues to be the primary cause of all cancer-related deaths despite the recent advancements in cancer treatments. To evaluate the role of mutations in overall survival (OS) and treatment outcomes, we analyzed 957 metastatic patients with seven major cancer types who had available molecular testing results with a FoundationOne CDx® panel. The most prevalent genes with somatic mutations were TP53, KRAS, APC, and LRP1B. In this analysis, these genes had mutation frequencies higher than in publicly available datasets. We identified that the somatic mutations were seven mutually exclusive gene pairs and an additional fifty-two co-occurring gene pairs. Mutations in the mutually exclusive gene pair APC and CDKN2A showed an opposite effect on the overall survival. However, patients with CDKN2A mutations showed significantly shorter OS (HR: 1.72, 95% CI: 1.34-2.21, p < 0.001) after adjusting for cancer type, age at diagnosis, and sex. Five-year post metastatic diagnosis survival analysis showed a significant improvement in OS (median survival 28 and 43 months in pre-2015 and post-2015 metastatic diagnosis, respectively, p = 0.00021) based on the year of metastatic diagnosis. Although the use of targeted therapies after metastatic diagnosis prolonged OS, the benefit was not statistically significant. However, longer five-year progression-free survival (PFS) was significantly associated with targeted therapy use (median 10.9 months (CI: 9.7-11.9 months) compared to 9.1 months (CI: 8.1-10.1 months) for non-targeted therapy, respectively, p = 0.0029). Our results provide a clinically relevant overview of the complex molecular landscape and survival mechanisms in metastatic solid cancers.

KRAS, BRAF, PIK3CA mutation frequency of radical prostatectomy samples and review of the literature

OBJECTIVE

The molecular basis of prostate cancer is highly heterogeneous. Our study aimed to perform the mutation analysis of KRAS, BRAF, PIK3CA, and immunohistochemical (IHC) evaluation of EGFR, HER2, p16, and PTEN to demonstrate new areas for targeted therapies.

METHODS

A total of 24 prostatectomy samples diagnosed with adenocarcinoma were analyzed by microarray hybridization. Also, these samples were IHC stained for EGFR, HER2, P16, and PTEN. The cases were divided into two groups based on low and high Gleason scores. All findings were compared with the clinicopathological parameters of the patients.

RESULTS

While KRAS mutation was in 3/24 (12.5%) of our cases, BRAF and PIK3CA mutations were not detected. There was no significant difference between the groups in terms of KRAS mutation frequency. HER2 was immunohistochemically negative in all samples. There was no correlation between EGFR, P16 immunopositivity, and clinicopathological features.

CONCLUSION

KRAS mutation frequency is similar to those in Asian populations. BRAF and PIK3CA mutation frequencies have been reported in the literature in the range of 0-15% and 0-10.4%, respectively, consistent with our study findings. HER2 immunoexpression is a controversial issue in the literature. EGFR and p16 expressions may not correlate with the stage.

Discovery of Targetable Genetic Alterations in NSCLC Patients with Different Metastatic Patterns Using a MassARRAY-Based Circulating Tumor DNA Assay

Circulating tumor DNA (ctDNA) has shown great promise as a minimally invasive liquid biopsy for personalized cancer diagnostics especially among metastatic patients. Here, we used a novel sensitive assay to detect clinically relevant mutations in ctDNA in blood plasma from metastatic non-small cell lung cancer (NSCLC) patients, including patients with a limited oligo-brain metastatic disease. We analyzed 66 plasma samples from 56 metastatic NSCLC patients for 74 hotspot mutations in five genes commonly mutated in NSCLC using a novel MassARRAY-based lung cancer panel with a turnaround time of only 3 days. Mutations in plasma DNA could be detected in 28 out of 56 patients (50.0%), with a variant allele frequency (VAF) ranging between 0.1% and 5.0%. Mutations were detected in 50.0% of patients with oligo-brain metastatic disease, although the median VAF was lower (0.4%) compared to multi-brain metastatic patients (0.9%) and patients with extra-cranial metastatic progression (1.2%). We observed an overall concordance of 86.4% (n = 38/44) for EGFR status between plasma and tissue. The MassARRAY technology can detect clinically relevant mutations in plasma DNA from metastatic NSCLC patients including patients with limited, oligo-brain metastatic disease.