NTRK gene fusions are detected in both secretory and non-secretory breast cancers.

NTRK fusions represent a new biomarker-defined population that can be treated with TRK inhibitors. Although rare, NTRK fusions are detected across a wide range of solid tumors. Previous reports suggest that NTRK fusions are limited to the secretory subtype of breast cancer. Here we examined NTRK fusions in a large real world next-generation sequencing (NGS) dataset and confirmed secretory versus non-secretory status using H&E images. Of 23 NTRK fusion-positive cases, 11 were classified as secretory, 11 as non-secretory, and one as mixed status. The secretory subtype trended younger, was predominantly estrogen receptor (ER)-, had lower tumor mutational burden, and exhibited lower levels of genomic loss of heterozygosity. The non-secretory subtype was enriched for TP53 mutations. The secretory subtype was enriched for ETV6-NTRK3 fusions in 7 of 11 cases, and the non-secretory subtype had NTRK1 fusions in 7 of 11 cases, each with a different fusion partner. Our data suggests NTRK fusions are present in both secretory and non-secretory subtypes, and that comprehensive genomic profiling should be considered across all clinically advanced breast cancers to identify patients that could receive benefit from TRK inhibitors.

Trends in Use of Next-Generation Sequencing in Patients With Solid Tumors by Race and Ethnicity After Implementation of the Medicare National Coverage Determination.

Importance: In March 2018, Medicare issued a national coverage determination (NCD) for next-generation sequencing (NGS) to facilitate access to NGS testing among Medicare beneficiaries. It is unknown whether the NCD affected health equity issues for Medicare beneficiaries and the overall population. Objective: To examine the association between the Medicare NCD and NGS use by insurance types and race and ethnicity. Design, Setting, and Participants: A retrospective cohort analysis was conducted using electronic health record data derived from a real-world database. Data originated from approximately 280 cancer clinics (approximately 800 sites of care) in the US. Patients with advanced non-small cell lung cancer (aNSCLC), metastatic colorectal cancer (mCRC), metastatic breast cancer (mBC), or advanced melanoma diagnosed from January 1, 2011, through March 31, 2020, were included. Exposure: Pre- vs post-NCD period. Main Outcomes and Measures: Patients were classified by insurance type and race and ethnicity to examine patterns in NGS testing less than or equal to 60 days after diagnosis. Difference-in-differences models examined changes in average NGS testing in the pre- and post-NCD periods by race and ethnicity, and interrupted time-series analysis examined whether trends over time varied by insurance type and race and ethnicity. Results: Among 92 687 patients with aNSCLC, mCRC, mBC, or advanced melanoma, mean (SD) age was 66.6 (11.2) years, 51 582 (55.7%) were women, and 63 864 (68.9%) were Medicare beneficiaries. The largest racial and ethnic categories according to the database used and further classification were Black or African American (8605 [9.3%]) and non-Hispanic White (59 806 [64.5%]). Compared with Medicare beneficiaries, changes in pre- to post-NCD NGS testing trends were similar in commercially insured patients (odds ratio [OR], 1.03; 95% CI, 0.98-1.08; P = .25). Pre- to post-NCD NGS testing trends increased at a slower rate among patients in assistance programs (OR, 0.93; 95% CI, 0.87-0.99; P = .03) compared with Medicare beneficiaries. The rate of increase for patients receiving Medicaid was not statistically significantly different compared with those receiving Medicare (OR, 0.92; 95% CI, 0.84-1.01; P = .07). The NCD was not associated with statistically significant changes in NGS use trends by racial and ethnic groups within Medicare beneficiaries alone or across all insurance types. Compared with non-Hispanic White individuals, increases in average NGS use from the pre-NCD to post-NCD period were 14% lower (OR, 0.86; 95% CI, 0.74-0.99; P = .04) among African American and 23% lower (OR, 0.77; 95% CI, 0.62-0.96; P = .02) among Hispanic/Latino individuals; increases among Asian individuals and those with other races and ethnicities were similar. Conclusions and Relevance: The findings of this study suggest that expansion of Medicare-covered benefits may not occur equally across insurance types, thereby further widening or maintaining disparities in NGS testing. Additional efforts beyond coverage policies are needed to ensure equitable access to the benefits of precision medicine.

The Application of Metagenomic Next-Generation Sequencing in Detection of Pathogen in Bronchoalveolar Lavage Fluid and Sputum Samples of Patients with Pulmonary Infection.

OBJECTIVE: To uncover the application value of metagenomic next-generation sequencing (mNGS) in the detection of pathogen in bronchoalveolar lavage fluid (BALF) and sputum samples. METHODS: Totally, 32 patients with pulmonary infection were included. Pathogens in BALF and sputum samples were tested simultaneously by routine microbial culture and mNGS. Main infected pathogens (bacteria, fungi, and viruses) and their distribution in BALF and sputum samples were analyzed. Moreover, the diagnostic performance of mNGS in paired BALF and sputum samples was assessed. RESULTS: The pathogen culture results were positive in 9 patients and negative in 13 patients. No statistical differences were recorded on the sensitivity (78.94% vs. 63.15%, p = 0.283) and specificity (62.50% vs. 75.00%, p = 0.375) of mNGS diagnosis in bacteria and fungus in two types of samples. As shown in mNGS detection, 10 patients' two samples were both positive, 13 patients' two samples were both negative, 7 patients were only positive in BALF samples, and 2 patients' sputum samples were positive. Main viruses mNGS detected were EB virus, human adenovirus 5, herpes simplex virus type 1, and human cytomegalovirus. Kappa consensus analysis indicated that mNGS showed significant consistency in detecting pathogens in two samples, no matter bacteria (p < 0.001), fungi (p = 0.026), or viruses (p = 0.008). CONCLUSION: mNGS showed no statistical differences in sensitivity and specificity of pathogen detection in BALF and sputum samples. Under certain conditions, sputum samples might be more suitable for pathogen detection because of invasiveness of BALF samples.

Machine learning random forest for predicting oncosomatic variant NGS analysis.

Since 2017, we have used IonTorrent NGS platform in our hospital to diagnose and treat cancer. Analyzing variants at each run requires considerable time, and we are still struggling with some variants that appear correct on the metrics at first, but are found to be negative upon further investigation. Can any machine learning algorithm (ML) help us classify NGS variants? This has led us to investigate which ML can fit our NGS data and to develop a tool that can be routinely implemented to help biologists. Currently, one of the greatest challenges in medicine is processing a significant quantity of data. This is particularly true in molecular biology with the advantage of next-generation sequencing (NGS) for profiling and identifying molecular tumors and their treatment. In addition to bioinformatics pipelines, artificial intelligence (AI) can be valuable in helping to analyze mutation variants. Generating sequencing data from patient DNA samples has become easy to perform in clinical trials. However, analyzing the massive quantities of genomic or transcriptomic data and extracting the key biomarkers associated with a clinical response to a specific therapy requires a formidable combination of scientific expertise, biomolecular skills and a panel of bioinformatic and biostatistic tools, in which artificial intelligence is now successful in developing future routine diagnostics. However, cancer genome complexity and technical artifacts make identifying real variants challenging. We present a machine learning method for classifying pathogenic single nucleotide variants (SNVs), single nucleotide polymorphisms (SNPs), multiple nucleotide variants (MNVs), insertions, and deletions detected by NGS from different types of tumor specimens, such as: colorectal, melanoma, lung and glioma cancer. We compared our NGS data to different machine learning algorithms using the k-fold cross-validation method and to neural networks (deep learning) to measure the performance of the different ML algorithms and determine which one is a valid model for confirming NGS variant calls in cancer diagnosis. We trained our machine learning with 70% of our data samples, extracted from our local database (our data structure had 7 parameters: chromosome, position, exon, variant allele frequency, minor allele frequency, coverage and protein description) and validated it with the 30% remaining data. The model offering the best accuracy was chosen and implemented in the NGS analysis routine. Artificial intelligence was developed with the R script language version 3.6.0. We trained our model on 70% of 102,011 variants. Our best error rate (0.22%) was found with random forest machine learning (ntree = 500 and mtry = 4), with an AUC of 0.99. Neural networks achieved some good scores. The final trained model with the neural network achieved an accuracy of 98% and an ROC-AUC of 0.99 with validation data. We tested our RF model to interpret more than 2000 variants from our NGS database: 20 variants were misclassified (error rate < 1%). The errors were nomenclature problems and false positives. After adding false positives to our training database and implementing our RF model routinely, our error rate was always < 0.5%. The RF model shows excellent results for oncosomatic NGS interpretation and can easily be implemented in other molecular biology laboratories. AI is becoming increasingly important in molecular biomedical analysis and can be very helpful in processing medical data. Neural networks show a good capacity in variant classification, and in the future, they may be useful in predicting more complex variants.

Targeted NGS Yields Plentiful Ultra-Rare Variants in Inborn Errors of Immunity Patients.

Inborn errors of immunity (IEI) include a large group of inherited diseases sharing either poor, dysregulated, or absent and/or acquired function in one or more components of the immune system. Next-generation sequencing (NGS) has driven a rapid increase in the recognition of such defects, though the wide heterogeneity of genetically diverse but phenotypically overlapping diseases has often prevented the molecular characterization of the most complex patients. Two hundred and seventy-two patients were submitted to three successive NGS-based gene panels composed of 58, 146, and 312 genes. Along with pathogenic and likely pathogenic causative gene variants, accounting for the corresponding disorders (37/272 patients, 13.6%), a number of either rare (probably) damaging variants in genes unrelated to patients' phenotype, variants of unknown significance (VUS) in genes consistent with their clinics, or apparently inconsistent benign, likely benign, or VUS variants were also detected. Finally, a remarkable amount of yet unreported variants of unknown significance were also found, often recurring in our dataset. The NGS approach demonstrated an expected IEI diagnostic rate. However, defining the appropriate list of genes for these panels may not be straightforward, and the application of unbiased approaches should be taken into consideration, especially when patients show atypical clinical pictures.

A practical guide to chimerism analysis: Review of the literature and testing practices worldwide.

BACKGROUND AND PURPOSE: Currently there are no widely accepted guidelines for chimerism analysis testing in hematopoietic cell transplantation (HCT) patients. The objective of this review is to provide a practical guide to address key aspects of performing and utilizing chimerism testing results. In developing this guide, we conducted a survey of testing practices among laboratories that are accredited for performing engraftment monitoring/chimerism analysis by either the American Society for Histocompatibility & Immunogenetics (ASHI) and/or the European Federation of Immunogenetics (EFI). We interpreted the survey results in the light of pertinent literature as well as the experience in the laboratories of the authors. RECENT DEVELOPMENTS: In recent years there has been significant advances in high throughput molecular methods such as next generation sequencing (NGS) as well as growing access to these technologies in histocompatibility and immunogenetics laboratories. These methods have the potential to improve the performance of chimerism testing in terms of sensitivity, availability of informative genetic markers that distinguish donors from recipients as well as cost. SUMMARY: The results of the survey revealed a great deal of heterogeneity in chimerism testing practices among participating laboratories. The most consistent response indicated monitoring of engraftment within the first 30 days. These responses are reflective of published literature. Additional clinical indications included early detection of impending relapse as well as identification of cases of HLA-loss relapse.

LIQA: long-read isoform quantification and analysis.

Long-read RNA sequencing (RNA-seq) technologies can sequence full-length transcripts, facilitating the exploration of isoform-specific gene expression over short-read RNA-seq. We present LIQA to quantify isoform expression and detect differential alternative splicing (DAS) events using long-read direct mRNA sequencing or cDNA sequencing data. LIQA incorporates base pair quality score and isoform-specific read length information in a survival model to assign different weights across reads, and uses an expectation-maximization algorithm for parameter estimation. We apply LIQA to long-read RNA-seq data from the Universal Human Reference, acute myeloid leukemia, and esophageal squamous epithelial cells and demonstrate its high accuracy in profiling alternative splicing events.

Out-of-pocket and private pay in clinical genetic testing: A scoping review.

Full coverage of the cost of clinical genetic testing is not always available through public or private insurance programs, or a public healthcare system. Consequently, some patients may be faced with the decision of whether to finance testing out-of-pocket (OOP), meet OOP expenses required by their insurer, or not proceed with testing. A scoping review was conducted to identify literature associated with patient OOP and private pay in clinical genetic testing. Seven databases (EMBASE, MEDLINE, CINAHL, PsychINFO, PAIS, the Cochrane Database of Systematic Reviews, and the JBI Evidence-Based Practice database) were searched, resulting in 83 unique publications included in the review. The presented evidence includes a descriptive analysis, followed by a narrative account of the extracted data. Results were divided into four groups according to clinical indication: (1) hereditary breast and ovarian cancer, (2) other hereditary cancers, (3) prenatal testing, (4) other clinical indications. The majority of studies focused on hereditary cancer and prenatal genetic testing. Overall trends indicated that OOP costs have fallen and payer coverage has improved, but OOP expenses continue to present a barrier to patients who do not qualify for full coverage.

Impact of molecular testing in advanced melanoma on outcomes in a tertiary cancer center and as reported in a publicly available database.

BACKGROUND: In patients with advanced melanoma (MM), genomic profiling may guide treatment decisions in the frontline setting and beyond as specific tumor mutations can be treated with targeted therapy (TT). The range of panel sizes used to identify targetable mutations (TM) can range from a few dozen to whole exome sequencing (WES). AIM: We investigated the impact of panel size and mutation status on first-line treatment selection and outcomes in MM. METHODS AND RESULTS: We analyzed data for 1109 MM patients from three cohorts: 169 patients at NYULH and profiled with the 50 gene Ion Torrent panel (IT), 195 patients at MSKCC, profiled with the 400-gene MSK-IMPACT panel (MSK-I) and 745 patients at seven different sites profiled with WES. Data for cohorts 2 and 3 were extrapolated from the publicly available cBioPortal. Treatment information was available for 100%, 25%, and 0% of patients in cohort 1, 2, and 3, respectively. BRAF and NRAS were among the top five most commonly mutated genes in the IT and MSK-I, whereas for WES only BRAF was a top five mutation. There was no significant difference in OS for BRAF MUT patients treated with immune checkpoint inhibitors (ICI) vs TT in cohort 1 (P = .19), nor for BRAF MUT patients from cohort 1 treated with ICI vs those from cohort 2 treated with TT (P = .762). CONCLUSION: Public datasets provide population-level data; however, the heterogeneity of reported clinical information limits their value and calls for data standardization. Without evidence of clear clinical benefit of a larger panel size, there is a rationale for adopting smaller, more cost effective panels in MM.

Molecular Profiling Practices in Pancreatic Adenocarcinoma: Academic vs Community Physicians.

Background: Pancreatic adenocarcinoma (PDAC) is relatively rare but highly aggressive, with most patients diagnosed once they have metastatic or locally invasive disease. Molecular profiling is being explored as a tool for selecting patients for targeted therapy clinical trials and for assessing whether targeted therapies may be effective in PDAC. Whether molecular profiling is being performed at both academic and community oncology clinics has yet to be examined. Here, we characterized the molecular profiling practice patterns in patients with PDAC in academic versus community practices in Denver, Colorado. Methods: We retrospectively reviewed records of all patients with refractory, metastatic PDAC who were referred to a tertiary clinical trials drug development unit in Denver between 2014 and 2019. Results: Of 77 patients, 41 (55%) were men with a mean age of 65 years (SD, 9.3). Fifty-three patients (69%) were referred from the community and 20 (26%) from academic centers; 4 (5%) were self-referred. A total of 51% received profiling prior to referral; 29 of 50 (58%) were from the community and 10 of 21 (47%) from academic settings. Guardant was the most commonly ordered test (47 of 77; 61%); FoundationOne was the second most common (40 of 77; 52%). Twenty-three of 77 patients (30%) received both Guardant and FoundationOne testing, and 3 of 77 (4%) received Caris MI Profile. One patient received a Mocha assay and another received Ascend/Clarient fluorescence in situ hybridization (FISH). Four patients were self-referred, 2 of whom underwent both Guardant and FoundationOne, 1 who underwent Guardant testing only, and 1 who did not receive any molecular profiling testing. Conclusions: This study characterizes molecular profiling practice patterns in individuals with advanced PDAC who were referred to a tertiary clinical trials drug development unit. Both academic and community physicians were found to order profiling about 50% of the time. Further research is needed to determine impact on clinical trial enrollment and detection of PDAC.

Databases for RNA Editing Collections.

A-to-I RNA editing in humans plays a relevant role since it can influence gene expression and increase proteome diversity. In addition, its deregulation has been linked to a variety of human diseases, including neurological disorders and cancer.In the last decade, massive transcriptome sequencing through the RNAseq technology has dramatically improved the investigation of RNA editing at single nucleotide resolution. Nowadays, different bioinformatics resources to discover and/or collect A-to-I events have been released. Hereafter, we initially provide an overview of the state-of-the-art RNA editing databases and, then, we focus on REDIportal, the largest collection of A-to-I events with more than 4.5 million sites from 2660 humans GTEx samples.

MSIsensor-ct: microsatellite instability detection using cfDNA sequencing data.

MOTIVATION: Microsatellite instability (MSI) is a promising biomarker for cancer prognosis and chemosensitivity. Techniques are rapidly evolving for the detection of MSI from tumor-normal paired or tumor-only sequencing data. However, tumor tissues are often insufficient, unavailable, or otherwise difficult to procure. Increasing clinical evidence indicates the enormous potential of plasma circulating cell-free DNA (cfNDA) technology as a noninvasive MSI detection approach. RESULTS: We developed MSIsensor-ct, a bioinformatics tool based on a machine learning protocol, dedicated to detecting MSI status using cfDNA sequencing data with a potential stable MSIscore threshold of 20%. Evaluation of MSIsensor-ct on independent testing datasets with various levels of circulating tumor DNA (ctDNA) and sequencing depth showed 100% accuracy within the limit of detection (LOD) of 0.05% ctDNA content. MSIsensor-ct requires only BAM files as input, rendering it user-friendly and readily integrated into next generation sequencing (NGS) analysis pipelines. AVAILABILITY: MSIsensor-ct is freely available at https://github.com/niu-lab/MSIsensor-ct. SUPPLEMENTARY INFORMATION: Supplementary data are available at Briefings in Bioinformatics online.

Real-world patterns on tumor mutation burden testing in a pan-tumor population.

Background: There is limited real-world information on use of tumor mutational burden (TMB) testing and characteristics of patients receiving it. Materials & methods: Patients ≥18 years old and diagnosed with advanced solid tumors between 1 January 2015 and 31 January 2019 with TMB testing (TMB cohort) and without it (non-TMB) were included in this retrospective, observational study. Results: The TMB cohort (n = 202) was younger than non-TMB (n = 212) (mean age: 62.1 vs 65.6 at diagnosis; p = 0.005). There were more Black patients in the TMB cohort (21.3 vs 11.8% in non-TMB; p = 0.004). Clinical characteristics were comparable between the two cohorts; however, systemic anticancer treatment was higher among TMB cohort (91.6 vs 77.8% in non-TMB). Conclusion: Notable differences were observed between patients receiving TMB test and those not receiving it.

Prognostic significance of postsurgery circulating tumor DNA in nonmetastatic colorectal cancer: Individual patient pooled analysis of three cohort studies.

Studies in multiple solid tumor types have demonstrated the prognostic significance of ctDNA analysis after curative intent surgery. A combined analysis of data across completed studies could further our understanding of circulating tumor DNA (ctDNA) as a prognostic marker and inform future trial design. We combined individual patient data from three independent cohort studies of nonmetastatic colorectal cancer (CRC). Plasma samples were collected 4 to 10 weeks after surgery. Mutations in ctDNA were assayed using a massively parallel sequencing technique called SafeSeqS. We analyzed 485 CRC patients (230 Stage II colon, 96 Stage III colon, and 159 locally advanced rectum). ctDNA was detected after surgery in 59 (12%) patients overall (11.0%, 12.5% and 13.8% for samples taken at 4-6, 6-8 and 8-10 weeks; P = .740). ctDNA detection was associated with poorer 5-year recurrence-free (38.6% vs 85.5%; P < .001) and overall survival (64.6% vs 89.4%; P < .001). The predictive accuracy of postsurgery ctDNA for recurrence was higher than that of individual clinicopathologic risk features. Recurrence risk increased exponentially with increasing ctDNA mutant allele frequency (MAF) (hazard ratio, 1.2, 2.5 and 5.8 for MAF of 0.1%, 0.5% and 1%). Postsurgery ctDNA was detected in 3 of 20 (15%) patients with locoregional and 27 of 60 (45%) with distant recurrence (P = .018). This analysis demonstrates a consistent long-term impact of ctDNA as a prognostic marker across nonmetastatic CRC, where ctDNA outperforms other clinicopathologic risk factors and MAF further stratifies recurrence risk. ctDNA is a better predictor of distant vs locoregional recurrence.

Integrative analysis of structural variations using short-reads and linked-reads yields highly specific and sensitive predictions.

Genetic diseases are driven by aberrations of the human genome. Identification of such aberrations including structural variations (SVs) is key to our understanding. Conventional short-reads whole genome sequencing (cWGS) can identify SVs to base-pair resolution, but utilizes only short-range information and suffers from high false discovery rate (FDR). Linked-reads sequencing (10XWGS) utilizes long-range information by linkage of short-reads originating from the same large DNA molecule. This can mitigate alignment-based artefacts especially in repetitive regions and should enable better prediction of SVs. However, an unbiased evaluation of this technology is not available. In this study, we performed a comprehensive analysis of different types and sizes of SVs predicted by both the technologies and validated with an independent PCR based approach. The SVs commonly identified by both the technologies were highly specific, while validation rate dropped for uncommon events. A particularly high FDR was observed for SVs only found by 10XWGS. To improve FDR and sensitivity, statistical models for both the technologies were trained. Using our approach, we characterized SVs from the MCF7 cell line and a primary breast cancer tumor with high precision. This approach improves SV prediction and can therefore help in understanding the underlying genetics in various diseases.

Deep sequencing detects human papillomavirus (HPV) in cervical cancers negative for HPV by PCR.

BACKGROUND: Human papillomavirus (HPV) is a necessary cause of cervical cancer, although some invasive cervical cancers may test negative by HPV PCR. We previously requested all invasive cervical cancers in Sweden during 10 years and subjected them to PCR. We also optimised methods for deep sequencing of formalin-fixed paraffin-embedded samples. METHODS: Using Novaseq 6000, we simultaneously sequenced total DNA and cDNA from 392 HPV PCR-negative cervical cancers. Non-human reads were queried against all known HPVs. The complete database now contains PCR and/or deep sequencing data on 2850 invasive cervical cancers. RESULTS: HPV sequences were detected in 169/392 of HPV PCR-negative cervical cancers. Overall, 30 different HPV types were detected, but only 5 types were present in proportions above 3% of cancers. More than 92% of tumours were HPV-positive in PCR and/or sequencing (95% confidence interval: 91.1-93.1%). Exploring possible reasons for failure to previously detect HPV suggest that more sensitive type-specific PCRs for HPV 31, 33, 45 and 73 targeting retained regions of HPV would have detected most of these (117/392). CONCLUSIONS: Unbiased deep sequencing provides comprehensive data on HPV types in cervical cancers and appears to be an important tool for quality assurance of HPV screening.

Evidence for hypoxia increasing the tempo of evolution in glioblastoma.

BACKGROUND: Tumour hypoxia is associated with metastatic disease, and while there have been many mechanisms proposed for why tumour hypoxia is associated with metastatic disease, it remains unclear whether one precise mechanism is the key reason or several in concert. Somatic evolution drives cancer progression and treatment resistance, fuelled not only by genetic and epigenetic mutation but also by selection from interactions between tumour cells, normal cells and physical micro-environment. Ecological habitats influence evolutionary dynamics, but the impact on tempo of evolution is less clear. METHODS: We explored this complex dialogue with a combined clinical-theoretical approach by simulating a proliferative hierarchy under heterogeneous oxygen availability with an agent-based model. Predictions were compared against histology samples taken from glioblastoma patients, stained to elucidate areas of necrosis and TP53 expression heterogeneity. RESULTS: Results indicate that cell division in hypoxic environments is effectively upregulated, with low-oxygen niches providing avenues for tumour cells to spread. Analysis of human data indicates that cell division is not decreased under hypoxia, consistent with our results. CONCLUSIONS: Our results suggest that hypoxia could be a crucible that effectively warps evolutionary velocity, making key mutations more likely. Thus, key tumour ecological niches such as hypoxic regions may alter the evolutionary tempo, driving mutations fuelling tumour heterogeneity.

BRCA testing in a genomic diagnostics referral center during the COVID-19 pandemic.

The first person-to-person transmission of the 2019-novel coronavirus in Italy on 21 February 2020 led to an infection chain that represents one of the largest known COVID-19 outbreaks outside Asia. Hospitals have been forced to reorganized their units in response to prepare for an unforeseen healthcare emergency. In this context, our laboratory (Molecular and Genomic Diagnostics Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS) re-modulated its priorities by temporarily interrupting most of the molecular tests guaranteeing only those considered "urgent" and not postponable. In particular, this paper details changes regarding the execution of germline BRCA (gBRCA) testing in our laboratory. A substantial reduction in gBRCA testing (about 60%) compared to the first 2 months of the current year was registered, but the requests have not been reset. The requesting physicians were mainly gynaecologists and oncologists. These evidences further emphasize the new era of gBRCA testing in the management of cancer patients and confirms definitively the integration of gBRCA testing/Next Generation Sequencing (NGS) into clinical oncology. Finally, a re-organization of gBRCA testing in our Unit, mainly related to delayed and reduced arrival of tests was necessary, ensuring, however, a high-quality standard and reliability, mandatory for gBRCA testing in a clinical setting.

Tumor Mutation Burden Computation in Two Pan-Cancer Precision Medicine Next-Generation Sequencing Panels.

FD-180 and FD-600 are two next-generation sequencing panels developed by First Dimension Biosciences Co. for detecting mutations in cancer tissues and providing therapeutics guidance in precision medicine applications. FD-180 includes the coding exons of about 180 genes, including all the known drug target genes and some important driver genes; whereas FD-600 includes the coding exons of 578 cancer driver genes in the COSMIC database as of year 2016 when the panels are developed. Additional noncoding regions in the selected genes are included if they are reported as clinically meaningful in ClinVar. Tumor mutation burden (TMB) is a statistical index calculated from genomic sequencing for immunotherapeutic treatments, especially for PD1/PD-L1 antibodies. We used our computational algorithm on 81 patients and provided their classifications. TMB can be estimated quite accurately for the FD-180 and FD-600 panels, both for The Cancer Genome Atlas data and in clinical practice.

Clinicopathological and Molecular Characterisation of Crohn's Disease-associated Small Bowel Adenocarcinomas.

BACKGROUND AND AIMS: Small bowel adenocarcinoma [SBA] is a recognised complication of Crohn's disease [CD], but its low absolute prevalence limits opportunities for clinicopathological characterisation. METHODS: We compared the clinical, pathological, and molecular features of 48 SBA from patients with CD [CDSBA] and 29 SBAs from patients without CD [NSBA] who underwent treatment at our tertiary care centre between 2000 and 2018. RESULTS: Patients with CDSBA were younger than those with NSBA [mean age, 56 vs 64; p = 0.02]. Males predominated in both groups. Most CDSBA [69%] occurred in the ileum, whereas most NSBA occurred in the duodenum [38%] and jejunum [31%; p < 0.001]. Stage I tumours were more prevalent in the CDSBA [33% vs 3%; p = 0.002], although the rates of Stage IV disease and disease-specific mortality were similar in both groups. CDSBA were less likely to present a discrete mass [35% vs 93%; p < 0.001] and were more often stricturing or fistulising [75% vs 10%, respectively, p < 0.001] than NSBA. Microscopically, CDSBA were relatively heterogeneous, exhibiting at least three distinct growth patterns in 39% compared with 1% of NSBA [p = 0.01]. Low-grade tubuloglandular adenocarcinoma was the predominant pattern in 19% of CDSBA compared with 0% of NSBA [p = 0.003]. CDSBA were more frequently DNA mismatch repair proficient [90% vs 62%; p = 0.04] and exhibited profiles of frequently mutated genes similar to those of NSBA, except for IDH1 [18%] and SMAD4 [12%] mutations that occurred uniquely in CDSBA. CONCLUSIONS: These observations, based on the largest single-centre series described hitherto, establish that CDSBA is a distinct clinical, pathological, and molecular entity.