Evaluation of the TruSight Oncology 500 Assay for Routine Clinical Testing of Tumor Mutational Burden and Clinical Utility for Predicting Response to Pembrolizumab

A phase 1 trial of the MEK inhibitor selumetinib in combination with pembrolizumab for advanced or metastatic solid tumors

MEK inhibitors have immunomodulatory activity and potential for synergistic activity when combined with PD-1 inhibitors. We evaluated selumetinib (inhibitor of MEK1/2) plus pembrolizumab (anti‒PD-1 antibody) in patients with advanced/metastatic solid tumors. In this phase 1b study, adults with previously treated advanced/metastatic solid tumors received pembrolizumab 200 mg intravenously every 3 weeks plus selumetinib on days 1‒14 per 3-week cycle (2 weeks on/1 week off); selumetinib dosing began at 50 mg orally twice daily with escalation in 25 mg increments for ≤ 35 cycles. Primary endpoints were dose-limiting toxicities (DLTs), adverse events (AEs), and treatment discontinuations due to AEs. Thirty-two patients were enrolled. Dose escalation was completed up to selumetinib 125 mg twice daily. The target DLT rate of 30% was not reached at any dose level. In the selumetinib 100 mg group, 2/11 patients (18.2%) experienced DLTs (n = 1 grade 3 diarrhea, n = 1 grade 3 fatigue). In the selumetinib 125 mg group, 3/14 (21.4%) experienced DLTs (n = 1 grade 2 retinal detachment, n = 1 grade 3 retinopathy, n = 1 grade 3 stomatitis). Dose-related changes in pharmacokinetic exposures were observed for selumetinib and N-desmethyl selumetinib up to 100 mg (saturation at 125 mg). Two patients achieved partial responses (1 each with selumetinib 75 mg and 125 mg) for an objective response rate of 6%. The study was stopped early because of insufficient efficacy. Although the target DLT rate was not reached at any dose level and no new safety signals were identified, selumetinib plus pembrolizumab had limited antitumor activity in this population. Trial registration: ClinicalTrials.gov , NCT03833427.

Integration of proteomics in the molecular tumor board

Cancer remains one of the most complex and challenging diseases in mankind. To address the need for a personalized treatment approach for particularly complex tumor cases, molecular tumor boards (MTBs) have been initiated. MTBs are interdisciplinary teams that perform in-depth molecular diagnostics to cooperatively and interdisciplinarily advise on the best therapeutic strategy. Current molecular diagnostics are routinely performed on the transcriptomic and genomic levels, aiming to identify tumor-driving mutations. However, these approaches can only partially capture the actual phenotype and the molecular key players of tumor growth and progression. Thus, direct investigation of the expressed proteins and activated signaling pathways provide valuable complementary information on the tumor-driving molecular characteristics of the tissue. Technological advancements in mass spectrometry-based proteomics enable the robust, rapid, and sensitive detection of thousands of proteins in minimal sample amounts, paving the way for clinical proteomics and the probing of oncogenic signaling activity. Therefore, proteomics is currently being integrated into molecular diagnostics within MTBs and holds promising potential in aiding tumor classification and identifying personalized treatment strategies. This review introduces MTBs and describes current clinical proteomics, its potential in precision oncology, and highlights the benefits of multi-omic data integration.

Molecular characterization of 13 patients with PIK3CA-related overgrowth spectrum using a targeted deep sequencing approach

Activating variants in the PIK3CA gene cause a heterogeneous spectrum of disorders that involve congenital or early-onset segmental/focal overgrowth, now referred to as PIK3CA-related overgrowth spectrum (PROS). Historically, the clinical diagnoses of patients with PROS included a range of distinct syndromes, including CLOVES syndrome, dysplastic megalencephaly, hemimegalencephaly, focal cortical dysplasia, Klippel-Trenaunay syndrome, CLAPO syndrome, fibroadipose hyperplasia or overgrowth, hemihyperplasia multiple lipomatosis, and megalencephaly capillary malformation-polymicrogyria (MCAP) syndrome. MCAP is a sporadic overgrowth disorder that exhibits core features of progressive megalencephaly, vascular malformations, distal limb malformations, cortical brain malformations, and connective tissue dysplasia. In 2012, our research group contributed to the identification of predominantly mosaic, gain-of-function variants in PIK3CA as an underlying genetic cause of the syndrome. Mosaic variants are technically more difficult to detect and require implementation of more sensitive sequencing technologies and less stringent variant calling algorithms. In this study, we demonstrated the utility of deep sequencing using the Illumina TruSight Oncology 500 (TSO500) sequencing panel in identifying variants with low allele fractions in a series of patients with PROS and suspected mosaicism: pathogenic, mosaic PIK3CA variants were identified in all 13 individuals, including 6 positive controls. This study highlights the importance of screening for low-level mosaic variants in PROS patients. The use of targeted panels with deep sequencing in clinical genetic testing laboratories would improve diagnostic yield and accuracy within this patient population.

Sarcomas With RAD51B Fusions Are Associated With a Heterogeneous Phenotype

RAD51B-rearranged sarcomas are rare neoplasms that exhibit a heterogeneous morphology. To date, 6 cases have been reported, all involving the uterus, including 4 perivascular epithelioid cell tumors (PEComas) and 2 leiomyosarcomas (LMS). In this study, we describe the morphologic, immunohistochemical, and molecular features of 8 additional sarcomas with RAD51B rearrangement, including the first extrauterine example. All patients were women with a median age of 57 years at presentation. Seven tumors originated in the uterus, and one in the lower extremity soft tissue, with a median tumor size of 12 cm. Histologically, 4 tumors showed predominantly spindle cell morphology with eosinophilic fibrillary cytoplasm, with or without nuclear pleomorphism, whereas 2 tumors exhibited pleomorphic epithelioid cells, featuring clear to eosinophilic, granular cytoplasm. Two neoplasms exhibited undifferentiated cytomorphology, including one with uniform small blue round cells. All tumors showed high-grade cytologic atypia and high mitotic activity (median: 30/10 high-power fields), whereas coagulative necrosis was noted in 6 cases and lymphovascular invasion in 2. By immunohistochemistry, 2 showed myoid and melanocytic markers in keeping with PEComa, whereas 4 cases were only positive for smooth muscle markers consistent with LMS (including 3 myxoid). The remaining 2 cases had a nonspecific immunoprofile. Five cases tested by targeted RNA sequencing (Archer FusionPlex, Illumina TruSight) showed different fusion partners (HMGA2, PDDC1, and CEP170). RAD51B rearrangements were identified by FISH in the remaining 3 cases. Targeted DNA sequencing in 2 cases was negative for TSC gene alterations. Clinical outcome, available in 5 patients (median follow-up, 19 months), revealed 3 local recurrences, 2 lung metastases, and 4 deaths due to disease. Our results expand the spectrum of sarcomas with RAD51B fusions, demonstrating variable clinical presentations, morphologic spectrum, and fusion partners. These tumors have a predilection for a uterine location, with either LMS, PEComa, or undifferentiated phenotypes, and are associated with an aggressive clinical course.

Impact of genetic counseling strategy on diagnostic yield and workload for genome-sequencing-based tumor diagnostics

PURPOSE

Genome sequencing (GS) enables comprehensive molecular analysis of tumors and identification of hereditary cancer predisposition. According to guidelines, directly determining pathogenic germline variants (PGVs) requires pretest genetic counseling, which is cost-ineffective. Referral for genetic counseling based on tumor variants alone could miss relevant PGVs and/or result in unnecessary referrals.

METHODS

We validated GS for detection of germline variants and simulated 3 strategies using paired tumor-normal GS data of 937 metastatic patients. In strategy-1, genetic counseling before tumor testing allowed direct PGV analysis. In strategy-2 and -3, germline testing and referral for post-test genetic counseling is based on tumor variants using Dutch (strategy-2) or Europen Society for Medical Oncology (ESMO) Precision Medicine Working Group (strategy-3) guidelines.

RESULTS

In strategy-1, PGVs would be detected in 50 patients (number-needed-to counsel; NTC = 18.7). In strategy-2, 86 patients would have been referred for genetic counseling and 43 would have PGVs (NTC = 2). In strategy-3, 94 patients would have been referred for genetic counseling and 32 would have PGVs (NTC = 2.9). Hence, 43 and 62 patients, respectively, were unnecessarily referred based on a somatic variant.

CONCLUSION

Both post-tumor test counseling strategies (2 and 3) had significantly lower NTC, and strategy-2 had the highest PGV yield. Combining pre-tumor test mainstreaming and post-tumor test counseling may maximize the clinically relevant PGV yield and minimize unnecessary referrals.

Comprehensive genomic profiling on metastatic Melanoma: results from a network screening from 7 Italian Cancer Centres

BACKGROUND

The current therapeutic algorithm for Advanced Stage Melanoma comprises of alternating lines of Targeted and Immuno-therapy, mostly via Immune-Checkpoint blockade. While Comprehensive Genomic Profiling of solid tumours has been approved as a companion diagnostic, still no approved predictive biomarkers are available for Melanoma aside from BRAF mutations and the controversial Tumor Mutational Burden. This study presents the results of a Multi-Centre Observational Clinical Trial of Comprehensive Genomic Profiling on Target and Immuno-therapy treated advanced Melanoma.

METHODS

82 samples, collected from 7 Italian Cancer Centres of FFPE-archived Metastatic Melanoma and matched blood were sequenced via a custom-made 184-gene amplicon-based NGS panel. Sequencing and bioinformatics analysis was performed at a central hub. Primary analysis was carried out via the Ion Reporter framework. Secondary analysis and Machine Learning modelling comprising of uni and multivariate, COX/Lasso combination, and Random Forest, was implemented via custom R/Python scripting.

RESULTS

The genomics landscape of the ACC-mela cohort is comparable at the somatic level for Single Nucleotide Variants and INDELs aside a few gene targets. All the clinically relevant targets such as BRAF and NRAS have a comparable distribution thus suggesting the value of larger scale sequencing in melanoma. No comparability is reached at the CNV level due to biotechnological biases and cohort numerosity. Tumour Mutational Burden is slightly higher in median for Complete Responders but fails to achieve statistical significance in Kaplan-Meier survival analysis via several thresholding strategies. Mutations on PDGFRB, NOTCH3 and RET were shown to have a positive effect on Immune-checkpoint treatment Overall and Disease-Free Survival, while variants in NOTCH4 were found to be detrimental for both endpoints.

CONCLUSIONS

The results presented in this study show the value and the challenge of a genomics-driven network trial. The data can be also a valuable resource as a validation cohort for Immunotherapy and Target therapy genomic biomarker research.

Systematic comparison of variant calling pipelines of target genome sequencing cross multiple next-generation sequencers

Targeted genomic sequencing (TS) greatly benefits precision oncology by rapidly detecting genetic variations with better accuracy and sensitivity owing to its high sequencing depth. Multiple sequencing platforms and variant calling tools are available for TS, making it excruciating for researchers to choose. Therefore, benchmarking study across different platforms and pipelines available for TS is imperative. In this study, we performed a TS of Reference OncoSpan FFPE (HD832) sample enriched by TSO500 panel using four commercially available sequencers, and analyzed the output 50 datasets using five commonly-used bioinformatics pipelines. We systematically investigated the sequencing quality and variant detection sensitivity, expecting to provide optimal recommendations for future research. Four sequencing platforms returned highly concordant results in terms of base quality (Q20 > 94%), sequencing coverage (>97%) and depth (>2000×). Benchmarking revealed good concordance of variant calling across different platforms and pipelines, among which, FASTASeq 300 platform showed the highest sensitivity (100%) and precision (100%) in high-confidence variants calling when analyzed by SNVer and VarScan 2 algorithms. Furthermore, this sequencer demonstrated the shortest sequencing time (∼21 h) at the sequencing mode PE150. Through the intersection of 50 datasets generated in this study, we recommended a novel set of variant genes outside the truth set published by HD832, expecting to replenish HD832 for future research on tumor variant diagnosis. Besides, we applied these five tools to another panel (TargetSeq One) for Twist cfDNA Pan-cancer Reference Standard, comprehensive consideration of SNP and InDel sensitivity, SNVer and VarScan 2 performed best among them. Furthermore, SNVer and VarScan 2 also performed best for six cancer cell lines samples regarding SNP and InDel sensitivity. Considering the dissimilarity of variant calls across different pipelines for datasets from the same platform, we recommended an integration of multiple tools to improve variant calling sensitivity and accuracy for the cancer genome. Illumina and GeneMind technologies can be used independently or together by public health laboratories performing tumor TS. SNVer and VarScan 2 perform better regarding variant detection sensitivity for three typical tumor samples. Our study provides a standardized target sequencing resource to benchmark new bioinformatics protocols and sequencing platforms.

Case Report: Identification of a novel STAT3 mutation in EBV-positive inflammatory follicular dendritic cell sarcoma

EBV-positive inflammatory follicular dendritic cell sarcoma (EBV+ IFDCS) is an uncommon disease primarily observed in Asia. It is characterized by the development of tumors believed to originate from follicular dendritic cells (FDC). The consistent association between this condition and clonal EBV infection suggests EBV's involvement as an etiological factor. However, diagnosing EBV+ IFDCS can be challenging due to its morphological variability and diverse immunohistochemical staining patterns. The genetic characteristics of EBV+ IFDCS remain insufficiently understood. To address this knowledge gap, we present a case study of a 47-year-old male patient diagnosed with EBV+ IFDCS. We utilized a Next-generation sequencing (NGS) platform to investigate the genetic profile of the tumor cells. We identified a single pathogenic mutation (G618R) in the STAT3 gene. This finding provides valuable insights into the genetic alterations associated with EBV+ IFDCS and potentially contributes to our understanding of the disease's pathogenesis.

Comprehensive clinical assays for molecular diagnostics of gliomas: the current state and future prospects

Glioma is one of the most intractable types of cancer, due to delayed diagnosis at advanced stages. The clinical symptoms of glioma are unclear and due to a variety of glioma subtypes, available low-invasive testing is not effective enough to be introduced into routine medical laboratory practice. Therefore, recent advances in the clinical diagnosis of glioma have focused on liquid biopsy approaches that utilize a wide range of techniques such as next-generation sequencing (NGS), droplet-digital polymerase chain reaction (ddPCR), and quantitative PCR (qPCR). Among all techniques, NGS is the most advantageous diagnostic method. Despite the rapid cheapening of NGS experiments, the cost of such diagnostics remains high. Moreover, high-throughput diagnostics are not appropriate for molecular profiling of gliomas since patients with gliomas exhibit only a few diagnostic markers. In this review, we highlighted all available assays for glioma diagnosing for main pathogenic glioma DNA sequence alterations. In the present study, we reviewed the possibility of integrating routine molecular methods into the diagnosis of gliomas. We state that the development of an affordable assay covering all glioma genetic aberrations could enable early detection and improve patient outcomes. Moreover, the development of such molecular diagnostic kits could potentially be a good alternative to expensive NGS-based approaches.

Phase II study of capecitabine-based concomitant chemoradiation followed by durvalumab as a neoadjuvant strategy in locally advanced rectal cancer: the PANDORA trial

BACKGROUND

This study investigated the efficacy of chemoradiotherapy (CRT) followed by durvalumab as neoadjuvant therapy of locally advanced rectal cancer.

PATIENTS AND METHODS

The PANDORA trial is a prospective, phase II, open-label, single-arm, multicenter study aimed at evaluating the efficacy and safety of preoperative treatment with durvalumab (1500 mg every 4 weeks for three administrations) following long-course radiotherapy (RT) plus concomitant capecitabine (5040 cGy RT in 25-28 fractions over 5 weeks and capecitabine administered at 825 mg/m2 twice daily). The primary endpoint was the pathological complete response (pCR) rate; secondary endpoints were the proportion of clinical complete remissions and safety. The sample size was estimated assuming a null pCR proportion of 0.15 and an alternative pCR proportion of 0.30 (α = 0.05, power = 0.80). The proposed treatment could be considered promising if ≥13 pCRs were observed in 55 patients (EudraCT: 2018-004758-39; NCT04083365).

RESULTS

Between November 2019 and August 2021, 60 patients were accrued, of which 55 were assessable for the study's objectives. Two patients experienced disease progression during treatment. Nineteen out of 55 eligible patients achieved a pCR (34.5%, 95% confidence interval 22.2% to 48.6%). Regarding toxicity related to durvalumab, grade 3 adverse events (AEs) occurred in four patients (7.3%) (diarrhea, skin toxicity, transaminase increase, lipase increase, and pancolitis). Grade 4 toxicity was not observed. In 20 patients (36.4%), grade 1-2 AEs related to durvalumab were observed. The most common were endocrine toxicity (hyper/hypothyroidism), dermatologic toxicity (skin rash), and gastrointestinal toxicity (transaminase increase, nausea, diarrhea, constipation).

CONCLUSION

This study met its primary endpoint showing that CRT followed by durvalumab could increase pCR with a safe toxicity profile. This combination is a promising, feasible strategy worthy of further investigation.

Reliability of panel-based mutational signatures for immune-checkpoint-inhibition efficacy prediction in non-small cell lung cancer

OBJECTIVES

Mutational signatures (MS) are gaining traction for deriving therapeutic insights for immune checkpoint inhibition (ICI). We asked if MS attributions from comprehensive targeted sequencing assays are reliable enough for predicting ICI efficacy in non-small cell lung cancer (NSCLC).

METHODS

Somatic mutations of m = 126 patients were assayed using panel-based sequencing of 523 cancer-related genes. In silico simulations of MS attributions for various panels were performed on a separate dataset of m = 101 whole genome sequenced patients. Non-synonymous mutations were deconvoluted using COSMIC v3.3 signatures and used to test a previously published machine learning classifier.

RESULTS

The ICI efficacy predictor performed poorly with an accuracy of 0.51-0.09+0.09, average precision of 0.52-0.11+0.11, and an area under the receiver operating characteristic curve of 0.50-0.09+0.10. Theoretical arguments, experimental data, and in silico simulations pointed to false negative rates (FNR) related to panel size. A secondary effect was observed, where deconvolution of small ensembles of point mutations lead to reconstruction errors and misattributions.

CONCLUSION

MS attributions from current targeted panel sequencing are not reliable enough to predict ICI efficacy. We suggest that, for downstream classification tasks in NSCLC, signature attributions be based on whole exome or genome sequencing instead.

The Optimal Tumor Mutational Burden Cutoff Value as a Novel Marker for Predicting the Efficacy of Programmed Cell Death-1 Checkpoint Inhibitors in Advanced Gastric Cancer

PURPOSE

The optimal tumor mutational burden (TMB) value for predicting treatment response to programmed cell death-1 (PD-1) checkpoint inhibitors in advanced gastric cancer (AGC) remains unclear. We aimed to investigate the optimal TMB cutoff value that could predict the efficacy of PD-1 checkpoint inhibitors in AGC.

MATERIALS AND METHODS

Patients with AGC who received pembrolizumab or nivolumab between October 1, 2020, and July 27, 2021, at Samsung Medical Center in Korea were retrospectively analyzed. The TMB levels were measured using a next-generation sequencing assay. Based on receiver operating characteristic curve analysis, the TMB cutoff value was determined.

RESULTS

A total 53 patients were analyzed. The TMB cutoff value for predicting the overall response rate (ORR) to PD-1 checkpoint inhibitors was defined as 13.31 mutations per megabase (mt/Mb) with 56% sensitivity and 95% specificity. Based on this definition, 7 (13.2%) patients were TMB-high (TMB-H). The ORR differed between the TMB-low (TMB-L) and TMB-H (8.7% vs. 71.4%, P=0.001). The progression-free survival and overall survival (OS) for 53 patients were 1.93 (95% confidence interval [CI], 1.600-2.268) and 4.26 months (95% CI, 2.992-5.532). The median OS was longer in the TMB-H (20.8 months; 95% CI, 2.292-39.281) than in the TMB-L (3.31 months; 95% CI, 1.604-5.019; P=0.049).

CONCLUSIONS

The TMB cutoff value for predicting treatment response in AGC patients who received PD-1 checkpoint inhibitor monotherapy as salvage treatment was 13.31 mt/Mb. When applying the programmed death ligand-1 status to TMB-H, patients who would benefit from PD-1 checkpoint inhibitors can be selected.

Development of a Somatic Variant Registry in a National Cancer Center: towards Molecular Real World Data preparedness

The Biomedical Research field is currently advancing to develop Clinical Trials and translational projects based on Real World Evidence. To make this transition feasible, clinical centers need to work toward Data Accessibility and Interoperability. This task is particularly challenging when applied to Genomics, that entered in routinary screening in the last years via mostly amplicon-based Next-Generation Sequencing panels. Said experiments produce up to hundreds of features per patient, and their summarized results are often stored in static clinical reports, making critical information inaccessible to automated access and Federated Search consortia. In this study, we present a reanalysis of 4620 solid tumor sequencing samples in five different histology settings. Furthermore, we describe all the Bioinformatics and Data Engineering processes that were put in place in order to create a Somatic Variant Registry able to deal with the large biotechnological variability of routinary Genomics Profiling.

Liquid Biopsy in Lung Cancer: Biomarkers for the Management of Recurrence and Metastasis

Liquid biopsies have emerged as a promising tool for the detection of metastases as well as local and regional recurrence in lung cancer. Liquid biopsy tests involve analyzing a patient's blood, urine, or other body fluids for the detection of biomarkers, including circulating tumor cells or tumor-derived DNA/RNA that have been shed into the bloodstream. Studies have shown that liquid biopsies can detect lung cancer metastases with high accuracy and sensitivity, even before they are visible on imaging scans. Such tests are valuable for early intervention and personalized treatment, aiming to improve patient outcomes. Liquid biopsies are also minimally invasive compared to traditional tissue biopsies, which require the removal of a sample of the tumor for further analysis. This makes liquid biopsies a more convenient and less risky option for patients, particularly those who are not good candidates for invasive procedures due to other medical conditions. While liquid biopsies for lung cancer metastases and relapse are still being developed and validated, they hold great promise for improving the detection and treatment of this deadly disease. Herein, we summarize available and novel approaches to liquid biopsy tests for lung cancer metastases and recurrence detection and describe their applications in clinical practice.

High tumor mutational burden predicts favorable response to anti-PD-(L)1 therapy in patients with solid tumor: a real-world pan-tumor analysis

BACKGROUND

Tumor mutation burden (TMB) is an important biomarker to predict response to anti-PD-L1 treatment across cancer types. TruSight Oncology 500 (TSO500) is currently used globally as a routine assay for TMB.

METHODS

Between 2019 and 2021, 1744 patients with cancer received TSO500 assay as part of a real-world clinical practice at the Samsung Medical Center, and 426 received anti-PD-(L)1 treatment. Correlations between TMB and clinical outcomes of anti-PD-(L)1 were analyzed. Digital spatial profiling (DSP) was used to investigate the tumor immune environment's influence on the treatment response to anti-PD-(L)1 in high TMB (TMB-H) patients (n=8).

RESULTS

The incidence of TMB-H (≥10 mutations (mt)/megabase (Mb)) was 14.7% (n=257). Among TMB-H patients, the most common cancer type was colorectal cancer (n=108, 42.0%), followed by gastric cancer (GC; n=49, 19.1%), bladder cancer (n=21, 8.2%), cholangiocarcinoma (n=21, 8.2%), non-small cell lung cancer (n=17, 6.6%), melanoma (n=8, 3.1%), gallbladder cancer (GBC; n=7, 2.7%), and others (n=26, 10.1%). The response rate to anti-PD-(L)1 therapy was substantially higher in GC (71.4% vs 25.8%), GBC (50.0% vs 12.5%), head and neck cancer (50.0% vs 11.1%), and melanoma (71.4% vs 50.7%) among TMB-H patients when compared with low TMB (TMB-L) (<10 mt/Mb) patients with statistical significance. Additional analysis of patients with TMB ≥16 mt/Mb demonstrated prolonged survival after anti-PD-(L)1 therapy compared with patients with TMB-L (not reached vs 418 days, p=0.03). The benefit of TMB ≥16 mt/Mb was greater when combined with microsatellite status and PD-L1 expression profiles. Among the TMB-H patients, those who responded to anti-PD-L1 therapy had numerous active immune cells that infiltrated the tumor regions during the DSP analysis. Natural killer cells (p=0.04), cytotoxic T cells (p<0.01), memory T cells (p<0.01), naïve memory T cells (p<0.01), and proteins related to T-cell proliferation (p<0.01) were observed in a responder group compared with a non-responder group. In contrast, exhausted T-cell and M2 macrophage counts were increased in the non-responder group.

CONCLUSIONS

The overall incidence of TMB status was analyzed by the TSO500 assay, and TMB-H was observed in 14.7% of the pan-cancer population. In a real-world setting, TMB-H identified by a target sequencing panel seemed to predict response to anti-PD-(L)1 therapy, especially in patients with a higher proportion of immune cells enriched in the tumor region.

Fusobacterium Nucleatum-Induced Tumor Mutation Burden Predicts Poor Survival of Gastric Cancer Patients

Co-infection of Helicobacter pylori and Fusobacterium nucleatum is a microbial biomarker for poor prognosis of gastric cancer patients. Fusobacterium nucleatum is associated with microsatellite instability and the accumulation of mutations in colorectal cancer. Here, we investigated the mutation landscape of Fusobacterium nucleatum-positive resected gastric cancer tissues using Illumina TruSight Oncology 500 comprehensive panel. Sequencing data were processed to identify the small nucleotide variants, small insertions and deletions, and unstable microsatellite sites. The bioinformatic algorithm also calculated copy number gains of preselected genes and tumor mutation burden. The recurrent genetic aberrations were identified in this study cohort. For gene amplification events, ERBB2, cell cycle regulators, and specific FGF ligands and receptors were the most frequently amplified genes. Pathogenic activation mutations of ERBB2, ERBB3, and PIK3CA, as well as loss-of-function of TP53, were identified in multiple patients. Furthermore, Fusobacterium nucleatum infection is positively correlated with a higher tumor mutation burden. Survival analysis showed that the combination of Fusobacterium nucleatum infection and high tumor mutation burden formed an extremely effective biomarker to predict poor prognosis. Our results indicated that the ERBB2-PIK3-AKT-mTOR pathway is frequently activated in gastric cancer and that Fusobacterium nucleatum and high mutation burden are strong biomarkers of poor prognosis for gastric cancer patients.

Assessment of Two Commercial Comprehensive Gene Panels for Personalized Cancer Treatment

(1) Background: Analysis of tumor DNA by next-generation sequencing (NGS) plays various roles in the classification and management of cancer. This study aimed to assess the performance of two similar and large, comprehensive gene panels with a focus on clinically relevant variant detection and tumor mutation burden (TMB) assessment; (2) Methods: DNA from 19 diagnostic small cell lung cancer biopsies and an AcroMetrix™ assessment sample with >500 mutations were sequenced using Oncomine™ Comprehensive Assay Plus (OCAP) on the Ion Torrent platform and TruSight Oncology 500 Assay (TSO500) on the Illumina platform; (3) Results: OCAP and TSO500 achieved comparable NGS quality, such as mean read coverage and mean coverage uniformity. A total of 100% of the variants in the diagnostic samples and 80% of the variants in the AcroMetrix™ assessment sample were detected by both panels, and the panels reported highly similar variant allele frequency. A proportion of 14/19 (74%) samples were classified in the same TMB category; (4) Conclusions: Comparable results were obtained using OCAP and TSO500, suggesting that both panels could be applied to screen patients for enrolment in personalized cancer treatment trials.

A Computational Framework for Comprehensive Genomic Profiling in Solid Cancers: The Analytical Performance of a High-Throughput Assay for Small and Copy Number Variants

In January 2022, our institution launched a comprehensive cancer genome profiling program on 10 cancer types using a non-IVD solution named the TruSight Oncology 500 Assay provided by Illumina^®. The assay analyzes both DNA and RNA, identifying Single-Nucleotide Variants (SNV)s and Insertion-Deletion (InDel) in 523 genes, as well as known and unknown fusions and splicing variants in 55 genes and Copy Number Alterations (CNVs), Mutational Tumor Burden (MTB) and Microsatellite Instability (MSI). According to the current European IVD Directive 98/79/EC, an internal validation was performed before running the test. A dedicated open-source bioinformatics pipeline was developed for data postprocessing, panel assessment and embedding in high-performance computing framework using the container technology to ensure scalability and reproducibility. Our protocols, applied to 71 DNA and 64 RNA samples, showed full agreement between the TruSight Oncology 500 assay and standard approaches, with only minor limitations, allowing to routinely perform our protocol in patient screening.

Predictive Biomarkers for Immunotherapy in Lung Cancer: Perspective From the International Association for the Study of Lung Cancer Pathology Committee

Immunotherapy including immune checkpoint inhibitors (ICIs) has become the backbone of treatment for most lung cancers with advanced or metastatic disease. In addition, they have increasingly been used for early stage tumors in neoadjuvant and adjuvant settings. Unfortunately, however, only a subset of patients experiences meaningful response to ICIs. Although programmed death-ligand 1 (PD-L1) protein expression by immunohistochemistry (IHC) has played a role as the principal predictive biomarker for immunotherapy, its performance may not be optimal, and it suffers multiple practical issues with different companion diagnostic assays approved. Similarly, tumor mutational burden (TMB) has multiple technical issues as a predictive biomarker for ICIs. Now, ongoing research on tumor- and host immune-specific factors has identified immunotherapy biomarkers that may provide better response and prognosis prediction, in particular in a multimodal approach. This review by the International Association for the Study of Lung Cancer Pathology Committee provides an overview of various immunotherapy biomarkers, including updated data on PD-L1 IHC and TMB, and assessments of neoantigens, genetic and epigenetic signatures, immune microenvironment by IHC and transcriptomics, and microbiome and pathologic response to neoadjuvant immunotherapies. The aim of this review is to underline the efficacy of new individual or combined predictive biomarkers beyond PD-L1 IHC and TMB.

Cutting-Edge AI Technologies Meet Precision Medicine to Improve Cancer Care

To provide precision medicine for better cancer care, researchers must work on clinical patient data, such as electronic medical records, physiological measurements, biochemistry, computerized tomography scans, digital pathology, and the genetic landscape of cancer tissue. To interpret big biodata in cancer genomics, an operational flow based on artificial intelligence (AI) models and medical management platforms with high-performance computing must be set up for precision cancer genomics in clinical practice. To work in the fast-evolving fields of patient care, clinical diagnostics, and therapeutic services, clinicians must understand the fundamentals of the AI tool approach. Therefore, the present article covers the following four themes: (i) computational prediction of pathogenic variants of cancer susceptibility genes; (ii) AI model for mutational analysis; (iii) single-cell genomics and computational biology; (iv) text mining for identifying gene targets in cancer; and (v) the NVIDIA graphics processing units, DRAGEN field programmable gate arrays systems and AI medical cloud platforms in clinical next-generation sequencing laboratories. Based on AI medical platforms and visualization, large amounts of clinical biodata can be rapidly copied and understood using an AI pipeline. The use of innovative AI technologies can deliver more accurate and rapid cancer therapy targets.

Diagnostic Validation of a Comprehensive Targeted Panel for Broad Mutational and Biomarker Analysis in Solid Tumors

The use of targeted Next Generation Sequencing (NGS) for the diagnostic screening of somatic variants in solid tumor samples has proven its high clinical value. Because of the large number of ongoing clinical trials for a multitude of variants in a growing number of genes, as well as the detection of proven and emerging pan-cancer biomarkers including microsatellite instability (MSI) and tumor mutation burden (TMB), the currently employed diagnostic gene panels will become vastly insufficient in the near future. Here, we describe the validation and implementation of the hybrid capture-based comprehensive TruSight Oncology (TSO500) assay that is able to detect single-nucleotide variants (SNVs) and subtle deletions and insertions (indels) in 523 tumor-associated genes, copy-number variants (CNVs) of 69 genes, fusions with 55 cancer driver genes, and MSI and TMB. Extensive validation of the TSO500 assay was performed on DNA or RNA from 170 clinical samples with neoplastic content down to 10%, using multiple tissue and specimen types. Starting with 80 ng DNA and 40 ng RNA extracted from formalin-fixed and paraffine-embedded (FFPE) samples revealed a precision and accuracy >99% for all variant types. The analytical sensitivity and specificity were at least 99% for SNVs, indels, CNVs, MSI, and gene rearrangements. For TMB, only values around the threshold could yield a deviating outcome. The limit-of-detection for SNVs and indels was well below the set threshold of 5% variant allele frequency (VAF). This validated comprehensive genomic profiling assay was then used to screen 624 diagnostic samples, and its success rate for adoption in a clinical diagnostic setting of broad solid tumor screening was assessed on this cohort.