The impact of tumor profiling approaches and genomic data strategies for cancer precision medicine

Next-generation sequencing-based evaluation of the actionable landscape of genomic alterations in solid tumors: the "MOZART" prospective observational study

BACKGROUND

The identification of the most appropriate targeted therapies for advanced cancers is challenging. We performed a molecular profiling of metastatic solid tumors utilizing a comprehensive next-generation sequencing (NGS) assay to determine genomic alterations' type, frequency, actionability, and potential correlations with PD-L1 expression.

METHODS

A total of 304 adult patients with heavily pretreated metastatic cancers treated between January 2019 and March 2021 were recruited. The CLIA-/UKAS-accredit Oncofocus assay targeting 505 genes was used on newly obtained or archived biopsies. Chi-square, Kruskal-Wallis, and Wilcoxon rank-sum tests were used where appropriate. Results were significant for P < .05.

RESULTS

A total of 237 tumors (78%) harbored potentially actionable genomic alterations. Tumors were positive for PD-L1 in 68.9% of cases. The median number of mutant genes/tumor was 2.0 (IQR: 1.0-3.0). Only 34.5% were actionable ESCAT Tier I-II with different prevalence according to cancer type. The DNA damage repair (14%), the PI3K/AKT/mTOR (14%), and the RAS/RAF/MAPK (12%) pathways were the most frequently altered. No association was found among PD-L1, ESCAT, age, sex, and tumor mutational status. Overall, 62 patients underwent targeted treatment, with 37.1% obtaining objective responses. The same molecular-driven treatment for different cancer types could be associated with opposite clinical outcomes.

CONCLUSIONS

We highlight the clinical value of molecular profiling in metastatic solid tumors using comprehensive NGS-based panels to improve treatment algorithms in situations of uncertainty and facilitate clinical trial recruitment. However, interpreting genomic alterations in a tumor type-specific manner is critical.

Recommendations for Tumor Mutational Burden Assay Validation and Reporting: A Joint Consensus Recommendation of the Association for Molecular Pathology, College of American Pathologists, and Society for Immunotherapy of Cancer

Tumor mutational burden (TMB) has been recognized as a predictive biomarker for immunotherapy response in several tumor types. Several laboratories offer TMB testing, but there is significant variation in how TMB is calculated, reported, and interpreted among laboratories. TMB standardization efforts are underway, but no published guidance for TMB validation and reporting is currently available. Recognizing the current challenges of clinical TMB testing, the Association for Molecular Pathology convened a multidisciplinary collaborative working group with representation from the American Society of Clinical Oncology, the College of American Pathologists, and the Society for the Immunotherapy of Cancer to review the laboratory practices surrounding TMB and develop recommendations for the analytical validation and reporting of TMB testing based on survey data, literature review, and expert consensus. These recommendations encompass pre-analytical, analytical, and postanalytical factors of TMB analysis, and they emphasize the relevance of comprehensive methodological descriptions to allow comparability between assays.

Microsatellite Instability, Mismatch Repair, and Tumor Mutation Burden in Lung Cancer

Since US Food and Drug Administration approval of programmed death ligand 1 (PD-L1) as the first companion diagnostic for immune checkpoint inhibitors (ICIs) in non-small cell lung cancer, many patients have experienced increased overall survival. To improve selection of ICI responders versus nonresponders, microsatellite instability/mismatch repair deficiency (MSI/MMR) and tumor mutation burden (TMB) came into play. Clinical data show PD-L1, MSI/MMR, and TMB are independent predictive immunotherapy biomarkers. Harmonization of testing methodologies, optimization of assay design, and results analysis are ongoing. Future algorithms to determine immunotherapy eligibility might involve complementary use of current and novel biomarkers. Artificial intelligence could facilitate algorithm implementation to convert complex genetic data into recommendations for specific ICIs.

Analytical and Clinical Validation of a Target-Enhanced Whole Genome Sequencing-Based Comprehensive Genomic Profiling Test

Evaluation of the test performance of the Target enhanced whole-genome sequencing (TE-WGS) assay for comprehensive oncology genomic profiling. The analytical validation of the assay included sensitivity and specificity for single nucleotide variants (SNVs), insertions/deletions (indels), and structural variants (SVs), revealing a revealed a sensitivity of 99.8% for SNVs and 99.2% for indels. The positive predictive value (PPV) was 99.3% SNVs and 98.7% indels. Clinical validation was benchmarked against established orthogonal methods and demonstrated high concordance with reference methods. TE-WGS provides insights beyond targeted panels by comprehensive analysis of key biomarkers and the entire genome encompassing both germline and somatic findings.

Disparities in care of older adults of color with cancer: A narrative review

This review describes the barriers and challenges faced by older adults of color with cancer and highlights methods to improve their overall care. In the next decade, cancer incidence rates are expected to increase in the United States for people aged ≥65 years. A large proportion will be older adults of color who often have worse outcomes than older White patients. Many issues contribute to racial disparities in older adults, including biological factors and social determinants of health (SDOH) related to healthcare access, socioeconomic concerns, systemic racism, mistrust, and the neighborhood where a person lives. These disparities are exacerbated by age-related challenges often experienced by older adults, such as decreased functional status, impaired cognition, high rates of comorbidities and polypharmacy, poor nutrition, and limited social support. Additionally, underrepresentation of both patients of color and older adults in cancer clinical research results in a lack of adequate data to guide the management of these patients. Use of geriatric assessments (GA) can aid providers in uncovering age-related concerns and personalizing interventions for older patients. Research demonstrates the ability of GA-directed care to result in fewer treatment-related toxicities and improved quality of life, thus supporting the routine incorporation of validated GA into these patients' care. GA can be enhanced by including evaluation of SDOH, which can help healthcare providers understand and address the needs of older adults of color with cancer who face disparities related to their age and race.

Enhancing the quality of panel-based tumor mutation burden assessment: a comprehensive study of real-world and in-silico outcomes

Targeted panel-based tumor mutation burden (TMB) assays are widely employed to guide immunotherapy for patients with solid tumors. However, the accuracy and consistency of this method can be compromised due to the variability in technical details across different laboratories, particularly in terms of panel size, somatic mutation detection and TMB calculation rules. Currently, systematic evaluations of the impact of these technical factors on existing assays and best practice recommendations remain lacking. We assessed the performance of 50 participating panel-based TMB assays involving 38 unique methods using cell line samples. In silico experiments utilizing TCGA MC3 datasets were performed to further dissect the impact of technical factors. Here we show that the panel sizes beyond 1.04 Mb and 389 genes are necessary for the basic discrete accuracy, as determined by over 40,000 synthetic panels. The somatic mutation detection should maintain a reciprocal gap of recall and precision less than 0.179 for reliable psTMB calculation results. The inclusion of synonymous, nonsense and hotspot mutations could enhance the accuracy of panel-based TMB assay. A 5% variant allele frequency cut-off is suitable for TMB assays using tumor samples with at least 20% tumor purity. In conclusion, this multicenter study elucidates the major technical factors as sources of variability in panel-based TMB assays and proposed comprehensive recommendations for the enhancement of accuracy and consistency. These findings will assist clinical laboratories in optimizing the methodological details through bioinformatic experiments to enhance the reliability of panel-based methods.

Development of Tumor Markers for Breast Cancer Immunotherapy

Although breast cancer treatment has been developed remarkably in recent years, it remains the primary cause of death among women. Immune checkpoint blockade therapy has significantly altered the way breast cancer is treated, although not all patients benefit from the changes. At present, the most effective mechanism of immune checkpoint blockade application in malignant tumors is not clear and efficacy may be influenced by many factors, including host, tumor, and tumor microenvironment dynamics. Therefore, there is a pressing need for tumor immunomarkers that can be used to screen patients and help determine which of them would benefit from breast cancer immunotherapy. At present, no single tumor marker can predict treatment efficacy with sufficient accuracy. Multiple markers may be combined to more accurately pinpoint patients who will respond favorably to immune checkpoint blockade medication. In this review, we have examined the breast cancer treatments, developments in research on the role of tumor markers in maximizing the clinical efficacy of immune checkpoint inhibitors, prospects for the identification of novel therapeutic targets, and the creation of individualized treatment plans. We also discuss how tumor markers can provide guidance for clinical practice.

Safety and efficacy of canakinumab treatment for undifferentiated autoinflammatory diseases: the data of a retrospective cohort two-centered study

Introduction

The blockade of interleukine-1 (anakinra and canakinumab) is a well-known highly effective tool for monogenic autoinflammatory diseases (AIDs), such as familial Mediterranean fever, tumor necrosis factor receptor-associated periodic syndrome, hyperimmunoglobulinaemia D syndrome, and cryopyrin-associated periodic syndrome, but this treatment has not been assessed for patients with undifferentiated AIDs (uAIDs). Our study aimed to assess the safety and efficacy of canakinumab for patients with uAIDs.

Methods

Information on 32 patients with uAIDs was retrospectively collected and analyzed. Next-generation sequencing and Federici criteria were used for the exclusion of the known monogenic AID.

Results

The median age of the first episode was 2.5 years (IQR: 1.3; 5.5), that of the disease diagnosis was 5.7 years (IQR: 2.5;12.7), and that of diagnostic delay was 1.1 years (IQR: 0.4; 6.1). Patients had variations in the following genes: IL10, NLRP12, STAT2, C8B, LPIN2, NLRC4, PSMB8, PRF1, CARD14, IFIH1, LYST, NFAT5, PLCG2, COPA, IL23R, STXBP2, IL36RN, JAK1, DDX58, LACC1, LRBA, TNFRSF11A, PTHR1, STAT4, TNFRSF1B, TNFAIP3, TREX1, and SLC7A7. The main clinical features were fever (100%), rash (91%; maculopapular predominantly), joint involvement (72%), splenomegaly (66%), hepatomegaly (59%), lymphadenopathy (50%), myalgia (28%), heart involvement (31%), intestinal involvement (19%); eye involvement (9%), pleuritis (16%), ascites (6%), deafness, hydrocephalia (3%), and failure to thrive (25%). Initial treatment before canakinumab consisted of non-biologic therapies: non-steroidal anti-inflammatory drugs (NSAID) (91%), corticosteroids (88%), methotrexate (38%), intravenous immunoglobulin (IVIG) (34%), cyclosporine A (25%), colchicine (6%) cyclophosphamide (6%), sulfasalazine (3%), mycophenolate mofetil (3%), hydroxychloroquine (3%), and biologic drugs: tocilizumab (62%), sarilumab, etanercept, adalimumab, rituximab, and infliximab (all 3%). Canakinumab induced complete remission in 27 patients (84%) and partial remission in one patient (3%). Two patients (6%) were primary non-responders, and two patients (6%) further developed secondary inefficacy. All patients with partial efficacy or inefficacy were switched to tocilizumab (n = 4) and sarilumab (n = 1). The total duration of canakinumab treatment was 3.6 (0.1; 8.7) years. During the study, there were no reported Serious Adverse Events (SAEs). The patients experienced non-frequent mild respiratory infections at a rate that is similar as before canakinumab is administered. Additionally, one patient developed leucopenia, but it was not necessary to stop canakinumab for this patient.

Conclusion

The treatment of patients with uAIDs using canakinumab was safe and effective. Further randomized clinical trials are required to confirm the efficacy and safety.

Biomarker-Driven Personalization of Neoadjuvant Immunotherapy in Melanoma

The introduction of immunotherapy has ushered in a new era of anticancer therapy for many cancer types including melanoma. Given the increasing development of novel compounds and combinations and the investigation in earlier disease stages, the need grows for biomarker-based treatment personalization. Stage III melanoma is one of the front-runners in the neoadjuvant immunotherapy field, facilitating quick biomarker identification by its immunogenic capacity, homogeneous patient population, and reliable efficacy readout. In this review, we discuss potential biomarkers for response prediction to neoadjuvant immunotherapy, and how the neoadjuvant melanoma platform could pave the way for biomarker identification in other tumor types.

SIGNIFICANCE

In accordance with the increasing rate of therapy development, the need for biomarker-driven personalized treatments grows. The current landscape of neoadjuvant treatment and biomarker development in stage III melanoma can function as a poster child for these personalized treatments in other tumors, assisting in the development of new biomarker-based neoadjuvant trials. This will contribute to personalized benefit-risk predictions to identify the most beneficial treatment for each patient.

The prognostic value of TMB in early-stage non-small cell lung cancer: a systematic review and meta-analysis

Background

Tumor mutation burden (TMB) has been validated as a predictive biomarker for immunotherapy response and survival in numerous cancer types. Limited data is available on the inherent prognostic role of TMB in early-stage tumors.

Objective

To evaluate the prognostic role of TMB in early-stage, resected non-small cell lung cancer (NSCLC).

Design

Systematic review and meta-analysis of pertinent prospective and retrospective studies.

Data sources and methods

Publication search was performed in PubMed, Embase, Cochrane Library, and Web of Science databases. Based on the level of heterogeneity, a random- or fixed-effects model was used to calculate pooled effects of hazard ratio (HR) for overall survival (OS) and disease-free survival (DFS). The source of heterogeneity was investigated using sensitivity analysis, subgroup analysis, and publication bias assessment.

Results

Ten studies comprising 2520 patients were included in this analysis. There was no statistically significant difference in OS (HR, 1.18, 95% CI, 0.70, 1.33; p 0.53, I2 = 80%; phet < 0.0001) and DFS (HR, 1.18, 95% CI, 0.91, 1.52; p = 0.53, I2 = 75%; phet = 0.0001) between the high-TMB and low-TMB group. Subgroup analyses indicated that East Asian ethnicity, and TMB detected using whole exome sequencing, and studies with <100 patients had poor DFS in the high-TMB group.

Conclusion

The inherent prognostic role of TMB is limited in early-stage NSCLC. Ethnic differences in mutation burden must be considered while designing future trials on neoadjuvant immunotherapy. Further research in the harmonization and standardization of panel-based TMB is essential for its widespread clinical utility.Registration: CRD42023392846.

Analytic validation of NeXT Dx™, a comprehensive genomic profiling assay

We describe the analytic validation of NeXT Dx, a comprehensive genomic profiling assay to aid therapy and clinical trial selection for patients diagnosed with solid tumor cancers. Proprietary methods were utilized to perform whole exome and whole transcriptome sequencing for detection of single nucleotide variants (SNVs), insertions/deletions (indels), copy number alterations (CNAs), and gene fusions, and determination of tumor mutation burden and microsatellite instability. Variant calling is enhanced by sequencing a patient-specific normal sample from, for example, a blood specimen. This provides highly accurate somatic variant calls as well as the incidental reporting of pathogenic and likely pathogenic germline alterations. Fusion detection via RNA sequencing provides more extensive and accurate fusion calling compared to DNA-based tests. NeXT Dx features the proprietary Accuracy and Content Enhanced technology, developed to optimize sequencing and provide more uniform coverage across the exome. The exome was validated at a median sequencing depth of >500x. While variants from 401 cancer-associated genes are currently reported from the assay, the exome/transcriptome assay is broadly validated to enable reporting of additional variants as they become clinically relevant. NeXT Dx demonstrated analytic sensitivities as follows: SNVs (99.4%), indels (98.2%), CNAs (98.0%), and fusions (95.8%). The overall analytic specificity was >99.0%.

Biomarkers for Predicting Response to Personalized Immunotherapy in Gastric Cancer

Despite advances in diagnostic imaging, surgical techniques, and systemic therapy, gastric cancer (GC) is the third leading cause of cancer-related death worldwide. Unfortunately, molecular heterogeneity and, consequently, acquired resistance in GC are the major causes of failure in the development of biomarker-guided targeted therapies. However, by showing promising survival benefits in some studies, the recent emergence of immunotherapy in GC has had a significant impact on treatment-selectable procedures. Immune checkpoint inhibitors (ICIs), widely indicated in the treatment of several malignancies, target inhibitory receptors on T lymphocytes, including the programmed cell death protein (PD-1)/programmed death-ligand 1 (PD-L1) axis and cytotoxic T-lymphocyte-associated protein 4 (CTLA4), and release effector T-cells from negative feedback signals. In this article, we review currently available predictive biomarkers (including PD-L1, microsatellite instability, Epstein-Barr virus, and tumor mutational burden) that affect the ICI treatment response, focusing on PD-L1 expression. We further briefly describe other potential biomarkers or mechanisms for predicting the response to ICIs in GC. This review may facilitate the expansion of the understanding of biomarkers for predicting the response to ICIs and help select the appropriate therapeutic approaches for patients with GC.

Japanese Society of Medical Oncology/Japan Society of Clinical Oncology/Japanese Society of Pediatric Hematology/Oncology-led clinical recommendations on the diagnosis and use of immunotherapy in patients with high tumor mutational burden tumors

The development of novel antitumor agents and accompanying biomarkers has improved survival across several tumor types. Previously, we developed recommendations for tumor-agnostic treatments in patients with solid tumors with DNA mismatch repair deficient or neurotrophic receptor tyrosine kinase fusions. Recently, immune checkpoint inhibitors have shown efficacy in patient with tumor mutation burden-high (TMB-H) solid tumors and have been established as a third tumor-agnostic agent, making it necessary to develop the guideline prioritized for these patients. Clinical questions regarding medical care were formulated for patients with TMB-H advanced solid tumors. Relevant publications were searched by PubMed and Cochrane Database. Critical publications and conference reports were added manually. Systematic reviews were performed for each clinical question for the purpose of developing clinical recommendations. The committee members identified by Japan Society of Clinical Oncology (JSCO), Japanese Society of Medical Oncology (JSMO), and Japanese society of pediatric hematology/oncology (JSPHO) voted to determine the level of each recommendation considering the strength of evidence, expected risks and benefits to patients, and other related factors. Thereafter, a peer review by experts nominated from JSCO, JSMO, and JSPHO, and the public comments among all societies' members was done. The current guideline describes three clinical questions and seven recommendations for whom, when, and how TMB should be tested, and what is recommended for patients with TMB-H advanced solid tumors. In this guideline, the committee proposed seven recommendations for performing TMB testing properly to select patients who are likely to benefit from immunotherapy.

Management of patients with presumed germline pathogenic variant from tumor-only genomic sequencing: A retrospective analysis at a single facility

Cancer treatment is increasingly evolving toward personalized medicine, which sequences numerous cancer-related genes and identifies therapeutic targets. On the other hand, patients with germline pathogenic variants (GPV) have been identified as secondary findings (SF) and oncologists have been urged to handle them. All SF disclosure considerations for patients are addressed and decided at the molecular tumor boards (MTB) in the facility. In this study, we retrospectively summarized the results of all cases in which comprehensive genomic profiling (CGP) test was conducted at our hospital, and discussed the possibility of presumed germline pathogenic variants (PGPV) at MTB. MTB recommended confirmatory testing for 64 patients. Informed consent was obtained from attending physicians for 53 of them, 30 patients requested testing, and 17 patients tested positive for a confirmatory test. Together with already known variants, 4.5 % of the total confirmed in this cohort. Variants verified in this study were BRCA1 (n = 12), BRCA2 (n = 6), MSH2 (n = 2), MSH6 (n = 2), WT1 (n = 2), TP53, MEN1, CHEK2, MLH1, TSC2, PTEN, RB1, and SMARCB1. There was no difference in the tumor's VAF between confirmed positive and negative cases for variants determined as PGPV by MTB. Current results demonstrate the actual number of cases until confirmatory germline test for patients with PGPV from tumor-only CGP test through the discussion at the MTB. The practical results at this single facility will serve as a guide for the management of the selection and distribution of SF in the genome analysis.

Liquid biopsy on the horizon in immunotherapy of non-small cell lung cancer: current status, challenges, and perspectives

Non-small cell lung cancer (NSCLC) is one of the most threatening malignancies to human health and life. In most cases, patients with NSCLC are already at an advanced stage when they are diagnosed. In recent years, lung cancer has made great progress in precision therapy, but the efficacy of immunotherapy is unstable, and its response rate varies from patient to patient. Several biomarkers have been proposed to predict the outcomes of immunotherapy, such as programmed cell death-ligand 1 (PD-L1) expression and tumor mutational burden (TMB). Nevertheless, the detection assays are invasive and demanding on tumor tissue. To effectively predict the outcomes of immunotherapy, novel biomarkers are needed to improve the performance of conventional biomarkers. Liquid biopsy is to capture and detect circulating tumor cells (CTCs), circulating tumor DNA (ctDNA) and exosomes in body fluids, such as blood, saliva, urine, pleural fluid and cerebrospinal fluid as samples from patients, so as to make analysis and diagnosis of cancer and other diseases. The application of liquid biopsy provides a new possible solution, as it has several advantages such as non-invasive, real-time dynamic monitoring, and overcoming tumor heterogeneity. Liquid biopsy has shown predictive value in immunotherapy, significantly improving the precision treatment of lung cancer patients. Herein, we review the application of liquid biopsy in predicting the outcomes of immunotherapy in NSCLC patients, and discuss the challenges and future directions in this field.

Immunotherapeutic Approaches in Ovarian Cancer

Ovarian cancer (OC) is gynecological cancer, and diagnosis and treatment are continuously advancing. Next-generation sequencing (NGS)-based diagnoses have emerged as novel methods for identifying molecules and pathways in cancer research. The NGS-based applications have expanded in OC research for early detection and identification of aberrant genes and dysregulation pathways, demonstrating comprehensive views of the entire transcriptome, such as fusion genes, genetic mutations, and gene expression profiling. Coinciding with advances in NGS-based diagnosis, treatment strategies for OC, such as molecular targeted therapy and immunotherapy, have also advanced. Immunotherapy is effective against many other cancers, and its efficacy against OC has also been demonstrated at the clinical phase. In this review, we describe several NGS-based applications for therapeutic targets of OC, and introduce current immunotherapeutic strategies, including vaccines, checkpoint inhibitors, and chimeric antigen receptor (CAR)-T cell transplantation, for effective diagnosis and treatment of OC.

A Clinician's Guide to Bioinformatics for Next-Generation Sequencing

Next-generation sequencing (NGS) technologies are high-throughput methods for DNA sequencing and have become a widely adopted tool in cancer research. The sheer amount and variety of data generated by NGS assays require sophisticated computational methods and bioinformatics expertise. In this review, we provide background details of NGS technology and basic bioinformatics concepts for the clinician investigator interested in cancer research applications, with a focus on DNA-based approaches. We introduce the general principles of presequencing library preparation, postsequencing alignment, and variant calling. We also highlight the common variant annotations and NGS applications for other molecular data types. Finally, we briefly discuss the revealed utility of NGS methods in NSCLC research and study design considerations for research studies that aim to leverage NGS technologies for clinical care.

Genomic disparities between cancers in adolescent and young adults and in older adults

Cancers cause significant mortality and morbidity in adolescents and young adults (AYAs), but their biological underpinnings are incompletely understood. Here, we analyze clinical and genomic disparities between AYAs and older adults (OAs) in more than 100,000 cancer patients. We find significant differences in clinical presentation between AYAs and OAs, including sex, metastasis rates, race and ethnicity, and cancer histology. In most cancer types, AYA tumors show lower mutation burden and less genome instability. Accordingly, most cancer genes show less mutations and copy number changes in AYAs, including the noncoding TERT promoter mutations. However, CTNNB1 and BRAF mutations are consistently overrepresented in AYAs across multiple cancer types. AYA tumors also exhibit more driver gene fusions that are frequently observed in pediatric cancers. We find that histology is an important contributor to genetic disparities between AYAs and OAs. Mutational signature analysis of hypermutators shows stronger endogenous mutational processes such as MMR-deficiency but weaker exogenous processes such as tobacco exposure in AYAs. Finally, we demonstrate a panoramic view of clinically actionable genetic events in AYA tumors.

Ancestry-driven recalibration of tumor mutational burden and disparate clinical outcomes in response to immune checkpoint inhibitors

The immune checkpoint inhibitor (ICI) pembrolizumab is US FDA approved for treatment of solid tumors with high tumor mutational burden (TMB-high; ≥10 variants/Mb). However, the extent to which TMB-high generalizes as an accurate biomarker in diverse patient populations is largely unknown. Using two clinical cohorts, we investigated the interplay between genetic ancestry, TMB, and tumor-only versus tumor-normal paired sequencing in solid tumors. TMB estimates from tumor-only panels substantially overclassified individuals into the clinically important TMB-high group due to germline contamination, and this bias was particularly pronounced in patients with Asian/African ancestry. Among patients with non-small cell lung cancer treated with ICIs, those misclassified as TMB-high from tumor-only panels did not associate with improved outcomes. TMB-high was significantly associated with improved outcomes only in European ancestries and merits validation in non-European ancestry populations. Ancestry-aware tumor-only TMB calibration and ancestry-diverse biomarker studies are critical to ensure that existing disparities are not exacerbated in precision medicine.

Deriving tumor purity from cancer next generation sequencing data: applications for quantitative ERBB2 (HER2) copy number analysis and germline inference of BRCA1 and BRCA2 mutations

Tumor purity, or the relative contribution of tumor cells out of all cells in a pathological specimen, influences mutation identification and clinical interpretation of cancer panel next generation sequencing results. Here, we describe a method of calculating tumor purity using pathologist-guided copy number analysis from sequencing data. Molecular calculation of tumor purity showed strong linear correlation with purity derived from driver KRAS or BRAF variant allele fractions in colorectal cancers (R² = 0.79) compared to histological estimation in the same set of colorectal cancers (R² = 0.01) and in a broader dataset of cancers with various diagnoses (R² = 0.35). We used calculated tumor purity to quantitate ERBB2 copy number in breast carcinomas with equivocal immunohistochemical staining and demonstrated strong correlation with fluorescence in situ hybridization (R² = 0.88). Finally, we used calculated tumor purity to infer the germline status of variants in breast and ovarian carcinomas with concurrent germline testing. Tumor-only next generation sequencing correctly predicted the somatic versus germline nature of 26 of 26 (100%) pathogenic TP53, BRCA1 and BRCA2 variants. In this article, we describe a framework for calculating tumor purity from cancer next generation sequencing data. Accurate tumor purity assessment can be assimilated into interpretation pipelines to derive clinically useful information from cancer genomic panels.

Effect of Antigen Retrieval on Genomic DNA From Immunodissected Samples

Immunohistochemical (IHC) staining is an established technique for visualizing proteins in tissue sections for research studies and clinical applications. IHC is increasingly used as a targeting strategy for procurement of labeled cells via tissue microdissection, including immunodissection, computer-aided laser dissection (CALD), expression microdissection (xMD), and other techniques. The initial antigen retrieval (AR) process increases epitope availability and improves staining characteristics; however, the procedure can damage DNA. To better understand the effects of AR on DNA quality and quantity in immunodissected samples, both clinical specimens (KRAS gene mutation positive cases) and model system samples (lung cancer patient-derived xenograft tissue) were subjected to commonly employed AR methods (heat induced epitope retrieval [HIER], protease digestion) and the effects on DNA were assessed by Qubit, fragment analysis, quantitative PCR, digital droplet PCR (ddPCR), library preparation, and targeted sequencing. The data showed that HIER resulted in optimal IHC staining characteristics, but induced significant damage to DNA, producing extensive fragmentation and decreased overall yields. However, neither of the AR methods combined with IHC prevented ddPCR amplification of small amplicons and gene mutations were successfully identified from immunodissected clinical samples. The results indicate for the first time that DNA recovered from immunostained slides after standard AR and IHC processing can be successfully employed for genomic mutation analysis via ddPCR and next-generation sequencing (NGS) short-read methods.

Addition of Germline Testing to Tumor-Only Sequencing Improves Detection of Pathogenic Germline Variants in Men With Advanced Prostate Cancer

PURPOSE

Guidelines recommend somatic and germline testing for men with advanced prostate cancer (PCa). Barriers to widespread implementation result in underutilization of germline testing. Somatic testing alone risks missing pathogenic germline variants (PGVs). We sought to determine whether the addition of germline testing to tumor-only sequencing improves detection of PGVs in men with advanced PCa. Secondarily, we sought to define the added value of combining somatic and germline testing to optimize detection of clinically actionable alterations.

PATIENTS AND METHODS

We analyzed results of independent germline testing and tumor-only sequencing from 100 men with advanced PCa from a prospective clinical trial (ClinicalTrials.gov identifier: NCT03328091). The primary outcome was the proportion of PGVs not reported with tumor-only sequencing. The secondary outcome was the association of locus-specific loss of heterozygosity for PGVs in homologous recombination genes with clinical-genomic features.

RESULTS

In the 100 men who underwent germline testing and tumor-only sequencing, 24 PGVs were identified, 17 of which were clinically actionable, in 23 patients. Tumor-only sequencing failed to report four (17%) of the PGVs. One additional PGV (4.2%) had variant allele frequency on tumor-sequencing below the threshold for follow-up germline testing. When integrating tumor-only sequencing with germling testing results, 33% of patients harbored clinically actionable alterations. Rates of locus-specific loss of heterozygosity were higher for BRCA2 PGVs in castration-resistant PCa than PGVs in other homologous recombination genes in hormone-sensitive PCa (P = .029).

CONCLUSION

Tumor-only sequencing failed to report more than 20% of PGVs in men with advanced PCa. These findings strongly support guideline recommendations for universal germline and somatic testing in this population. Combining tumor and germline sequencing doubled the chance of detecting a clinically actionable alteration.

Automated next-generation profiling of genomic alterations in human cancers

The lack of validated, distributed comprehensive genomic profiling assays for patients with cancer inhibits access to precision oncology treatment. To address this, we describe elio tissue complete, which has been FDA-cleared for examination of 505 cancer-related genes. Independent analyses of clinically and biologically relevant sequence changes across 170 clinical tumor samples using MSK-IMPACT, FoundationOne, and PCR-based methods reveals a positive percent agreement of >97%. We observe high concordance with whole-exome sequencing for evaluation of tumor mutational burden for 307 solid tumors (Pearson r = 0.95) and comparison of the elio tissue complete microsatellite instability detection approach with an independent PCR assay for 223 samples displays a positive percent agreement of 99%. Finally, evaluation of amplifications and translocations against DNA- and RNA-based approaches exhibits >98% negative percent agreement and positive percent agreement of 86% and 82%, respectively. These methods provide an approach for pan-solid tumor comprehensive genomic profiling with high analytical performance.

Associations of HER2 Mutation With Immune-Related Features and Immunotherapy Outcomes in Solid Tumors

Background

HER2 is one of the most extensively studied oncogenes in solid tumors. However, the association between tumor microenvironment (TME) and HER2 mutation remains elusive, and there are no specific therapies for HER2-mutated tumors. Immune checkpoint inhibitors (ICIs) have been approved for some tumor subgroups that lack targeted therapies, while their effects are still unclear in HER2-mutated tumors. We examined whether HER2 mutation impacts treatment outcomes of ICIs in solid tumors via its association with anticancer immunity.

Methods

Multi-omics data of solid tumors from The Cancer Genome Atlas (TCGA), the Asian Cancer Research Group and the Affiliated Hospital of Jiangsu University were used to analyze the association between HER2 mutations and tumor features. Data of patients with multiple microsatellite-stable solid tumors, who were treated by ICIs including antibodies against programmed cell death-1 (PD-1), programmed cell death ligand-1 (PD-L1), or cytotoxic T lymphocyte-associated protein 4 (CTLA-4) in eight studies, were collected to investigate the effects of HER2 mutations on immunotherapy outcomes.

Results

The mutation rate of HER2 varied in solid tumors of TCGA, with an overall incidence of 3.13%, ranged from 0.39% to 12.2%. Concurrent HER2 mutations and amplifications were rare (0.26%). HER2 mutation was not associated with HER2 protein expression but was positively associated with microsatellite instability, tumor mutation and neoantigen burdens, infiltrating antitumor immune cells, and signal activities of antitumor immunity. Of 321 ICI-treated patients, 18 carried HER2 mutations (5.6%) and showed improved objective response rates compared with those with HER2 wild-type (44.4% vs. 25.7%, p=0.081), especially in the anti-PD-1/anti-PD-L1 subgroup (62.5% vs. 28.4%, p=0.04). Heterogeneity was observed among tumor types. Patients with HER2 mutations also had superior overall survival than those with HER2 wild-type (HR=0.47, 95%CI: 0.23-0.97, p=0.04), especially in the presence of co-mutations in ABCA1 (HR = 0.23, 95% CI: 0.07-0.73, p=0.013), CELSR1 (HR = 0.24, 95% CI: 0.08-0.77, p=0.016), LRP2 (HR = 0.24, 95% CI: 0.07-0.74, p=0.014), or PKHD1L1 (HR = 0.2, 95% CI: 0.05-0.8, p=0.023).

Conclusions

HER2 mutations may improve the TME to favor immunotherapy. A prospective basket trial is needed to further investigate the impacts of HER2 mutations on immunotherapy outcomes in solid tumors.

Open the Technical Black Box of Tumor Mutational Burden (TMB): Factors Affecting Harmonization and Standardization of Panel-Based TMB

As tumor mutational burden (TMB) has been approved as a predictive biomarker for immune checkpoint inhibitors (ICIs), next-generation sequencing (NGS) TMB panels are being increasingly used clinically. However, only a few of them have been validated in clinical trials or authorized by administration. The harmonization and standardization of TMB panels are thus essential for clinical implementation. In this review, preanalytic, sequencing, bioinformatics and interpretative factors are summarized to provide a comprehensive picture of how the different factors affect the estimation of panel-based TMB. Among the factors, poor DNA quality, improper formalin fixation and residual germline variants after filtration may overestimate TMB, while low tumor purity may decrease the sensitivity of the TMB panel. In addition, a small panel size leads to more variability when comparing with true TMB values detected by whole-exome sequencing (WES). A panel covering a genomic region of more than 1Mb is more stable for harmonization and standardization. Because the TMB estimate reflects the sum of effects from multiple factors, deliberation based on laboratory and specimen quality, as well as clinical information, is essential for decision making.

High tumor mutational burden predicts worse prognosis for cervical cancer treated with radiotherapy

PURPOSE

Tumor mutational burden (TMB) is a surrogate biomarker of neo-antigens and high TMB status is associated with favorable response to immune-checkpoint inhibitors (ICIs). This study aimed to elucidate the association between TMB and the outcome of definitive radiotherapy in patients with cervical cancer.

MATERIALS AND METHODS

TMB and treatment outcome were retrospectively analyzed in patients with newly diagnosed cervical cancer treated with definitive radiotherapy available with somatic mutation data of pre-treatment tumors obtained using a commercially available gene panel.

RESULTS

The study enrolled 98 patients (median follow-up period, 61 months). The median TMB was 9.5 mutations per megabase (range, 3.0-35.5 mutations per megabase). After dichotomization based on this median value, the 5-year overall survival (OS) for TMB-high patients was significantly worse than that of TMB-low patients (61.1% vs. 82.2%). Multivariate analysis identified high TMB status as a significant prognostic factor for worse OS, along with advanced stage, para-aortic lymph node involvement, and absence of concurrent chemotherapy.

CONCLUSION

These data indicate that TMB is a potential prognostic factor for worse survival in patients with cervical cancer treated with definitive radiotherapy, thereby providing a rationale for treatment of TMB-high cervical cancers with a combination of ICIs plus radiotherapy. This retrospective study of 98 patients demonstrates for the first time that tumor mutational burden (TMB) is an independent prognostic factor for worse overall survival of patients treated with definitive radiotherapy, providing a rationale for treatment of TMB-high cervical cancers with a combination of immune-checkpoint inhibitors plus radiotherapy.

Visualization of the Effect of Assay Size on the Error Profile of Tumor Mutational Burden Measurement

Tumor mutational burden (TMB) refers to the number of somatic mutations in a tumor per megabase and is a biomarker for response to immune checkpoint inhibitor therapy. Immune checkpoint inhibitors are currently approved for tumors with TMB greater than or equal to 10 mutations/megabase. Many laboratories are currently reporting TMB values based upon targeted resequencing panels with limited genomic coverage. Due to sampling variation, this leads to significant uncertainty in the assay’s TMB result, particularly at relatively low TMB levels near the 10 mutation per megabase therapeutic threshold. In order to allow clinicians and laboratorians to explore this uncertainty, we built a novel web application that allows a user to view the potential error of a TMB result given the sequencing panel size. This application also allows the user to explore the effect of incorporating knowledge of a specific tumor type’s typical TMB distribution on the error profile of the TMB result.

Predictive molecular markers for the treatment with immune checkpoint inhibitors in colorectal cancer

Colorectal cancer is one of the most common malignant tumors and, hence, has become one of the most important public health issues in the world. Treatment with immune checkpoint inhibitors (ICIs) successfully improves the survival rate of patients with melanoma, non-small-cell lung cancer, and other malignancies, and its application in metastatic colorectal cancer is being actively explored. However, a few patients develop drug resistance. Predictive molecular markers are important tools to precisely screen patient groups that can benefit from treatment with ICIs. The current article focused on certain important predictive molecular markers for ICI treatment in colorectal cancer, including not only some of the mature molecular markers, such as deficient mismatch repair (d-MMR), microsatellite instability-high (MSI-H), tumor mutational burden (TMB), programmed death-ligand-1 (PD-L1), tumor immune microenvironment (TiME), and tumor-infiltrating lymphocytes (TILs), but also some of the novel molecular markers, such as DNA polymerase epsilon (POLE), polymerase delta 1 (POLD1), circulating tumor DNA (ctDNA), and consensus molecular subtypes (CMS). We have reviewed these markers in-depth and presented the results from certain important studies, which suggest their applicability in CRC and indicate their advantages and disadvantages. We hope this article is helpful for clinicians and researchers to systematically understand these markers and can guide the treatment of colorectal cancer.

Design of Personalized Neoantigen RNA Vaccines Against Cancer Based on Next-Generation Sequencing Data

The good clinical results of immune checkpoint inhibitors (ICIs) in recent cancer therapy and the success of RNA vaccines against SARS-nCoV2 have provided important lessons to the scientific community. On the one hand, the efficacy of ICI depends on the number and immunogenicity of tumor neoantigens (TNAs) which unfortunately are not abundantly expressed in many cancer subtypes. On the other hand, novel RNA vaccines have significantly improved both the stability and immunogenicity of mRNA and its efficient delivery, this way overcoming past technique limitations and also allowing a quick vaccine development at the same time. These two facts together have triggered a resurgence of therapeutic cancer vaccines which can be designed to include individual TNAs and be synthesized in a timeframe short enough to be suitable for the tailored treatment of a given cancer patient.In this chapter, we explain the pipeline for the synthesis of TNA-carrying RNA vaccines which encompasses several steps such as individual tumor next-generation sequencing (NGS), selection of immunogenic TNAs, nucleic acid synthesis, drug delivery systems, and immunogenicity assessment, all of each step comprising different alternatives and variations which will be discussed.

Integration of Genomic Profiling and Organoid Development in Precision Oncology

Precision oncology involves an innovative personalized treatment strategy for each cancer patient that provides strategies and options for cancer treatment. Currently, personalized cancer medicine is primarily based on molecular matching. Next-generation sequencing and related technologies, such as single-cell whole-transcriptome sequencing, enable the accurate elucidation of the genetic landscape in individual cancer patients and consequently provide clinical benefits. Furthermore, advances in cancer organoid models that represent genetic variations and mutations in individual cancer patients have direct and important clinical implications in precision oncology. This review aimed to discuss recent advances, clinical potential, and limitations of genomic profiling and the use of organoids in breast and ovarian cancer. We also discuss the integration of genomic profiling and organoid models for applications in cancer precision medicine.

Recent advances in lung cancer genomics: Application in targeted therapy

Genomic characterization of lung cancer has not only improved our understanding of disease biology and carcinogenesis but also revealed several therapeutic opportunities. Targeting tumor dependencies on specific genomic alterations (oncogene addiction) has accelerated the therapeutic developments and significantly improved the outcomes even in advanced stage of disease. Identification of genomic alterations predicting response to specific targeted treatment is the key to success for this "personalized treatment" approach. Availability of multiple choices of therapeutic options for specific genomic alterations highlight the importance of optimum sequencing of drugs. Multiplex gene testing has become mandatory in view of constantly increasing number of therapeutic targets and effective treatment options. Influence of genomic characteristics on response to immunotherapy further makes comprehensive genomic profiling necessary before therapeutic decision making. A comprehensive elucidation of resistance mechanisms and directed treatments have made the continuum of care possible and transformed this deadly disease into a chronic condition. Liquid biopsy-based approach has made the dynamic monitoring of disease possible and enabled treatment optimizations accordingly. Current lung cancer management is the perfect example of "precision-medicine" in clinical oncology.

Liquid Biopsy Biomarkers for Immunotherapy in Non-Small Cell Lung Carcinoma: Lessons Learned and the Road Ahead

Over the recent years, advances in the development of anti-cancer treatments, particularly the implementation of ICIs (immune checkpoint inhibitors), have resulted in increased survival rates in NSCLC (non-small cell lung cancer) patients. However, a significant proportion of patients does not seem respond to immunotherapy, and some individuals even develop secondary resistance to treatment. Therefore, it is imperative to correctly identify the patients that will benefit from ICI therapy in order to tailor therapeutic options in an individualised setting, ultimately benefitting both the patient and the health system. Many different biomarkers have been explored to correctly stratify patients and predict response to immunotherapy, but liquid biopsy approaches have recently arisen as an interesting opportunity to predict and monitor treatment response due to their logistic accessibility. This review summarises the current data and efforts in the field of ICI response biomarkers in NSCLC patients and highlights advantages and limitations as we discuss the road to clinical implementation.

Clinical cancer genomic profiling

Technological innovation and rapid reduction in sequencing costs have enabled the genomic profiling of hundreds of cancer-associated genes as a component of routine cancer care. Tumour genomic profiling can refine cancer subtype classification, identify which patients are most likely to benefit from systemic therapies and screen for germline variants that influence heritable cancer risk. Here, we discuss ongoing efforts to enhance the clinical utility of tumour genomic profiling by integrating tumour and germline analyses, characterizing allelic context and identifying mutational signatures that influence therapy response. We also discuss the potential clinical utility of more comprehensive whole-genome and whole-transcriptome sequencing and ultra-sensitive cell-free DNA profiling platforms, which allow for minimally invasive, serial analyses of tumour-derived DNA in blood.

Tumor Mutational Burden as a Potential Biomarker for Immunotherapy in Pancreatic Cancer: Systematic Review and Still-Open Questions

Simple Summary

Tumor mutational burden (TMB) represents the number of mutations per megabase (muts/Mb) harbored by tumor cells in a given neoplasm, and can be determined with next-generation sequencing. High values are an indicator of potential response to immunotherapy. With this systematic review, we assessed its role in pancreatic ductal adenocarcinoma (PDAC). Our main findings can be summarized as: (i) high-TMB can be found in about 1% of PDAC; (ii) it is associated with mucinous/colloid and medullary histology; (iii) high-TMB PDAC frequently harbor other actionable alterations, with microsatellite instability as the most common; (iv) immunotherapy has shown promising results in high-TMB PDAC.

Abstract

Tumor mutational burden (TMB) is a numeric index that expresses the number of mutations per megabase (muts/Mb) harbored by tumor cells in a neoplasm. TMB can be determined using different approaches based on next-generation sequencing. In the case of high values, it indicates a potential response to immunotherapy. In this systematic review, we assessed the potential predictive role of high-TMB in pancreatic ductal adenocarcinoma (PDAC), as well as the histo-molecular features of high-TMB PDAC. High-TMB appeared as a rare but not-negligible molecular feature in PDAC, being present in about 1.1% of cases. This genetic condition was closely associated with mucinous/colloid and medullary histology (p < 0.01). PDAC with high-TMB frequently harbored other actionable alterations, with microsatellite instability/defective mismatch repair as the most common. Immunotherapy has shown promising results in high-TMB PDAC, but the sample size of high-TMB PDAC treated so far is quite small. This study highlights interesting peculiarities of PDAC harboring high-TMB and may represent a reliable starting point for the assessment of TMB in the clinical management of patients affected by pancreatic cancer.

DNA Damage Repair Gene Set as a Potential Biomarker for Stratifying Patients with High Tumor Mutational Burden

Simple Summary

Immunotherapy has been a promising therapeutic approach for cancer treatment in recent years. Although cancer immunotherapy has achieved remarkable success, treatment response is only observed in a small number of patients. As nonresponders need to endure high treatment costs and toxicities with little benefit from treatment, identifying potential predictive biomarkers is critical to optimize the benefits of immunotherapy in patients. The total number of mutations in the tumor genome is a useful biomarker. Patients with a large number of mutations tend to respond better to cancer immunotherapy. However, assessment of the total number of mutations may not be easy. In this study, we identified gene sets with only a small number of genes whose mutations serve as an indicator of the total number of mutations. These cancer-specific gene sets can be used as a cost-effective approach to stratify patients with a large number of mutations in clinical practice.

Abstract

Tumor mutational burden (TMB) is a promising predictive biomarker for cancer immunotherapy. Patients with a high TMB have better responses to immune checkpoint inhibitors. Currently, the gold standard for determining TMB is whole-exome sequencing (WES). However, high cost, long turnaround time, infrastructure requirements, and bioinformatics demands have prevented WES from being implemented in routine clinical practice. Panel-sequencing-based estimates of TMB have gradually replaced WES TMB; however, panel design biases could lead to overestimation of TMB. To stratify TMB-high patients better without sequencing all genes and avoid overestimating TMB, we focused on DNA damage repair (DDR) genes, in which dysfunction may increase somatic mutation rates. We extensively explored the association between the mutation status of DDR genes and TMB in different cancer types. By analyzing the mutation data from The Cancer Genome Atlas, which includes information for 33 different cancer types, we observed no single DDR gene/pathway in which mutation status was significantly associated with high TMB across all 33 cancer types. Therefore, a computational algorithm was proposed to identify a cancer-specific gene set as a surrogate for stratifying patients with high TMB in each cancer. We applied our algorithm to skin cutaneous melanoma and lung adenocarcinoma, demonstrating that the mutation status of the identified cancer-specific DDR gene sets, which included only 9 and 14 genes, respectively, was significantly associated with TMB. The cancer-specific DDR gene set can be used as a cost-effective approach to stratify patients with high TMB in clinical practice.

Profiling of host genetic alterations and intra-tumor microbiomes in colorectal cancer

Some bacteria are symbiotic in tumor tissues, and metabolites of several bacterial species have been found to cause DNA damage. However, to date, the association between bacteria and host genetic alterations in colorectal cancer (CRC) has not been fully investigated. We evaluated the association between the intra-tumor microbiome and host genetic alterations in 29 Japanese CRC patients. The tumor and non-tumor tissues were extracted from the patients, and 16S rRNA genes were sequenced for each sample. We identified enriched bacteria in tumor and non-tumor tissues. Some bacteria, such as Fusobacterium, which is already known to be enriched in CRC, were found to be enriched in tumor tissues. Interestingly, Bacteroides, which is also known to be enriched in CRC, was enriched in non-tumor tissues. Furthermore, it was shown that certain bacteria that often coexist within tumor tissue were enriched in the presence of a mutated gene or signal pathway with mutated genes in the host cells. Fusobacterium was associated with many mutated genes, as well as cell cycle-related pathways including mutated genes. In addition, the patients with a high abundance of Campylobacter were suggested to be associated with mutational signature 3 indicating failure of double-strand DNA break repairs. These results suggest that CRC development may be partly caused by DNA damage caused by substances released by bacterial infection. Taken together, the identification of distinct gut microbiome patterns and their host specific genetic alterations might facilitate targeted interventions, such as modulation of the microbiome in addition to anticancer agents or immunotherapy.

TMB or not TMB as a biomarker: That is the question

Immune checkpoint inhibitors (ICIs) have revolutionized the landscape of therapeutic options for many cancers. These treatments have demonstrated improved efficacy and often a more favourable toxicity profile compared to standard cytotoxic chemotherapy. There are considerable differences among responders, with some patients experiencing durable long-term disease control and even remission. Given this variability, determining a proper biomarker to select patients for ICI therapy has become increasingly important. The only biomarker proven to be predictive of overall survival benefit with ICI therapy is PD-L1 expression level measured by immunohistochemistry. Several attempts have been made to identify different predictive biomarkers. One of the most intriguing and divisive is tumor mutational burden (TMB). TMB represents the number of mutations per megabase (Mut/Mb) of DNA that were sequenced in a specific cancer. With a higher number of mutations detected, and consequentially an increase in the number neo-epitopes, then it is more likely that one or more of those neo-antigens could be immunogenic and trigger a T cell response. Initially, TMB was identified as a biomarker for ICIs in melanoma and subsequent studies suggested a possible clinical role for TMB in non-small cell lung cancer. The initial data were not confirmed in a prospective study assessing OS as the primary endpoint. Recently, the FDA has approved pembrolizumab in all cancers with a TMB > 10Mut/Mb[12] based on findings from the phase 2 KEYNOTE-158. Much criticism has emerged about this pan-cancer approval, in particular about the use of TMB as biomarker to select patients. Here we review the data about the importance and role of TMB as possible pan-cancer one-size-fits-all biomarker. We highlight the strengths and intrinsic limitations of such a complex biomarker and its adoption in the daily practice.

Elastic Net Models Based on DNA Copy Number Variations Predicts Clinical Features, Expression Signatures, and Mutations in Lung Adenocarcinoma

In the precision medicine of lung adenocarcinoma, the identification and prediction of tumor phenotypes for specific biomolecular events are still not studied in depth. Various earlier researches sheds light on the close correlation between genetic expression signatures and DNA copy number variations (CNVs), for which analysis of CNVs provides valuable information about molecular and phenotypic changes in tumorigenesis. In this study, we propose a comprehensive analysis combining genome-wide association analysis and an Elastic Net Regression predictive model, focus on predicting the levels of many gene expression signatures in lung adenocarcinoma, based upon DNA copy number features alone. Additionally, we predicted many other key phenotypes, including clinical features (pathological stage), gene mutations, and protein expressions. These Elastic Net prediction methods can also be applied to other gene sets, thereby facilitating their use as biomarkers in monitoring therapy.

Exploration of the Associations of lncRNA Expression Patterns with Tumor Mutation Burden and Prognosis in Colon Cancer

Background

Tumor mutation burden (TMB) is emerging as a new biomarker to monitor the response of cancer patients to immunotherapy. Long non-coding RNAs (lncRNAs) are critical in regulating gene expression and play a significant role in cancer-associated immune responses. However, the association between lncRNA expression patterns and TMB levels and survival outcomes remains unknown in colon cancer.

Methods

In colon cancer patients from The Cancer Genome Atlas Program (TCGA), a multi-lncRNAs based classifier for predicting TMB levels was established using the least absolute shrinkage and selection operator (LASSO) method. The association between classifier index and immune-related characteristics of patients was also investigated. Quantitative polymerase chain reaction (qPCR) was used to verify the expression levels of these lncRNAs in normal and CRC cell lines.

Results

The multi-lncRNAs based classifier had ability to predict TMB level of patients with accuracy (AUC= 0.70), and the general applicability of this classifier was proved in the validation set (AUC= 0.71) and the pooled set (AUC= 0.70). The classifier index was related to three immune checkpoints (PD1, PD-L1, and CTLA-4), the infiltration level of immune cells, and immune response-related score (IFN-γ score, gene expression profiles (GEP) score, cytolytic activity (CYT) score and MHC score). A nomogram, which integrates classifier and some common clinical information, was able to predict the overall survival of colon cancer patients accurately.

Conclusion

LncRNA expression patterns are associated with TMB, which may serve as a classifier to predict the TMB in colon cancer patients. The nomogram could potentially evaluate survival outcomes and provide a reference to better manage colon cancer patients.

Cross-oncopanel study reveals high sensitivity and accuracy with overall analytical performance depending on genomic regions

BACKGROUND

Targeted sequencing using oncopanels requires comprehensive assessments of accuracy and detection sensitivity to ensure analytical validity. By employing reference materials characterized by the U.S. Food and Drug Administration-led SEquence Quality Control project phase2 (SEQC2) effort, we perform a cross-platform multi-lab evaluation of eight Pan-Cancer panels to assess best practices for oncopanel sequencing.

RESULTS

All panels demonstrate high sensitivity across targeted high-confidence coding regions and variant types for the variants previously verified to have variant allele frequency (VAF) in the 5-20% range. Sensitivity is reduced by utilizing VAF thresholds due to inherent variability in VAF measurements. Enforcing a VAF threshold for reporting has a positive impact on reducing false positive calls. Importantly, the false positive rate is found to be significantly higher outside the high-confidence coding regions, resulting in lower reproducibility. Thus, region restriction and VAF thresholds lead to low relative technical variability in estimating promising biomarkers and tumor mutational burden.

CONCLUSION

This comprehensive study provides actionable guidelines for oncopanel sequencing and clear evidence that supports a simplified approach to assess the analytical performance of oncopanels. It will facilitate the rapid implementation, validation, and quality control of oncopanels in clinical use.

Analytic validation and clinical utilization of the comprehensive genomic profiling test, GEM ExTra®

We developed and analytically validated a comprehensive genomic profiling (CGP) assay, GEM ExTra, for patients with advanced solid tumors that uses Next Generation Sequencing (NGS) to characterize whole exomes employing a paired tumor-normal subtraction methodology. The assay detects single nucleotide variants (SNV), indels, focal copy number alterations (CNA), TERT promoter region, as well as tumor mutation burden (TMB) and microsatellite instability (MSI) status. Additionally, the assay incorporates whole transcriptome sequencing of the tumor sample that allows for the detection of gene fusions and select special transcripts, including AR-V7, EGFR vIII, EGFRvIV, and MET exon 14 skipping events. The assay has a mean target coverage of 180X for the normal (germline) and 400X for tumor DNA including enhanced probe design to facilitate the sequencing of difficult regions. Proprietary bioinformatics, paired with comprehensive clinical curation results in reporting that defines clinically actionable, FDA-approved, and clinical trial drug options for the management of the patient's cancer. GEM ExTra demonstrated analytic specificity (PPV) of > 99.9% and analytic sensitivity of 98.8%. Application of GEM ExTra to 1,435 patient samples revealed clinically actionable alterations in 83.9% of reports, including 31 (2.5%) where therapeutic recommendations were based on RNA fusion findings only.

Biomarkers in Immunotherapy-Based Precision Treatments of Digestive System Tumors

Immunotherapy, represented by immune checkpoint inhibitors (mainly referring to programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1) blockades), derives durable remission and survival benefits for multiple tumor types including digestive system tumors [gastric cancer (GC), colorectal cancer (CRC), and hepatocellular carcinoma (HCC)], particularly those with metastatic or recurrent lesions. Even so, not all patients would respond well to anti-programmed death-1/programmed death-ligand 1 agents (anti-PD-1/PD-L1) in gastrointestinal malignancies, suggesting the need for biomarkers to identify the responders and non-responders, as well as to predict the clinical outcomes. PD-L1expression has increasingly emerged as a potential biomarker when predicting the immunotherapy-based efficacy; but regrettably, PD-L1 alone is not sufficient to differentiate patients. Other molecules, such as tumor mutational burden (TMB), microsatellite instability (MSI), and circulating tumor DNA (ctDNA) as well, are involved in further explorations. Overall, there are not still no perfect or well-established biomarkers in immunotherapy for digestive system tumors at present as a result of the inherent limitations, especially for HCC. Standardizing and harmonizing the assessments of existing biomarkers, and meanwhile, switching to other novel biomarkers are presumably wise and feasible.

Tumor Mutational Burden as a Predictor of Immunotherapy Response: Is More Always Better?

Immune checkpoint inhibitors, including antibodies that block programmed cell death protein-1 (PD-1) and PD-L1, have transformed the management of many cancers. However, the majority of patients have primary or acquired resistance to these immunotherapies. There is a significant unmet need for predictive biomarkers that can reliably identify patients who derive a clinically meaningful response from PD-1/PD-L1 blockade. High tumor mutational burden (TMB-H) has shown promise as a biomarker in lung cancer, but the broad applicability of TMB-H as a biomarker of response across all solid tumors is unclear. The FDA has approved the PD-1 inhibitor, pembrolizumab, as a therapy for all solid tumors with TMB equal to or greater than 10 mutations/megabase as measured by the FoundationOne CDx assay. This approval was based on an exploratory analysis of the KEYNOTE-158 study, which was a single-arm, phase II multi-cohort study of pembrolizumab for select, previously treated advanced solid tumors. Here, we elucidate the caveats of using TMB as a biomarker with a universal threshold across all solid tumors. While we recognize the importance of this and other FDA pan-cancer approvals, several questions about TMB as a predictive biomarker remain unanswered. In this perspective, we discuss clinical trial evidence in this area. We review the relationship between TMB and the tumor immune microenvironment. We highlight the risks of extrapolating evidence from a limited number of tumor histologies to all solid tumors, and we propose avenues for future research.

RNA-Seq Reveals Differences in Expressed Tumor Mutation Burden in Colorectal and Endometrial Cancers with and without Defective DNA-Mismatch Repair

Tumor mutation burden (TMB) is an emerging biomarker of immunotherapy response. RNA sequencing in FFPE tissue samples was used for determining TMB in microsatellite-stable (MSS) and microsatellite instability-high (MSI-H) tumors in patients with colorectal or endometrial cancer. Tissue from tumors and paired normal tissue from 46 MSI-H and 12 MSS cases were included. Of the MSI-H tumors, 29 had defective DNA mismatch-repair mutations, and 17 had MLH1 promoter hypermethylation. TMB was measured using the expressed somatic nucleotide variants (eTMB). A method of accurate measurement of eTMB was developed that removes FFPE-derived artifacts by leveraging mutation signatures. There was a significant difference in the median eTMB values observed between MSI-H and MSS cases: 27.3 versus 6.7 mutations/megabase (mut/Mb) (P = 3.5 × 10^-9). Among tumors with defective DNA-mismatch repair, those with mismatch-repair mutations had a significantly higher median eTMB than those with hypermethylation: 28.1 versus 17.5 mut/Mb (P = 0.037). Multivariate analysis showed that MSI status, tumor type (endometrial or colorectal), and age were significantly associated with eTMB. Additionally, using whole-exome sequencing in a subset of these patients, it was determined that DNA TMB correlated well with eTMB (Spearman correlation coefficient, 0.83). These results demonstrate that RNA sequencing can be used for measuring eTMB in FFPE tumor specimens.

Predictive value of tumor mutation burden (TMB) with targeted next-generation sequencing in immunocheckpoint inhibitors for non-small cell lung cancer (NSCLC)

Background: To evaluate the clinical predictive value of tumor mutation burden (TMB) for immune checkpoint inhibitor (ICI) therapy in patients with non-small cell lung cancer (NSCLC).

Method: As of 15 February 2020, PubMed, PMC and EMBASE databases as well as the American society of clinical oncology (ASCO) and European society of medical oncology (ESMO) databases were searched. The Mantel-Haenszel or inverse variance weighted fixed-effects model (I² ≤ 50%) or random-effects model (I² > 50%) were used to evaluate OR and its 95% CI of objective response rate (ORR) and disease control rate (DCR) , as well as HR and its 95% CI of progression-free survival (PFS) and overall survival (OS). In addition, we did publication bias, heterogeneity analysis, sensitivity analysis and subgroup analysis. And quality of the studies included and the level of evidence for outcome measures were evaluated.

Results: 14 studies involving 2872 patients were included. The ORR (OR 3.52, 95%CI 2.32-5.35, p < 0.00001), DCR (OR 3.26, 95%CI 1.91-5.55, p < 0.0001), PFS (HR 0.81, 95%CI 0.74-0.89, p < 0.00001) and OS (HR 0.83, 95%CI 0.74-0.94, p = 0.002) of ICI therapy in the high TMB group were all superior to those in the low TMB group.

Conclusions: TMB is a promising biomarker, which can predict the efficacy of ICI therapy in advanced NSCLC patients, included ORR, DCR, PFS and OS.

Beyond Tumor PD-L1: Emerging Genomic Biomarkers for Checkpoint Inhibitor Immunotherapy

Despite the success of immune checkpoint blockade as a strategy for activating an antitumor immune response and promoting cancer regression, only a subset of patients have durable clinical benefit. Efforts are ongoing to identify robust biomarkers that can effectively predict treatment response to immune checkpoint inhibitors (ICIs). Although PD-L1 expression is useful for stratifying patients, it is an imperfect tool. Comprehensive next-generation sequencing platforms that are readily used in clinical practice to identify a tumor's potentially actionable genetic alterations also reveal tumor genomic features, including tumor mutation burden (TMB), that may impact the response to ICIs. High TMB enhances tumor immunogenicity through increased numbers of tumor neoantigens that may promote an immune response. Defective DNA repair, leading to microsatellite instability, is an endogenous mechanism for increased tumor TMB that augments response to anti-PD-1 blockade. Alternatively, DNA damage from exogenous factors is responsible for high TMB seen in melanoma, lung cancer, and urothelial carcinoma, among tumor subtypes with higher response rates to ICIs. In this review, we summarize data supporting the use of TMB as a biomarker as well as its known limitations. We also highlight specific tumor suppressor genes and oncogenes that are under investigation as biomarkers for ICI response and resistance. Efforts are ongoing to delineate which genomic tumor characteristics can eventually be utilized in clinical practice to ascertain the benefit of ICIs for an individual patient.

Informed consent for genetic testing in hematology

Informed consent is a fundamental component of modern health care. All competent adult patients have the legal and ethical authority to accept (consent) or refuse (dissent) recommended health-related interventions. Various models of informed consent have been described, and herein I introduce a model that divides informed consent into 7 distinct elements: competence, voluntariness, disclosure, recommendation, understanding, decision, and authorization. Genetic testing, which is rapidly becoming a common feature of both clinical care and research in hematology, adds additional layers of complexity to each of these consent elements. Using the example case of Mr. Smith, a man with newly diagnosed acute myeloid leukemia whose clinicians offer him genetic testing of the leukemia through a clinical trial, I highlight the challenges and controversies of informed consent for genetic testing, focusing on each consent element as it pertains to genetic testing in such a setting. Ultimately, given the growing importance of genetic testing for hematologic disorders, clinicians, and researchers in hematology should be facile at participating in all aspects of informed consent for genetic testing.