Molecular and Clinical Epidemiology of SARS-CoV-2 Infection among Vaccinated and Unvaccinated Individuals in a Large Healthcare Organization from New Jersey

New Jersey was among the first states impacted by the COVID-19 pandemic, with one of the highest overall death rates in the nation. Nevertheless, relatively few reports have been published focusing specifically on New Jersey. Here we report on molecular, clinical, and epidemiologic observations, from the largest healthcare network in the state, in a cohort of vaccinated and unvaccinated individuals with laboratory-confirmed SARS-CoV-2 infection. We conducted molecular surveillance of SARS-CoV-2-positive nasopharyngeal swabs collected in nine hospitals from December 2020 through June 2022, using both whole genome sequencing (WGS) and a real-time RT-PCR screening assay targeting spike protein mutations found in variants of concern (VOCs) within our region. De-identified clinical data were obtained retrospectively, including demographics, COVID-19 vaccination status, ICU admission, ventilator support, mortality, and medical history. Statistical analyses were performed to identify associations between SARS-CoV-2 variants, vaccination status, clinical outcomes, and medical risk factors. A total of 5007 SARS-CoV-2-positive nasopharyngeal swabs were successfully screened and/or sequenced. Variant screening identified three predominant VOCs, including Alpha (n = 714), Delta (n = 1877), and Omicron (n = 1802). Omicron isolates were further sub-typed as BA.1 (n = 899), BA.2 (n = 853), or BA.4/BA.5 (n = 50); the remaining 614 isolates were classified as "Other". Approximately 31.5% (1577/5007) of the samples were associated with vaccine breakthrough infections, which increased in frequency following the emergence of Delta and Omicron. Severe clinical outcomes included ICU admission (336/5007 = 6.7%), ventilator support (236/5007 = 4.7%), and mortality (430/5007 = 8.6%), with increasing age being the most significant contributor to each (p < 0.001). Unvaccinated individuals accounted for 79.7% (268/336) of ICU admissions, 78.3% (185/236) of ventilator cases, and 74.4% (320/430) of deaths. Highly significant (p < 0.001) increases in mortality were observed in individuals with cardiovascular disease, hypertension, cancer, diabetes, and hyperlipidemia, but not with obesity, thyroid disease, or respiratory disease. Significant differences (p < 0.001) in clinical outcomes were also noted between SARS-CoV-2 variants, including Delta, Omicron BA.1, and Omicron BA.2. Vaccination was associated with significantly improved clinical outcomes in our study, despite an increase in breakthrough infections associated with waning immunity, greater antigenic variability, or both. Underlying comorbidities contributed significantly to mortality in both vaccinated and unvaccinated individuals, with increasing risk based on the total number of comorbidities. Real-time RT-PCR-based screening facilitated timely identification of predominant variants using a minimal number of spike protein mutations, with faster turnaround time and reduced cost compared to WGS. Continued evolution of SARS-CoV-2 variants will likely require ongoing surveillance for new VOCs, with real-time assessment of clinical impact.

Postvaccination SARS-COV-2 among Health Care Workers in New Jersey: A Genomic Epidemiological Study

Emergence of SARS-CoV-2 with high transmission and immune evasion potential, the so-called variants of concern (VOC), is a major concern. We describe the early genomic epidemiology of SARS-CoV-2 recovered from vaccinated health care professionals (HCP). Our postvaccination COVID-19 symptoms-based surveillance program among HCPs in a 17-hospital network identified all vaccinated HCPs who tested positive for COVID-19 after routine screening or after self-reporting. From 1 January 2021 to 30 April 2021, 23,687 HCPs received either mRNA-1273 or BNT162b2 mRNA vaccine. All available postvaccination SARS-CoV-2 samples and a random collection from nonvaccinated patients during the similar time frame were subjected to VOC screening and whole-genome sequencing (WGS). Sixty-two percent (23,697/37,500) of HCPs received at least one vaccine dose, with 60% (22,458) fully vaccinated. We detected 138 (0.58%, 138/23,697) COVID-19 cases, 105 among partially vaccinated and 33 (0.15%, 33/22,458) among fully vaccinated. Five partially vaccinated required hospitalization, four with supplemental oxygen. VOC screening from 16 fully vaccinated HCPs identified 6 (38%) harboring N501Y and 1 (6%) with E484K polymorphisms; percentage of concurrent nonvaccinated samples was 37% (523/1,404) and 20% (284/1,394), respectively. There was an upward trend from January to April for E484K/Q (3% to 26%) and N501Y (1% to 49%). WGS analysis from vaccinated and nonvaccinated individuals indicated highly congruent phylogenies. We did not detect an increased frequency of any receptor-binding domain (RBD)/N-terminal domain (NTD) polymorphism between groups (P > 0.05). Our results support robust protection by vaccination, particularly among recipients of both doses. Despite VOCs accounting for over 40% of SARS-CoV-2 from fully vaccinated individuals, the genomic diversity appears to proportionally represent VOCs among nonvaccinated populations. IMPORTANCE A number of highly effective vaccines have been developed and deployed to combat the COVID-19 pandemic. The emergence and epidemiological dominance of SARS-CoV-2 mutants with high transmission potential and immune evasion properties, the so-called variants of concern (VOC), continue to be a major concern. Whether these VOCs alter the efficacy of the administered vaccines is of great concern and a critical question to study. We describe the initial genomic epidemiology of SARS-CoV-2 recovered from partial/fully vaccinated health care professionals and probe specifically for VOC enrichment. Our findings support the high level of protection provided by full vaccination despite a steep increase in the prevalence of polymorphisms associated with increased transmission potential (N501Y) and immune evasion (E484K) in the nonvaccinated population. Thus, we do not find evidence of VOC enrichment among vaccinated groups. Overall, the genomic diversity of SARS-CoV-2 recovered postvaccination appears to proportionally represent the observed viral diversity within the community.

Abstract 2328: Polyethnic-1000: Advancing cancer genomics by studying ethnically diverse, underserved patient populations in New York

Advances in sequencing technologies have revolutionized our approaches in medicine. However, our current knowledge about the molecular attributes of cancer has primarily been derived from patients of European descent. The overall aims of Polyethnic-1000 are to study the variability of somatic profiles and the effects of genetic ancestry on cancer biology and to bring genomic innovation to under-represented ethnic groups in the diverse patient population of New York City.A dynamic research platform is being created, involving the New York Genome Center, academic centers and partnering hospitals in the New York City region. In an initial retrospective study, the infrastructure, sample workflow, analysis and data sharing policies within the consortium have been developed. Whole-exome and RNA sequencing has been performed on 146 samples from self-identified non-white cancer patients treated at 14 different centers. Genetic ancestry estimation was performed at the super-population and population level using the 1000Genomes references. Data from over 24 tumor types were shared with our collaborators and the somatic variants were made available through our local installation of cBioPortal. Using the knowledge gained during the first stage, we are designing a prospective study to demonstrate our capacity to obtain samples from patients of varied ethnicities and to allow the formation of cohorts of interest for particular cancer types and particular ethnicities, with uniform consent for germline and somatic sequencing and return of results for potentially actionable mutations.By establishing a collaborative network, Polyethnic-1000 will deepen our understanding of the contributions that ethnicities make to the incidence and biology of cancers, potentially improving outcomes for patients who currently lack access to the most recent advances in medical science.

Citation Format: Nicolas Robine, Fieke Froeling, Benjamin Hubert, Timothy Chu, Ashlea Chandler, Michael C. Zody, Dayna M. Oschwald, Harold E. Varmus, Charles Sawyers, David Tuveson. Polyethnic-1000: Advancing cancer genomics by studying ethnically diverse, underserved patient populations in New York [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2328.

Deep whole-genome sequencing of 3 cancer cell lines on 2 sequencing platforms

To test the performance of a new sequencing platform, develop an updated somatic calling pipeline and establish a reference for future benchmarking experiments, we performed whole-genome sequencing of 3 common cancer cell lines (COLO-829, HCC-1143 and HCC-1187) along with their matched normal cell lines to great sequencing depths (up to 278x coverage) on both Illumina HiSeqX and NovaSeq sequencing instruments. Somatic calling was generally consistent between the two platforms despite minor differences at the read level. We designed and implemented a novel pipeline for the analysis of tumor-normal samples, using multiple variant callers. We show that coupled with a high-confidence filtering strategy, the use of combination of tools improves the accuracy of somatic variant calling. We also demonstrate the utility of the dataset by creating an artificial purity ladder to evaluate the somatic pipeline and benchmark methods for estimating purity and ploidy from tumor-normal pairs. The data and results of the pipeline are made accessible to the cancer genomics community.

Genetic Determinants of Cisplatin Resistance in Patients With Advanced Germ Cell Tumors

Purpose Owing to its exquisite chemotherapy sensitivity, most patients with metastatic germ cell tumors (GCTs) are cured with cisplatin-based chemotherapy. However, up to 30% of patients with advanced GCT exhibit cisplatin resistance, which requires intensive salvage treatment, and have a 50% risk of cancer-related death. To identify a genetic basis for cisplatin resistance, we performed whole-exome and targeted sequencing of cisplatin-sensitive and cisplatin-resistant GCTs. Methods Men with GCT who received a cisplatin-containing chemotherapy regimen and had available tumor tissue were eligible to participate in this study. Whole-exome sequencing or targeted exon-capture-based sequencing was performed on 180 tumors. Patients were categorized as cisplatin sensitive or cisplatin resistant by using a combination of postchemotherapy parameters, including serum tumor marker levels, radiology, and pathology at surgical resection of residual disease. Results TP53 alterations were present exclusively in cisplatin-resistant tumors and were particularly prevalent among primary mediastinal nonseminomas (72%). TP53 pathway alterations including MDM2 amplifications were more common among patients with adverse clinical features, categorized as poor risk according to the International Germ Cell Cancer Collaborative Group (IGCCCG) model. Despite this association, TP53 and MDM2 alterations predicted adverse prognosis independent of the IGCCCG model. Actionable alterations, including novel RAC1 mutations, were detected in 55% of cisplatin-resistant GCTs. Conclusion In GCT, TP53 and MDM2 alterations were associated with cisplatin resistance and inferior outcomes, independent of the IGCCCG model. The finding of frequent TP53 alterations among mediastinal primary nonseminomas may explain the more frequent chemoresistance observed with this tumor subtype. A substantial portion of cisplatin-resistant GCTs harbor actionable alterations, which might respond to targeted therapies. Genomic profiling of patients with advanced GCT could improve current risk stratification and identify novel therapeutic approaches for patients with cisplatin-resistant disease.

Integrative genetic analysis of mouse and human AML identifies cooperating disease alleles

Hatlen et al. provide an integrative analysis of the mutational landscape of mouse and human AML and identify functionally relevant cooperation between AML1-ETO and PTPN11 D61Y. Based on these findings, they generate a novel mouse model of t(8;21)⁺ AML.

t(8;21) is one of the most frequent chromosomal abnormalities observed in acute myeloid leukemia (AML). However, expression of AML1-ETO is not sufficient to induce transformation in vivo. Consistent with this observation, patients with this translocation harbor additional genetic abnormalities, suggesting a requirement for cooperating mutations. To better define the genetic landscape in AML and distinguish driver from passenger mutations, we compared the mutational profiles of AML1-ETO–driven mouse models of leukemia with the mutational profiles of human AML patients. We identified TET2 and PTPN11 mutations in both mouse and human AML and then demonstrated the ability of Tet2 loss and PTPN11 D61Y to initiate leukemogenesis in concert with expression of AML1-ETO in vivo. This integrative genetic profiling approach allowed us to accurately predict cooperating events in t(8;21)⁺ AML in a robust and unbiased manner, while also revealing functional convergence in mouse and human AML.

Abstract 4876: An integrated pipeline for detecting and characterizing structural variation in cancer

Detection and characterization of somatic structural variants (SVs) and copy-number variants (CNVs) from whole genome sequencing remains a challenging part of cancer analysis. Many callers have been developed that use different detection strategies, but most methods suffer from high rates of false positives and false negatives, and agreement between different callers is usually low.

We have developed a flexible pipeline that combines the results of multiple callers, filters calls to remove likely artifacts, and functionally annotates the resulting variants. We employ a diverse set of variant callers utilizing a combination of read depth, read pair, and split read detection methods: NBIC-seq (Xi et al., 2011), Crest (Wang et al., 2011), Delly (Rausch et al., 2012), and BreakDancer (Chen et al., 2009). To remove artifact calls due to mis-mapping, we apply filters that discard predicted SVs whose breakpoints exhibit certain sequence features (e.g. extensive mapping ambiguity, high repeat content). SVs corresponding to known germline variants (1000G, DGV, in-house database) are marked and removed as unlikely somatic variants: this greatly helps to prevent both sequencing protocol- and caller-specific artifacts as well as false positive somatic calls arising from missed calls in the matched germline sample. Finally, we employ our sensitive split read mapper SplazerS to identify SV breakpoints with base pair precision. In this step, we are also able to remove remaining germline variants for which we find split read support in the matched normal sample. The final predicted structural variants are annotated for overlap with SVs in COSMIC, overlap with known cancer genes and potential impact on gene structure.

We use a public synthetic data set (DREAM challenge; Boutros et al., 2014) to demonstrate that using our selected ensemble of tools significantly improves sensitivity as compared to any single caller and that our filters effectively remove artifacts. Further, we show results from a set of colorectal cancer samples (Brannon et al., 2014) in which highly similar primary and metastatic tumors show excellent agreement in somatic SV calls in the absence of overlap between unrelated samples. Results from testing our pipeline on TCGA glioblastoma multiforme tumors, for which validated genomic rearrangements are available, will also be presented.

In conclusion, our pipeline improves detection of SVs by integrating orthogonal calling methods and facilitates identification of clinically relevant SVs through effective filters and cancer-specific functional annotation.

Citation Format: Minita Shah, Dayna M. Oschwald, Soren Germer, Michael C. Zody, Toby Bloom, Anne-Katrin Emde. An integrated pipeline for detecting and characterizing structural variation in cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4876. doi:10.1158/1538-7445.AM2015-4876

Comparative sequencing analysis reveals high genomic concordance between matched primary and metastatic colorectal cancer lesions

Background

Colorectal cancer is the second leading cause of cancer death in the United States, with over 50,000 deaths estimated in 2014. Molecular profiling for somatic mutations that predict absence of response to anti-EGFR therapy has become standard practice in the treatment of metastatic colorectal cancer; however, the quantity and type of tissue available for testing is frequently limited. Further, the degree to which the primary tumor is a faithful representation of metastatic disease has been questioned. As next-generation sequencing technology becomes more widely available for clinical use and additional molecularly targeted agents are considered as treatment options in colorectal cancer, it is important to characterize the extent of tumor heterogeneity between primary and metastatic tumors.

Results

We performed deep coverage, targeted next-generation sequencing of 230 key cancer-associated genes for 69 matched primary and metastatic tumors and normal tissue. Mutation profiles were 100% concordant for KRAS, NRAS, and BRAF, and were highly concordant for recurrent alterations in colorectal cancer. Additionally, whole genome sequencing of four patient trios did not reveal any additional site-specific targetable alterations.

Conclusions

Colorectal cancer primary tumors and metastases exhibit high genomic concordance. As current clinical practices in colorectal cancer revolve around KRAS, NRAS, and BRAF mutation status, diagnostic sequencing of either primary or metastatic tissue as available is acceptable for most patients. Additionally, consistency between targeted sequencing and whole genome sequencing results suggests that targeted sequencing may be a suitable strategy for clinical diagnostic applications.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0454-7) contains supplementary material, which is available to authorized users.

Validation of a next-generation sequencing assay for clinical molecular oncology

Currently, oncology testing includes molecular studies and cytogenetic analysis to detect genetic aberrations of clinical significance. Next-generation sequencing (NGS) allows rapid analysis of multiple genes for clinically actionable somatic variants. The WUCaMP assay uses targeted capture for NGS analysis of 25 cancer-associated genes to detect mutations at actionable loci. We present clinical validation of the assay and a detailed framework for design and validation of similar clinical assays. Deep sequencing of 78 tumor specimens (≥ 1000× average unique coverage across the capture region) achieved high sensitivity for detecting somatic variants at low allele fraction (AF). Validation revealed sensitivities and specificities of 100% for detection of single-nucleotide variants (SNVs) within coding regions, compared with SNP array sequence data (95% CI = 83.4-100.0 for sensitivity and 94.2-100.0 for specificity) or whole-genome sequencing (95% CI = 89.1-100.0 for sensitivity and 99.9-100.0 for specificity) of HapMap samples. Sensitivity for detecting variants at an observed 10% AF was 100% (95% CI = 93.2-100.0) in HapMap mixes. Analysis of 15 masked specimens harboring clinically reported variants yielded concordant calls for 13/13 variants at AF of ≥ 15%. The WUCaMP assay is a robust and sensitive method to detect somatic variants of clinical significance in molecular oncology laboratories, with reduced time and cost of genetic analysis allowing for strategic patient management.