Next-Generation Sequencing of Patients With Breast Cancer in Community Oncology Clinics

Pathologically confirmed women's breast cancer: A descriptive study of Tunisian and Algerian series

BACKGROUND

Breast cancer (BC) is the most frequent malignancy among women in Tunisia and Algeria. Clinical and pathological characteristics of this cancer among these populations are not widely reported. The aim of the study was to report clinical and pathological characteristics of women's BC in a Tunisian and Algerian series.

METHODS

Pathologically confirmed 1089 BCs were gathered in the pathology departments of three Northern Tunisian hospitals: Tunis military, Charles Nicolle and Jendouba and in the pathology department of Alger Douera hospital between January 2015 and December 2020. Clinical and pathological findings of the two series: age, tumor size, histological type, grading according to Scarff-Bloom Richardson grading system, lymph node status at the time of diagnosis in axillary lymphadenectomy specimens and the immunohistochemical expression of estrogen and progesterone receptors (ER/PR), HER2 and Ki-67, were collected from the pathological reports.

RESULTS

The median age at diagnosis was 50 and 48 years in Tunisian and Algerian series, respectively (p = 0.016). The diagnosis of BC was made on surgical specimens (lumpectomy or mastectomy) in 373/491 (76%) cases of the Tunisian series and in 225/598 (37.6%) cases of the Algerian one. Median tumor size was 2.8 cm and 2.5 cm in Algerian and Tunisian series, respectively (p = 0.252). Invasive BCs not otherwise specified was observed in 440/481 (91.5%) BCs in Tunisian series and in 519/586 (88.6%) BCs in Algerian series. Axillary lymph node positive tumors were observed in 64.6% and 58.8% of Tunisian and Algerian women, respectively (p = 0.926). BCs were ER positive in 311/385 (80.8%) and 486/571 (85.1%) cases and HER2 positive in 86/283 (30.4%) and 60/385 (15.6%) cases of Tunisian and Algerian series, respectively.

CONCLUSIONS

In Tunisia and Algeria, BC has poor prognostic factors with large tumor sizes and high rates of lymph nodes involvement at diagnosis.

Prognostic analysis of patients with breast cancer based on tumor mutational burden and DNA damage repair genes

Background

Breast cancer has a high tumor-specific death rate and poor prognosis. In this study, we aimed to provide a basis for the prognostic risk in patients with breast cancer using significant gene sets selected by analyzing tumor mutational burden (TMB) and DNA damage repair (DDR).

Methods

Breast cancer genomic and transcriptomic data were obtained from The Cancer Genome Atlas (TCGA). Breast cancer samples were dichotomized into high- and low-TMB groups according to TMB values. Differentially expressed DDR genes between high- and low-TMB groups were incorporated into univariate and multivariate cox regression model to build prognosis model. Performance of the prognosis model was validated in an independently new GEO dataset and evaluated by time-dependent ROC curves.

Results

Between high- and low-TMB groups, there were 6,424 differentially expressed genes, including 67 DDR genes. Ten genes associated with prognosis were selected by univariate cox regression analysis, among which seven genes constituted a panel to predict breast cancer prognosis. The seven-gene prognostic model, as well as the gene copy numbers are closely associated with tumor-infiltrating immune cells.

Conclusion

We established a seven-gene prognostic model comprising MDC1, PARP3, PSMB1, PSMB9, PSMD2, PSMD7, and PSMD14 genes, which provides a basis for further exploration of a population-based prediction of prognosis and immunotherapy response in patients with breast cancer.

Understanding inequities in precision oncology diagnostics

Advances in molecular diagnostics have enabled the identification of targetable driver pathogenic variants, forming the basis of precision oncology care. However, the adoption of new technologies, such as next-generation sequencing (NGS) panels, can exacerbate healthcare disparities. Here, we summarize data on use patterns of advanced biomarker testing, highlight the disparities in both accessing NGS testing and using this data to match patients to appropriate personalized therapies and propose multidisciplinary strategies to address inequities looking forward.

Molecular Profile and Matched Targeted Therapy for Advanced Breast Cancer Patients

(1) Background: Precision oncology is opening new treatment opportunities for patients suffering from solid tumors. In the last two decades, the advent of CDK4/6 inhibitors, immunotherapy, and antibody-drug conjugates (ADC) improved survival outcomes for advanced or metastatic breast cancers (BC). Nevertheless, some patients progress to approved therapies and still maintain good clinical conditions. (2) Methods: With the aim to estimate the accrual rate to experimental precision oncology treatments, we collected molecular and clinical characteristics of BC patients evaluated at Phase 1 Unit of Fondazione Policlinico Gemelli. Clinical data were retrieved from hospital records. Molecular analysis was performed using Next-Generation Sequencing (NGS) FoundationOne CDx on tissue or blood. (3) Results: Among the 38 BC patients referred to our unit, 35 completed the genomic analysis. All patients were female with advanced (mean number of metastatic sites: 3, range 1-6) BC. Median age at our evaluation was 52 (IQR, 48-59). ECOG PS was good in 97% of the study population, although heavily pre-treated (median number of systemic treatments: 5, IQR 3-7). Half of referred patients were HR⁺/HER2^- BC, with 39% triple negative breast cancer (TNBC). NGS testing was performed on relapsed disease among most (71%) participants, in particular lymph nodes and soft tissue. Liquid biopsy was requested in 23% of cases. The median time from sample collection to NGS testing was 1 month and from diagnosis 54 months. The median value of mutations, VUS, and TMB were 6, 11, and 5, respectively. TP53, PIK3CA, BRCA2, ESR1, and RAD21 were the genes with the highest number of molecular alterations. In 5 patients (14%), the molecular analysis was helpful to assign targeted therapy in the context of clinical trials with a median progression-free survival of 5 months. (4) Conclusions: HR⁺/HER2^- and TNBC were the most frequent subtypes referred for NGS testing. Tissue biopsy of relapsed disease was feasible in 71% of cases. The molecular analysis offered a new treatment opportunity in 14% of patients. The real benefit of these treatments remains to be evaluated in larger cohorts.

Evaluation of the Available Variant Calling Tools for Oxford Nanopore Sequencing in Breast Cancer

The goal of biomarker testing, in the field of personalized medicine, is to guide treatments to achieve the best possible results for each patient. The accurate and reliable identification of everyone’s genome variants is essential for the success of clinical genomics, employing third-generation sequencing. Different variant calling techniques have been used and recommended by both Oxford Nanopore Technologies (ONT) and Nanopore communities. A thorough examination of the variant callers might give critical guidance for third-generation sequencing-based clinical genomics. In this study, two reference genome sample datasets (NA12878) and (NA24385) and the set of high-confidence variant calls provided by the Genome in a Bottle (GIAB) were used to allow the evaluation of the performance of six variant calling tools, including Human-SNP-wf, Clair3, Clair, NanoCaller, Longshot, and Medaka, as an integral step in the in-house variant detection workflow. Out of the six variant callers understudy, Clair3 and Human-SNP-wf that has Clair3 incorporated into it achieved the highest performance rates in comparison to the other variant callers. Evaluation of the results for the tool was expressed in terms of Precision, Recall, and F1-score using Hap.py tools for the comparison. In conclusion, our findings give important insights for identifying accurate variants from third-generation sequencing of personal genomes using different variant detection tools available for long-read sequencing.

Dissecting Molecular Heterogeneity of Circulating Tumor Cells (CTCs) from Metastatic Breast Cancer Patients through Copy Number Aberration (CNA) and Single Nucleotide Variant (SNV) Single Cell Analysis

Circulating tumor cells' (CTCs) heterogeneity contributes to counteract their introduction in clinical practice. Through single-cell sequencing we aim at exploring CTC heterogeneity in metastatic breast cancer (MBC) patients. Single CTCs were isolated using DEPArray NxT. After whole genome amplification, libraries were prepared for copy number aberration (CNA) and single nucleotide variant (SNV) analysis and sequenced using Ion GeneStudio S5 and Illumina MiSeq, respectively. CTCs demonstrate distinctive mutational signatures but retain molecular traces of their common origin. CNA profiling identifies frequent aberrations involving critical genes in pathogenesis: gains of 1q (CCND1) and 11q (WNT3A), loss of 22q (CHEK2). The longitudinal single-CTC analysis allows tracking of clonal selection and the emergence of resistance-associated aberrations, such as gain of a region in 12q (CDK4). A group composed of CTCs from different patients sharing common traits emerges. Further analyses identify losses of 15q and enrichment of terms associated with pseudopodium formation as frequent and exclusive events. CTCs from MBC patients are heterogeneous, especially concerning their mutational status. The single-cell analysis allows the identification of aberrations associated with resistance, and is a candidate tool to better address treatment strategy. The translational significance of the group populated by similar CTCs should be elucidated.

Using Technology to Enhance Cancer Clinical Trial Participation

The COVID-19 pandemic presented many challenges to health care systems, including oncology clinical research programs. There were substantial negative effects on oncology clinical trial screening, enrollment, and study activities that forced institutions and regulatory bodies to develop innovative solutions to maintain robust and equitable participation in these trials. Digital pathology innovations at Memorial Sloan Kettering Cancer Center have streamlined the diagnostic life cycle for patients with cancer, and the seamless integration of digital pathology services with next-generation sequencing and other molecular pathology services have accelerated the time to diagnosis and receipt of molecular results. Timely access to these results, coupled with Memorial Sloan Kettering Cancer Center's knowledge engine OncoKB, enhances patient clinical trial coordination precisely and efficiently. At the Sarah Cannon Research Institute, centralized remote clinical trial matching and screening, virtual molecular tumor boards, and centralized molecular interpretation support services have empowered clinic staff to identify more efficiently potential participants in clinical research, despite the COVID-19 pandemic. In addition, the U.S. Food and Drug Administration Oncology Center of Excellence has been involved in several efforts to address challenges for patients with cancer during the COVID-19 pandemic, including writing guidance documents and participating in efforts to modernize clinical trials. The enclosed personal experience of a patient with cancer currently participating in an oncology clinical trial emphasizes the need for continued decreasing of barriers to study participation. Clinical trial advances that were accelerated by the pandemic will ultimately help patients with cancer and the greater oncology health care community.

Discordance in Tumor Mutation Burden from Blood and Tissue Affects Association with Response to Immune Checkpoint Inhibition in Real-World Settings

BACKGROUND

Tumor mutation burden (TMB), a biomarker for immune checkpoint inhibitor (CPI) response, is reported by both blood- and tissue-based next-generation sequencing (NGS) vendors. However, the agreement between TMB from blood (bTMB) and tissue (tTMB) in real-world settings, both in absolute value and association with CPI response, is not known.

MATERIALS AND METHODS

This study utilizes Sarah Cannon's precision medicine platform, Genospace, to harmonize clinico-genomic data from 17 206 patients with cancer with NGS results from September 2015 to August 2021. A subset of patients have both bTMB and tTMB results. Statistical analyses are performed in R and include (1) correlation (r) and concordance (ρ) between patient-matched bTMB-tTMB pairs, (2) distribution of total bTMB and tTMB values, and (3) association of bTMB and tTMB with time to CPI therapy failure.

RESULTS

In 410 patient-matched bTMB-tTMB pairs, the median bTMB (m = 10.5 mut/Mb) was significantly higher than the median tTMB (m = 6.0 mut/Mb, P < .001) leading to conflicting "high" and "low" statuses in over one-third of cases at a threshold of 10 mut/Mb (n = 410). Significant differences were observed in the distribution of bTMB values from blood-NGS vendors, with guardant health (GH) reporting higher (m = 10.5 mut/Mb, n = 2183) than Foundation Medicine (FMI, m = 3.8 mut/Mb, n = 462, P < .001). bTMB from GH required a higher threshold (≥40 mut/Mb) than bTMB from FMI (≥12 mut/Mb) in order to be associated with CPI response.

CONCLUSIONS

This study uncovers variability in bTMB reporting among commercial NGS platforms, thereby evidencing a need for assay-specific thresholds in identifying patients who may respond to CPI therapy.