Determining homologous recombination deficiency scores with whole exome sequencing and their association with responses to neoadjuvant chemotherapy in breast cancer

AcornHRD: an HRD algorithm highly associated with anthracycline-based neoadjuvant chemotherapy in breast cancer in China

PURPOSE

Our study aimed to develop and validate a homologous recombination deficiency (HRD) scoring algorithm in the Chinese breast cancer population.

METHODS AND MATERIALS

Ninety-six in-house breast cancer (BC) samples and 6 HRD-positive standard cells were analyzed by whole-genome sequencing (WGS). Besides, 122 BCs from the TCGA database were down-sampled to ~ 1X WGS. We constructed an algorithm named AcornHRD for HRD score calculated based on WGS at low coverage as input data to estimate large-scale copy number alteration (LCNA) events on the genome. A clinical cohort of 50 BCs (15 cases carrying BRCA mutation) was used to assess the association between HRD status and anthracyclines-based neoadjuvant treatment outcomes.

RESULTS

A 100-kb window was defined as the optimal size using 41 in-house cases and the TCGA dataset. HRD score high threshold was determined as HRD score ≥ 10 using 55 in-house BCs with BRCA mutation to achieve a 95% BRCA-positive agreement rate. Furthermore, the HRD status agreement rate of AcornHRD is 100%, while the ShallowHRD is 60% in standard cells. BRCA mutation was significantly associated with a high HRD score evaluated by AcornHRD and ShallowHRD (p = 0.008 and p = 0.003, respectively) in the TCGA dataset. However, AcornHRD showed a higher positive agreement rate than did the ShallowHRD algorithm (70% vs 60%). In addition, the BRCA-positive agreement rate of AcornHRD was superior to that of ShallowHRD (87% vs 13%) in the clinical cohort. Importantly, the high HRD score assessed by AcornHRD was significantly correlated with a residual cancer burden score of 0 or 1 (RCB0/1). Besides, the HRD-positive group was more likely to respond to anthracycline-based chemotherapy than the HRD-negative group (pCR [OR = 9.5, 95% CI 1.11-81.5, p = 0.040] and RCB0/1 [OR = 10.29, 95% CI 2.02-52.36, p = 0.005]).

CONCLUSION

Using the AcornHRD algorithm evaluation, our analysis demonstrated the high performance of the LCNA genomic signature for HRD detection in breast cancers.

Homologous Recombination Abnormalities Associated With BRCA1/2 Mutations as Predicted by Machine Learning of Targeted Next-Generation Sequencing Data

Background

Homologous recombination deficiency (HRD) is the hallmark of breast cancer gene 1/2 (BRCA1/2)-mutated tumors and the unique biomarker for predicting response to double-strand break (DSB)-inducing drugs. The demonstration of HRD in tumors with mutations in genes other than BRCA1/2 is considered the best biomarker of potential response to these DSB-inducer drugs.

Objectives

We explored the potential of developing a practical approach to predict in any tumor the presence of HRD that is similar to that seen in tumors with BRCA1/2 mutations using next-generation sequencing (NGS) along with machine learning (ML).

Design

We use copy number alteration (CNA) generated from routine-targeted NGS data along with a modified naïve Bayesian model for the prediction of the presence of HRD.

Methods

The CNA from NGS of 434 targeted genes was analyzed using CNVkit software to calculate the log2 of CNA changes. The log2 values of various sequencing reads (bins) were used in ML to train the system on predicting tumors with BRCA1/2 mutations and tumors with abnormalities similar to those detected in BRCA1/2 mutations.

Results

Using 31 breast or ovarian cancers with BRCA1/2 mutations and 84 tumors without mutations in any of 12 homologous recombination repair (HRR) genes, the ML demonstrated high sensitivity (90%, 95% confidence interval [CI] = 73%-97.5%) and specificity (98%, 95% CI = 90%-100%). Testing of 114 tumors with mutations in HRR genes other than BRCA1/2 showed 39% positivity for HRD similar to that seen in BRCA1/2. Testing 213 additional wild-type (WT) cancers showed HRD positivity similar to BRCA1/2 in 32% of cases. Correlation with proportional loss of heterozygosity (LOH) as determined using whole exome sequencing of 51 samples showed 90% (95% CI = 72%-97%) concordance. The approach was also validated in an independent set of 1312 consecutive tumor samples.

Conclusions

These data demonstrate that CNA when combined with ML can reliably predict the presence of BRCA1/2 level HRD with high specificity. Using BRCA1/2 mutant cases as gold standard, this ML can be used to predict HRD in cancers with mutations in other HRR genes as well as in WT tumors.

RNA-Based Classification of Homologous Recombination Deficiency in Racially Diverse Patients with Breast Cancer

BACKGROUND

Aberrant expression of DNA repair pathways such as homologous recombination (HR) can lead to DNA repair imbalance, genomic instability, and altered chemotherapy response. DNA repair imbalance may predict prognosis, but variation in DNA repair in diverse cohorts of breast cancer patients is understudied.

METHODS

To identify RNA-based patterns of DNA repair expression, we performed unsupervised clustering on 51 DNA repair-related genes in the Cancer Genome Atlas Breast Cancer [TCGA BRCA (n = 1,094)] and Carolina Breast Cancer Study [CBCS (n = 1,461)]. Using published DNA-based HR deficiency (HRD) scores (high-HRD ≥ 42) from TCGA, we trained an RNA-based supervised classifier. Unsupervised and supervised HRD classifiers were evaluated in association with demographics, tumor characteristics, and clinical outcomes.

RESULTS

: Unsupervised clustering on DNA repair genes identified four clusters of breast tumors, with one group having high expression of HR genes. Approximately 39.7% of CBCS and 29.3% of TCGA breast tumors had this unsupervised high-HRD (U-HRD) profile. A supervised HRD classifier (S-HRD) trained on TCGA had 84% sensitivity and 73% specificity to detect HRD-high samples. Both U-HRD and S-HRD tumors in CBCS had higher frequency of TP53 mutant-like status (45% and 41% enrichment) and basal-like subtype (63% and 58% enrichment). S-HRD high was more common among black patients. Among chemotherapy-treated participants, recurrence was associated with S-HRD high (HR: 2.38, 95% confidence interval = 1.50-3.78).

CONCLUSIONS

HRD is associated with poor prognosis and enriched in the tumors of black women.

IMPACT

RNA-level indicators of HRD are predictive of breast cancer outcomes in diverse populations.

Pan-cancer analysis reveals homologous recombination deficiency score as a predictive marker for immunotherapy responders

The immune context of the tumor microenvironment (TME) is critical for effective immunotherapy. Nonetheless, DNA-based biomarkers for the immune-sensitive TME and the identification of immune checkpoint inhibitor (ICI) responders are under-explored. This study aims to comprehensively landscape the homologous recombination deficiency (HRD) score, an emerging hallmark for tumor genome instability that triggers immune responsiveness across major cancer types, and to unveil their link to the TME and immunotherapeutic response. The HRD-associated genomic scars were characterized in 9088 tumor samples across 32 cancer types from TCGA. We evaluated the HRD score's performance in classifying ICI responders using an independent breast cancer cohort (GSE87049) and 11 in vivo murine mammary tumor models treated with anti-PD1/CTLA4 regimen (GSE124821). This study revealed a broad association between HRD-high genotype and neoantigenesis in the major cancer types including bladder cancer, breast cancer, head and neck squamous carcinoma, lung adenocarcinoma, lung squamous cell carcinoma, ovarian cancer, and sarcoma. Tumors with high HRD score bears increased leukocyte infiltration and lymphocyte fraction and demonstrated immune-sensitive microenvironment. The tumor immune dysfunction and exclusion (TIDE) model further confirmed HRD score-high genotype as a potential predictor for ICI immunotherapy responders in breast cancer. In conclusion, tumors with high HRD score exhibit an immune-sensitive TME. The HRD-high genotype is a promising marker for identifying ICI therapy responders among breast cancer patients.

Prevalence of mutations in BRCA and homologous recombination repair genes and real-world standard of care of Asian patients with HER2-negative metastatic breast cancer starting first-line systemic cytotoxic chemotherapy: subgroup analysis of the global BREAKOUT study

Background

The multinational BREAKOUT study (NCT03078036) sought to determine the prevalence of germline BRCA1/2 (gBRCA1/2) and somatic BRCA1/2 (sBRCA1/2) mutations and mutations in other homologous recombination repair (HRR) genes in women with HER2-negative metastatic breast cancer (MBC) starting first-line chemotherapy.

Methods

Genetic testing for gBRCA, sBRCA, and HRR gene mutations was performed in patients who started first-line chemotherapy for MBC in the last 90 days (341 patients across 14 countries) who were not selected based on risk factors for gBRCA mutations. We report data from the Asian cohort, which included patients in Japan (7 sites), South Korea (10 sites), and Taiwan (8 sites).

Results

Of 116 patients screened, 104 patients were enrolled in the Asian cohort. The median age was 53.0 (range 25–87) years. gBRCA1/2, gBRCA1, and gBRCA2 mutations were detected in 10.6% (11/104), 5.8% (6/104), and 4.8% (5/104) of patients, respectively; none had mutations in both gBRCA1 and gBRCA2. gBRCA1/2 mutations were detected in 10.0% (6/60) and 11.6% (5/43) of patients with hormone receptor-positive and triple-negative MBC, respectively. HRR gene mutations were tested in 48 patients without gBRCA mutations, and 5 (10.4%) had at least one HRR mutation in sBRCA, ATM, PALB2, and CHEK2.

Conclusion

We report for the first time the prevalence of gBRCA and HRR mutations in an Asian cohort of patients with HER2-negative MBC. Our results suggest that BRCA mutation testing is valuable to determine appropriate treatment options for patients with hormone receptor-positive or triple-negative MBC.

Study registration

NCT03078036.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12282-021-01283-4.