Characterization of Frequently Mutated Cancer Genes and Tumor Mutation Burden in Chinese Breast Cancer

Exploring breast cancer associated-gene panel for next-generation sequencing and identifying new, pathogenic variants in breast cancer from western China

Breast cancer (BC) is the most frequently diagnosed and the leading cause of cancer-related deaths among women worldwide. It is crucial to develop a cost-effective BC genetic panel for detection and diagnosis. In this study, tissue samples from 52 BC patients and peripheral blood samples from 18 healthy volunteers were collected in western China, followed by gDNA extraction. H&E and IHC analysis were employed to detect the expression of invasive BC tissues. We analyzed data using public databases such as COSMIC/ClinVar/HGMD along with our own previously published data and queried commercial BC panels to select high-risk genes. Using Illumina DesignStudio, gene panel primers consisting of 13 genes were designed with 696 primer pairs. The specificity of all primers was validated through common PCR assays. Once the gene panel was completed, multiple polymerase chain reactions (MPCR) were performed using the designed panel primers. The resulting MPCR products were purified to enrich them as library templates. Subsequently, after passing quality tests for library integrity assessment, Next-generation sequencing (NGS) was conducted. Through bioinformatics analysis of the NGS data, 4,571 variants were identified in the annotation files from 52 samples, classified into different types. Among these variants, 358 (approximately 7.8%) were newly discovered and distributed across 11 genes in 52 patients without in the ExAC database. The KMT2C gene exhibited the highest frequency of variants, presenting in 83.0% of 52 patient samples. Variants in BRCA2 (71%), BRCA1 (48%), PALB2 (40%), PIK3CA (23%), and RNF40 (21%) genes were found in over 20% of patients. Additionally, variants were observed in the AKT1 (12%), ERBB2 (10%), ESR1 (8%), TWIST1 (8%), and PIK3R1 (4%) genes. Further analysis using PolyPhen-2, SIFT, CADD, and Mutation Taster tools analysis showed that out of these new variants, 49 (49/358) had potential pathogenic effects on protein functions and structure across 52 patients. Consequently, a high-risk gene panel has been preliminarily established for early detection/diagnosis that will contribute to earlier prevention and treatment strategies for individuals with BC, particularly those residing in developing or underdeveloped countries. The identification of novel pathogenic variants within our cohort not only expands knowledge regarding genetic diagnosis applications for BC patients but also facilitates genetic counseling services for affected individuals and their families.

Joint Screening for Ultra-High Dimensional Multi-Omics Data

Investigators often face ultra-high dimensional multi-omics data, where identifying significant genes and omics within a gene is of interest. In such data, each gene forms a group consisting of its multiple omics. Moreover, some genes may also be highly correlated. This leads to a tri-level hierarchical structured data: the cluster level, which is the group of correlated genes, the subgroup level, which is the group of omics of the same gene, and the individual level, which consists of omics. Screening is widely used to remove unimportant variables so that the number of remaining variables becomes smaller than the sample size. Penalized regression with the remaining variables after performing screening is then used to identify important variables. To screen unimportant genes, we propose to cluster genes and conduct screening. We show that the proposed screening method possesses the sure screening property. Extensive simulations show that the proposed screening method outperforms competing methods. We apply the proposed variable selection method to the TCGA breast cancer dataset to identify genes and omics that are related to breast cancer.

DNA damage response in breast cancer and its significant role in guiding novel precise therapies

DNA damage response (DDR) deficiency has been one of the emerging targets in treating breast cancer in recent years. On the one hand, DDR coordinates cell cycle and signal transduction, whose dysfunction may lead to cell apoptosis, genomic instability, and tumor development. Conversely, DDR deficiency is an intrinsic feature of tumors that underlies their response to treatments that inflict DNA damage. In this review, we systematically explore various mechanisms of DDR, the rationale and research advances in DDR-targeted drugs in breast cancer, and discuss the challenges in its clinical applications. Notably, poly (ADP-ribose) polymerase (PARP) inhibitors have demonstrated favorable efficacy and safety in breast cancer with high homogenous recombination deficiency (HRD) status in a series of clinical trials. Moreover, several studies on novel DDR-related molecules are actively exploring to target tumors that become resistant to PARP inhibition. Before further clinical application of new regimens or drugs, novel and standardized biomarkers are needed to develop for accurately characterizing the benefit population and predicting efficacy. Despite the promising efficacy of DDR-related treatments, challenges of off-target toxicity and drug resistance need to be addressed. Strategies to overcome drug resistance await further exploration on DDR mechanisms, and combined targeted drugs or immunotherapy will hopefully provide more precise or combined strategies and expand potential responsive populations.

A structured iterative division approach for non-sparse regression models and applications in biological data analysis

In this paper, we focus on the modeling problem of estimating data with non-sparse structures, specifically focusing on biological data that exhibit a high degree of relevant features. Various fields, such as biology and finance, face the challenge of non-sparse estimation. We address the problems using the proposed method, called structured iterative division. Structured iterative division effectively divides data into non-sparse and sparse structures and eliminates numerous irrelevant variables, significantly reducing the error while maintaining computational efficiency. Numerical and theoretical results demonstrate the competitive advantage of the proposed method on a wide range of problems, and the proposed method exhibits excellent statistical performance in numerical comparisons with several existing methods. We apply the proposed algorithm to two biology problems, gene microarray datasets, and chimeric protein datasets, to the prognostic risk of distant metastasis in breast cancer and Alzheimer's disease, respectively. Structured iterative division provides insights into gene identification and selection, and we also provide meaningful results in anticipating cancer risk and identifying key factors.

Germline rare variants in HER2-positive breast cancer predisposition: a systematic review and meta-analysis

Introduction

Approximately 10% of breast cancer (BC) cases result from hereditary causes. Genetic testing has been widely implemented in BC care to determine hereditary cancer syndromes and personalized medicine. Thus, identification of individuals carrying germline pathogenic variants could be useful to provide appropriate prophylactic or screening measures for each BC subtype, however, there are few formal recommendations for genetic testing in this sense so far. In this study, we assessed rare germline variants in a specific group of genes in order to determine the association with human epidermal growth factor 2 enriched (HER2+) BC phenotype through a systematic review and meta-analysis comparing subtypes overexpressing HER2 with other clinically recognized subtypes of BC. This review was registered with PROSPERO (ID: CRD42023447571).

Methods

We conducted an online literature search in PubMed (MEDLINE), Scopus, and EMBASE databases. We included original studies that investigated germline variants in HER2+ BC patients and selected the studies that reported only rare and/or pathogenic germline variants. We assessed the risk of bias and quality of the studies using the Joanna Briggs Institute Critical Appraisal checklists and the Modified Newcastle-Ottawa Scale for Genetic Studies, respectively. Considering hormone receptor and HER2 expression status, we compared gene-based risks initially in HR-HER2-, HR+HER2-, HR+HER2+, and HR-HER2+ groups, conducting separate meta-analyses using the random effects model for each comparison, and within them for each gene.

Results

Of the total 36 studies describing germline variants, 11 studies provided information on the prevalence of variants in the different clinically relevant BC subtypes and allowed comparisons. Germline variants within eight genes showed significant differences when meta-analyzed between the BC groups: BRCA1, BRCA2, TP53, ATM, CHEK2, PALB2, RAD51C, and BARD1. Notably, TP53, ATM, and CHEK2 germline variants were identified as predisposing factors for HER2+ subtypes, whereas BRCA1, BRCA2, PALB2, RAD51C, and BARD1 germline variants were associated with a predisposition to low HER2 expression. Main concerns about bias and quality assessment were the lack of confounding factors control; and comparability or outcome assessment, respectively.

Discussion

Our findings underscore the connection between germline variants and differential expression of the HER2 protein and BC subtypes.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO, identifier CRD42023447571.

Development and validation of a random survival forest model for predicting long-term survival of early-stage young breast cancer patients based on the SEER database and an external validation cohort

Young breast cancer (YBC) patients often face a poor prognosis, hence it's necessary to construct a model that can accurately predict their long-term survival in early stage. To realize this goal, we utilized data from the Surveillance, Epidemiology, and End Results (SEER) databases between January 2010 and December 2020, and meanwhile, enrolled an independent external cohort from Tianjin Medical University Cancer Institute and Hospital. The study aimed to develop and validate a prediction model constructed using the Random Survival Forest (RSF) machine learning algorithm. By applying the Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, we pinpointed key prognostic factors for YBC patients, which were used to create a prediction model capable of forecasting the 3-year, 5-year, 7-year, and 10-year survival rates of YBC patients. The RSF model constructed in the study demonstrated exceptional performance, achieving C-index values of 0.920 in the training set, 0.789 in the internal validation set, and 0.701 in the external validation set, outperforming the Cox regression model. The model's calibration was confirmed by Brier scores at various time points, showcasing its excellent accuracy in prediction. Decision curve analysis (DCA) underscored the model's importance in clinical application, and the Shapley Additive Explanations (SHAP) plots highlighted the importance of key variables. The RSF model also proved valuable in risk stratification, which has effectively categorized patients based on their survival risks. In summary, this study has constructed a well-performed prediction model for the evaluation of prognostic factors influencing the long-term survival of early-stage YBC patients, which is significant in risk stratification when physicians handle YBC patients in clinical settings.

Somatic mutations in a multigene panel and impact on prognosis based on TP53 status in Chinese HER2-positive patients undergoing neoadjuvant therapy: A single-institution retrospective cohort

BACKGROUND

Gene mutations play a crucial role in the occurrence and development of tumors, particularly in breast cancer (BC). Neoadjuvant therapy (NAT) has shown greater clinical benefit in HER2-positive breast cancer. However, further clinical investigation is needed to fully understand the correlation between genetic mutations and NAT efficacy and the long-term prognosis in HER2-positive BC.

METHODS

This was a retrospective cohort study of 222 patients receiving NAT between 2017 and 2021 in the Department of Breast Surgery of Fudan University Shanghai Cancer Center. Tumor samples from these patients were subjected to Next Generation Sequencing (NGS) to analyze mutations in 513 cancer-related genes. This study aimed to investigate the association between these genetic mutations and postoperative pathological complete response (pCR), as well as their impact on disease-free survival (DFS).

RESULTS

In total, 48.65% patients reached pCR, ER-negative status (p < 0.001), PR-negative status (p < 0.001), Ki67 ≥ 20 (p = 0.011), and dual-targeted therapy (p < 0.001) were all associated with enhanced pCR rates. The frequency of somatic alterations in TP53 (60%), PIK3CA (15%), and ERBB2 (11%) was highest. In the HER2+/HR- cohort, patients who achieved pCR had a significant benefit in prognosis (HR = 3.049, p = 0.0498). KMT2C (p = 0.036) and TP53 (p = 0.037) mutations were significantly increased in patients with DFS events. Moreover, TP53 mutations had prognostic significance in HER2-positive BC patients with HR-negative (HR = 3.712, p = 0.027) and pCR (HR = 6.253, p = 0.027) status and who received herceptin-only targeted therapy (HR = 4.145, p = 0.011).

CONCLUSIONS

The genetic mutation profiles of Chinese HER2+ patients who received NAT were discrepant with respect to HR status or DFS events. TP53 mutations have significant prognostic value in patients with NAT for HER2-positive BC and patients benefit differently depending on HR status, the neoadjuvant regimen and response, which highlights the significance of genetic factors in treatment customization based on individual genetic and clinical characteristics.

Distinct clinicopathological characteristics, genomic alteration and prognosis in breast cancer with concurrent TP53 mutation and MYC amplification

BACKGROUND

Both TP53 mutation and MYC amplification indicate poor outcomes in breast cancer (BC), but the clinical values of concurrent TP53 and MYC alterations have not been well-characterized.

METHODS

A total of 494 BC patients diagnosed at Guangdong Provincial People's Hospital (GDPH) were retrospectively analyzed. Genomic alterations were determined using next-generation sequencing. Survival analysis was applied to assess the effects of genetic alterations on relapse-free survival. The prognosis was verified based on 1405 patients from METABRIC cohort. Additionally, we used logistic regression to identify the factors associated with pathological complete response (pCR) after neoadjuvant chemotherapy.

RESULTS

In GDPH cohort, patients with TP53/MYC co-alteration exhibited higher grade and stage, more positive HER2 status and higher Ki67 levels, but less luminal A subtypes. They also had more mutations in genes involved in ERBB and TGF-β signaling pathways, as well as exclusive FANCG/CDKN2B/QKI copy number amplifications and SUFU/HIST3H3/ERCC4/JUN/BCR mutations. Concurrent TP53 and MYC alterations independently increased hazards of relapse (HR, 5.425; 95% CI: 2.019-14.579; p < 0.001). They maintained independent significance for relapse-free (HR, 1.310; 95% CI: 1.012-1.697; p = 0.041) and overall survival (HR, 1.373; 95% CI: 1.093-1.725; p = 0.006) in METABRIC cohort. Among the 81 patients receiving chemotherapy, TP53 mutation (OR, 5.750; 95% CI: 1.553-25.776; p = 0.013) and earlier stage (OR, 0.275; 95% CI 0.088-0.788; p = 0.020) were associated with pCR, while the co-alteration did not serve as an independent predictor (p = 0.199).

CONCLUSIONS

TP53/MYC co-alteration was associated with distinct clinicopathological and genomic features. They also conferred unfavorable prognosis in BC patients, and did not improve pCR after neoadjuvant chemotherapy.

Stepwise evolutionary genomics of early-stage lung adenocarcinoma manifesting as pure, heterogeneous and part-solid ground-glass nodules

BACKGROUND

This study was designed to unravel the genomic landscape and evolution of early-stage subsolid lung adenocarcinomas (SSN-LUADs) manifesting as pure ground-glass nodules (pGGNs), heterogeneous ground-glass nodules (HGGNs) and part-solid nodules (PSNs).

METHODS

Samples subjected to either broad-panel next-generation sequencing (NGS) or whole-exome sequencing (WES) were included. Clinicopathologic and genomic features were compared among pGGN, HGGN and PSN, while tumour evolutionary trajectories and mutational signatures were evaluated in the entire cohort.

RESULTS

In total, 247 SSN-LUAD samples subjected to broad-panel NGS and 125 to WES were identified. Compared with PSNs, HGGNs had significantly lower tumour mutation count (P < 0.001), genomic alteration count (P < 0.001), and intra-tumour heterogeneity (P = 0.005). Statistically significant upward trends were observed in alterations involving driver mutations and oncogenic pathways from pGGNs to HGGNs to PSNs. EGFR mutation was proved to be a key early event in the progression of SSN-LUADs, with subsequently two evolutionary trajectories involving either RBM10 or TP53 mutation in the cancer-evolution models.

CONCLUSIONS

This study provided evidence for unravelling the previously unknown genomic underpinnings associated with SSN-LUAD evolution from pGGN to HGGN to PSN, proving that HGGN was an intermediate SSN form between pGGN and PSN genetically.

A Tale of Two Cancers: A Current Concise Overview of Breast and Prostate Cancer

Cancer is a global issue, and it is expected to have a major impact on our continuing global health crisis. As populations age, we see an increased incidence in cancer rates, but considerable variation is observed in survival rates across different geographical regions and cancer types. Both breast and prostate cancer are leading causes of morbidity and mortality worldwide. Although cancer statistics indicate improvements in some areas of breast and prostate cancer prevention, diagnosis, and treatment, such statistics clearly convey the need for improvements in our understanding of the disease, risk factors, and interventions to improve life span and quality of life for all patients, and hopefully to effect a cure for people living in developed and developing countries. This concise review compiles the current information on statistics, pathophysiology, risk factors, and treatments associated with breast and prostate cancer.

Identification of mutation patterns and circulating tumour DNA-derived prognostic markers in advanced breast cancer patients

BACKGROUND

The correlations between circulating tumour DNA (ctDNA)-derived genomic markers and treatment response and survival outcome in Chinese patients with advanced breast cancer (ABC) have not been extensively characterized.

METHODS

Blood samples from 141 ABC patients who underwent first-line standard treatment in Peking University Cancer Hospital were collected. A next-generation sequencing based liquid biopsy assay (PredicineCARE) was used to detect somatic mutations and copy number variations (CNVs) in ctDNA. A subset of matched blood samples and tumour tissue biopsies were compared to evaluate the concordance.

RESULTS

Overall, TP53 (44.0%) and PIK3CA (28.4%) were the top two altered genes. Frequent CNVs included amplifications of ERBB2 (24.8%) and FGFR1 (8.5%) and deletions of CDKN2A (3.5%). PIK3CA/TP53 and FGFR1/2/3 variants were associated with drug resistance in hormone receptor-positive (HR +) and human epidermal growth factor receptor 2-positive (HER2 +) patients. The comparison of genomic variants across matched tumour tissue and ctDNA samples revealed a moderate to high concordance that was gene dependent. Triple-negative breast cancer (TNBC) patients harbouring TP53 or PIK3CA alterations had a shorter overall survival than those without corresponding mutations (P = 0.03 and 0.008). A high ctDNA fraction was correlated with a shorter progression-free survival (PFS) (P = 0.005) in TNBC patients. High blood-based tumor mutation burden (bTMB) was associated with a shorter PFS for HER2 + and TNBC patients (P = 0.009 and 0.05). Moreover, disease monitoring revealed several acquired genomic variants such as ESR1 mutations, CDKN2A deletions, and FGFR1 amplifications.

CONCLUSIONS

This study revealed the molecular profiles of Chinese patients with ABC and the clinical validity of ctDNA-derived markers, including the ctDNA fraction and bTMB, for predicting treatment response, prognosis, and disease progression.

TRIAL REGISTRATION

ClinicalTrials.gov ID: NCT03792529. Registered January 3rd 2019, https://clinicaltrials.gov/ct2/show/NCT03792529 .

Characteristics of MYC Amplification and Their Association with Clinicopathological and Molecular Factors in Patients with Breast Cancer

MYC amplification is detected in ∼15% of breast tumors and is associated with poor prognosis by mediating acquired resistance to anticancer therapies. This study aimed to determine the prevalence of MYC amplifications in Chinese women with breast cancer (BRCA) and investigate the correlation between MYC amplification and clinicopathological and molecular characteristics and its clinical implications. We analyzed MYC alterations in tissue specimens from 410 women diagnosed with BRCA in our hospital from June 1, 2017 to September 27, 2018. We compared our results with publicly available data from The Cancer Genome Atlas (TCGA) BRCA cohort (n = 1079). MYC amplification was identified in 12.4% (51/410) of our cohort, with mean copy number (CN) of 4.42 (range: 2.84-11.27). In TCGA cohort, MYC amplification was identified in 21.2% (229/1079) and was associated with age, estrogen receptor status, progesterone receptor status, human epidermal growth factor receptor 2 (HER2) status, and molecular subtype, whereas in our cohort, MYC amplification was associated with smaller tumor size (T1-2, p = 0.023) and higher Ki-67 levels (≥20%; p = 0.031). Analysis of molecular profiles revealed that MYC-amplified breast tumors had significantly more concurrent CN variations compared with MYC nonamplified BRCA in both Guangdong Provincial People's Hospital (GDPH) and TCGA cohorts (p < 0.001). Pathway mapping analysis demonstrated that MYC-amplified tumors had more mutations involved in 15 different but interrelated pathways critical in DNA repair, cell cycle, and cell proliferation. Patients in TCGA cohort with MYC-amplified hormone receptor (HR)-positive/HER2-positive BRCA (p = 0.038) and MYC nonamplified triple-negative BRCA (p = 0.027) had significantly shorter overall survival. In conclusion, this study contributes to a better understanding that MYC-amplified breast tumors had distinct clinicopathological and molecular features compared with MYC nonamplified breast tumors. Further research with a larger sample size is necessary to further elucidate the clinical and survival implications of MYC amplifications.

Clinicopathologic and Genomic Features in Triple-Negative Breast Cancer Between Special and No-Special Morphologic Pattern

Background

Triple-negative breast cancer (TNBC) is refractory and heterogeneous, comprising various entities with divergent phenotype, biology, and clinical presentation. As an aggressive subtype, Chinese TNBC patients with special morphologic patterns (STs) were restricted to its incidence of 10-15% in total TNBC population.

Methods

We recruited 89 patients with TNBC at Guangdong Provincial People’s Hospital (GDPH) from October 2014 to May 2021, comprising 72 cases of invasive ductal carcinoma of no-special type (NSTs) and 17 cases of STs. The clinical data of these patients was collected and statistically analyzed. Formalin-fixed, paraffin-embedded (FFPE) tumor tissues and matched blood samples were collected for targeted next-generation sequencing (NGS) with cancer-related, 520- or 33-gene assay. Immunohistochemical analysis of FFPE tissue sections was performed using anti-programmed cell death-ligand 1(PD-L1) and anti-androgen receptor antibodies.

Results

Cases with NSTs presented with higher histologic grade and Ki-67 index rate than ST patients (NSTs to STs: grade I/II/III 1.4%, 16.7%,81.9% vs 0%, 29.4%, 58.8%; p<0.05; Ki-67 ≥30%: 83.3% vs. 58.8%, p<0.05), while androgen receptor (AR) and PD-L1 positive (combined positive score≥10) rates were lower than of STs cases (AR: 11.1% vs. 47.1%; PD-L1: 9.6% vs. 33.3%, p<0.05). The most commonly altered genes were TP53 (88.7%), PIK3CA (26.8%), MYC (18.3%) in NSTs, and TP53 (68.8%), PIK3CA (50%), JAK3 (18.8%), KMT2C (18.8%) in STs respectively. Compared with NSTs, PIK3CA and TP53 mutation frequency showed difference in STs (47.1% vs 19.4%, p=0.039; 64.7% vs 87.5%, p=0.035).

Conclusions

In TNBC patients with STs, decrease in histologic grade and ki-67 index, as well as increase in PD-L1 and AR expression were observed when compared to those with NSTs, suggesting that TNBC patients with STs may better benefit from immune checkpoint inhibitors and/or AR inhibitors. Additionally, lower TP53 and higher PIK3CA mutation rates were also found in STs patients, providing genetic evidence for deciphering at least partly potential mechanism of action.

Breast cancer screening and early diagnosis in Chinese women

Breast cancer is the most common malignant tumor in Chinese women, and its incidence is increasing. Regular screening is an effective method for early tumor detection and improving patient prognosis. In this review, we analyze the epidemiological changes and risk factors associated with breast cancer in China and describe the establishment of a screening strategy suitable for Chinese women. Chinese patients with breast cancer tend to be younger than Western patients and to have denser breasts. Therefore, the age of initial screening in Chinese women should be earlier, and the importance of screening with a combination of ultrasound and mammography is stressed. Moreover, Chinese patients with breast cancers have several ancestry-specific genetic features, and aiding in the determination of genetic screening strategies for identifying high-risk populations. On the basis of current studies, we summarize the development of risk-stratified breast cancer screening guidelines for Chinese women and describe the significant improvement in the prognosis of patients with breast cancer in China.

Mutational Analysis of Triple-Negative Breast Cancer Using Targeted Kinome Sequencing

Purpose

Triple-negative breast cancer (TNBC) does not have defined therapeutic targets and is currently treated with chemotherapy only. Kinase dysregulation triggers cancer cell proliferation and metastasis and is a crucial therapeutic target for cancer. In this study, targeted kinome sequencing of TNBC tumors was performed to assess the association between kinome gene alterations and disease outcomes in TNBC.

Methods

A kinome gene panel consisting of 612 genes was used for the targeted sequencing of 166 TNBC samples and matched normal tissues. Analyses of the significantly mutated genes were performed. Genomic differences between Asian and non-Asian patients with TNBC were evaluated using two Asian TNBC datasets (from Seoul National University Hospital [SNUH] and Fudan University Shanghai Cancer Center [FUSCC]) and three non-Asian TNBC datasets (The Cancer Genome Atlas [TCGA], METABRIC, and Gustave Roussy). The prognostic value of kinome gene mutations was evaluated using tumor mutational burden (TMB) and oncogenic pathway analyses. Mutational profiles from the TCGA were used for validation.

Results

The significantly mutated genes included TP53 (60% of patients), PIK3CA (21%), BRCA2 (8%), and ATM (8%). Compared with data from non-Asian public databases, the mutation rates of PIK3CA p.H1047R/Q were significantly higher in the SNUH cohort (p = 0.003, 0.048, and 0.032, respectively). This was verified using the FUSCC dataset (p = 0.003, 0.078, and 0.05, respectively). The TMB-high group showed a trend toward longer progression-free survival in our cohort and the TCGA TNBC cohort (p = 0.041 and 0.195, respectively). Kinome gene alterations in the Wnt pathway in patients with TNBC were associated with poor survival in both datasets (p = 0.002 and 0.003, respectively).

Conclusion

Comprehensive analyses of kinome gene alterations in TNBC revealed genomic alterations that offer therapeutic targets and should help identify high-risk patients more precisely in future studies.