Genetic mutation profile of Chinese HER2-positive breast cancers and genetic predictors of responses to Neoadjuvant anti-HER2 therapy

Next-generation sequencing based deep learning model for prediction of HER2 status and response to HER2-targeted neoadjuvant chemotherapy

INTRODUCTION

For patients with breast cancer, the amplification of Human Epidermal Growth Factor 2 (HER2) is closely related to their prognosis and treatment decisions. This study aimed to further improve the accuracy and efficiency of HER2 amplification status detection with a deep learning model, and apply the model to predict the efficacy of neoadjuvant therapy.

METHODS

We combined Next-Generation Sequencing (NGS) data and IHC staining images of 606 breast cancer patients and developed a Vision Transformer (ViT) deep learning model to identify the amplification of HER2 through these IHC staining images. This model was then applied to predict the efficacy of neoadjuvant therapy in 399 HER2-positive breast cancer patients.

RESULTS

The NGS data of 606 patients were split into training (N = 404), validation (N = 101), and testing (N = 101) sets. The top 3 genes with highest mutation frequency were TP53, ERBB2 and PIK3CA. With the NGS results as deep learning model labels, the accuracy of our ViT model was 93.1% for HER2 amplification recognition. The misidentifications was likely due to the heterogeneity of HER2 expression in cancer tissues. For predicting the efficacy of neoadjuvant therapy, receiver operating characteristic (ROC) curves were plotted, and the combination of image recognition result and clinical pathological features yielded an area under the curve (AUC) value of 0.855 in the training set and 0.841 in the testing set.

CONCLUSIONS

Our study provided a method of HER2 status recognition based on IHC images, improving the efficiency and accuracy of HER2 status assessment, and can be used for predicting the efficacy of anti-HER2 targeted neoadjuvant therapy. We intend our deep learning model to assist pathologists in HER2 amplification recognition.

Genomic and transcriptomic profiling of inflammatory breast cancer reveals distinct molecular characteristics to non-inflammatory breast cancers

PURPOSE

Inflammatory breast cancer (IBC), a rare and highly aggressive form of breast cancer, accounts for 10% of breast cancer-related deaths. Previous omics studies of IBC have focused solely on one of genomics or transcriptomics and did not discover common differences that could distinguish IBC from non-IBC.

METHODS

Seventeen IBC patients and five non-IBC patients as well as additional thirty-three Asian breast cancer samples from TCGA-BRCA were included for the study. We performed whole-exon sequencing (WES) to investigate different somatic genomic alterations, copy number variants, and large structural variants between IBC and non-IBC. Bulk RNA sequencing (RNA-seq) was performed to examine the differentially expressed genes, pathway enrichment, and gene fusions. WES and RNA-seq data were further investigated in combination to discover genes that were dysregulated in both genomics and transcriptomics.

RESULTS

Copy number variation analysis identified 10 cytobands that showed higher frequency in IBC. Structural variation analysis showed more frequent deletions in IBC. Pathway enrichment and immune infiltration analysis indicated increased immune activation in IBC samples. Gene fusions including CTSC-RAB38 were found to be more common in IBC. We demonstrated more commonly dysregulated RAS pathway in IBC according to both WES and RNA-seq. Inhibitors targeting RAS signaling and its downstream pathways were predicted to possess promising effects in IBC treatment.

CONCLUSION

We discovered differences unique in Asian women that could potentially explain IBC etiology and presented RAS signaling pathway as a potential therapeutic target in IBC treatment.

Exploring the effectiveness of molecular subtypes, biomarkers, and genetic variations as first-line treatment predictors in Asian breast cancer patients: a systematic review and meta-analysis

BACKGROUND

Breast cancer incidence has been on the rise significantly in the Asian population, occurring at an earlier age and a later stage. The potential predictive value of molecular subtypes, biomarkers, and genetic variations has not been deeply explored in the Asian population. This study evaluated the effect of molecular subtype classification and the presence or absence of biomarkers and genetic variations on pathological complete response (pCR) after neoadjuvant treatment in Asian breast cancer patients.

METHODS

A systematic search was conducted in MEDLINE (PubMed), Science Direct, Scopus, and Cochrane Library databases. Studies were selected if they included Asian breast cancer patients treated with neoadjuvant chemotherapy and contained data for qualitative or quantitative analyses. The quality of the included studies was assessed using the Newcastle Ottawa Scale. Following the random effects model, pooled odds ratios or hazard ratios with 95% confidence intervals for pCR were analysed using Review Manager Software. Heterogeneity between studies was assessed using Cochran's Q-test and I2 test statistics.

RESULTS

In total, 19,708 Asian breast cancer patients were pooled from 101 studies. In the neoadjuvant setting, taxane-anthracycline (TA) chemotherapy showed better pCR outcomes in triple-negative breast cancer (TNBC) (p<0.0001) and human epidermal growth factor receptor 2 enriched (HER2E) (p<0.0001) than luminal breast cancer patients. Similarly, taxane-platinum (TP) chemotherapy also showed better pCR outcomes in TNBC (p<0.0001) and HER2E (p<0.0001). Oestrogen receptor (ER)-negative, progesterone receptor (PR)-negative, HER2-positive and high Ki-67 were significantly associated with better pCR outcomes when treated with either TA or TP. Asian breast cancer patients harbouring wildtype PIK3CA were significantly associated with better pCR outcomes when treated with TA in the neoadjuvant setting (p=0.001).

CONCLUSIONS

In the neoadjuvant setting, molecular subtypes (HER2E and TNBC), biomarkers (ER, PR, HER2, HR, Ki-67, nm23-H1, CK5/6, and Tau), and gene (PIK3CA) are associated with increased pCR rates in Asian breast cancer patients. Hence, they could be further explored for their possible role in first-line treatment response, which can be utilised to treat breast cancer more efficiently in the Asian population. However, it needs to be further validated with additional powered studies.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42021246295.

Predictive markers for pathological complete response (pCR) after neo-adjuvant chemotherapy in HER2-positive breast carcinoma

OBJECTIVES

Patients with HER2-positive invasive breast cancer that is node-positive and/or larger than 3 cm are generally treated with neoadjuvant chemotherapy (NAC). We aimed to identify predictive markers for pathological complete response (pCR) after NAC in HER2-positive breast carcinoma.

METHODS

Hematoxylin/eosin-stained slides of 43 HER2-positive breast carcinoma biopsies were histopathologically reviewed. Immunohistochemistry (IHC) was performed on pre-NAC biopsies, comprising HER2, estrogen receptor (ER), progesterone receptor (PR), Ki-67, epidermal growth factor receptor (EGFR), mucin-4 (MUC4), p53 and p63. Dual-probe HER2 in situ hybridization (ISH) was performed to study the mean HER2 and CEP17 copy numbers. ISH and IHC data were retrospectively collected for a validation cohort, comprising 33 patients.

RESULTS

Younger age at diagnosis, 3+ HER2 IHC scores, high mean HER2 copy numbers and high mean HER2/CEP17 ratios were significantly associated with an increased chance of achieving a pCR, and the latter two associations were confirmed in the validation cohort. No other immunohistochemical or histopathological markers were associated with pCR.

CONCLUSIONS

This retrospective study of two community-based NAC-treated HER2-positive breast cancer patient cohorts identified high mean HER2 copy numbers as a strong predictor for pCR. Further studies on larger cohorts are required to determine a precise cut-point for this predictive marker.

The impact of genomic context on outcomes of solid cancer patients treated with genotype-matched targeted therapies: a comprehensive review

INTRODUCTION

A critical need in the field of genotype-matched targeted therapy in cancer is to identify patients unlikely to respond to precision medicines. This will manage expectations of individualised therapies and avoid clinical progression to a point where institution of alternative treatments might not be possible. We examined the evidence base of the impact of genomic context on which targeted alterations are inscribed to identify baseline biomarkers distinguishing those obtaining the expected response from those with less benefit from targeted therapies.

METHODS

A comprehensive narrative review was conducted: scoping searches were undertaken in PubMed, Cochrane Database of Systematic Reviews, and PROSPERO. Outcomes included in meta-analysis were progression-free and overall survival. Data were extracted from Kaplan-Meier and used to calculate hazard ratios. Studies presenting data on two molecular subcohorts (e.g. co-mutation versus no co-mutation) were included in fixed meta-analysis. Other studies were used for descriptive purposes.

RESULTS

The presence of concomitant driver mutations, higher tumour mutational burden (TMB), greater copy number burden, and APOBEC signatures significantly reduces benefits of targeted therapy in lung cancers in never smokers (LCINS - less than 100 cigarettes per lifetime) and breast cancer, cancers with low TMB. LCINS have significantly poorer outcomes if their cancers harbour p53 co-mutations, an effect also seen in human epidermal growth factor receptor 2-positive (HER2+) breast cancer patients (trastuzumab) and head and neck cancer patients [phosphoinositide 3-kinase (PI3K) inhibition]. PI3K co-alterations have less impact when targeting epidermal growth factor receptor mutations and anaplastic lymphoma kinase fusions, but significantly reduce the impact of targeting HER2 and MET amplifications. SMARCA4 co-mutations predict for poor outcome in patients treated with osimertinib and sotorasib. In BRAF-mutant melanoma, whilst there are no genomic features distinguishing exceptional responders from primary progressors, there are clear transcriptomic features dichotomising these outcomes.

CONCLUSION

To our knowledge, this is the most comprehensive review to date of the impact of genomic context on outcomes with targeted therapy. It represents a valuable resource informing progress towards contextualised precision medicine.

Association of PIK3CA mutation with outcomes in HER2-positive breast cancer treated with anti-HER2 therapy: A meta-analysis and bioinformatic analysis of TCGA‑BRCA data

BACKGROUND

This study aimed to comprehensively explore the clinical significance of PIK3CA mutation in human epidermal growth factor receptor 2 (HER2)-positive breast cancer treated with anti-HER2 therapy.

METHODS

We systematically searched PubMed, Embase, and the Cochrane databases for eligible studies assessing the association between PIK3CA mutation and outcomes in patients with HER2-positive breast cancer receiving anti-HER2 therapy. The main outcomes included: (1) pathological complete response (pCR) or disease-free survival (DFS) for the neoadjuvant setting; (2) DFS or invasive DFS for the adjuvant setting; (3) objective response rate (ORR), progression-free survival (PFS), time-to-progression (TTP), or overall survival (OS) for the metastatic setting. The mutational landscape of HER2-positive breast cancer according to PIK3CA mutation status was examined based on TCGA breast cancer dataset.

RESULTS

Totally, 43 eligible studies, covering 11,099 patients with available data on PIK3CA mutation status, were identified. In the neoadjuvant setting, PIK3CA mutation was significantly associated with a lower pCR rate (OR=0.23, 95% CI 0.19-0.27, p<0.001). This association remained significant irrespective of the type of anti-HER2 therapy (single-agent or dual-agent) and hormone receptor status. There were no significant differences in DFS between PIK3CA mutated and wild-type patients in either the neoadjuvant or adjuvant settings. In the metastatic setting, PIK3CA mutation predicted worse ORR (OR=0.26, 95%CI 0.17-0.40, p<0.001), PFS (HR=1.28, 95%CI 1.03-1.59, p = 0.024) and TTP (HR=2.27, 95%CI 1.54-3.34, p<0.001). However, no significant association was observed between PIK3CA mutation status and OS. Distinct mutational landscapes were observed in HER2-positive breast cancer between individuals with PIK3CA mutations and those with wild-type PIK3CA.

CONCLUSIONS

PIK3CA mutation was significantly associated with a lower pCR rate in HER2-positive breast cancer treated with neoadjuvant anti-HER2 therapy. In the metastatic setting, PIK3CA mutation was predictive of worse ORR, PFS and TTP. These results suggest the potential for developing PI3K inhibitors as a therapeutic option for these patients.

Clinical implication of genetic composition and molecular mechanism on treatment strategies of HER2-positive breast cancers

The current clinical management model of HER2-positive breast cancers is commonly based on guidelines, which in turn are based on the design and outcome of clinical trials. While this model is useful to most practicing clinicians, the treatment outcome of individual patient is not certain at the start of treatment. As the understanding of the translational research of carcinogenesis and the related changes in cancer genetics and tumor microenvironment during treatment is critical in the selection of right choice of treatment to maximize the successful clinical outcome for the patient, this review article intends to discuss the latest developments in the genetic and molecular mechanisms of cancer progression and treatment resistance, and how they influence the planning of the treatment strategies of HER2-positive breast cancers.

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.