Biology subjects

Chin, S.-F.

Publications and source records attributed to Chin, S.-F..

12 recordsLinked to original sources

bioRxiv2026

Chemotherapy reshapes cellular clonal landscape via persister programs in breast cancer xenografts

Tumor ecosystems evolve in response to chemotherapy, but how treatment reshapes clonal architecture and the transcriptional programs of distinct cell states remains unclear. To investigate the response to chemotherapy by individual single cell-derived clones, we used a high-complexity lentiviral barcoding strategy by genetically labelling with unique, heritable and expressible barcode sequences individual cells from four human breast cancer patient-derived tumor xenograft models. We tracked 3,248 single cell-derived clones across 39 xenografts and profiled 676,292 cells with single cell RNA sequencing. The most striking changes following chemotherapy occurred in non-responsive xenografts, attributed to the emergence of previously minor cell clones that are chemotherapy resistant. In a triple negative model, epithelial and mesenchymal cell states showed distinct sensitivities to chemotherapy. ER+/HER2-models activated stress adaptive programs in response to carboplatin, highlighting DUSP1 and KLF4 as markers of platinum tolerance and a slow cycling, persister-like state. Together, these findings reveal that chemotherapy triggers an immediate and substantial reorganization of the cellular clonal landscape, driven by the selective engagement of stress response programs in cell clones that survive treatment.

cancer biology↗

bioRxiv2023

Clustering of HR+/HER2- breast cancer in an Asian cohort is driven by immune phenotypes

Breast cancer exhibits significant heterogeneity, manifesting in various subtypes that are critical in guiding treatment decisions. This study aimed to investigate the existence of distinct subtypes of breast cancer within the Asian population, by analysing the transcriptomic profiles of 934 breast cancer patients from a Malaysian cohort. Our findings reveal that the HR+/HER2-breast cancer samples display a distinct clustering pattern based on immune phenotypes, rather than conforming to the conventional luminal A-luminal B paradigm previously reported in breast cancers from women of European descent. This suggests that the activation of the immune system may play a more important role in Asian HR+/HER2-breast cancer than has been previously recognized. Analysis of somatic mutations by whole exome sequencing showed that counter-intuitively, the cluster of HR+/HER2-samples exhibiting higher immune scores was associated with lower tumour mutational burden, lower homologous recombination deficiency scores, and fewer copy number aberrations, implicating the involvement of non-canonical tumour immune pathways. Further investigations are warranted to determine the underlying mechanisms of these pathways, with the potential to develop innovative immunotherapeutic approaches tailored to this specific patient population.

cancer biology↗

bioRxiv2023

A large-scale retrospective study in metastatic breast cancer patients using circulating tumor DNA and machine learning to predict treatment outcome and progression-free survival

PurposeMonitoring levels of circulating tumor-derived DNA (ctDNA) represents a non-invasive snapshot of tumor burden and potentially clonal evolution. Here we describe how a novel statistical model that uses serial ctDNA measurements from shallow whole genome sequencing (sWGS) in metastatic breast cancer patients produces a rapid and inexpensive assessment that is predictive of treatment response and progression-free survival. Patients and MethodsA cohort of 188 metastatic breast cancer patients had DNA extracted from serial plasma samples (total 1098, median=4, mean=5.87). Plasma DNA was assessed using sWGS and the tumor fraction in total cell free DNA estimated using ichorCNA. This approach was compared with ctDNA targeted sequencing and serial CA 15-3 measurements. The longitudinal ichorCNA values were used to develop a Bayesian learning model to predict subsequent treatment response. ResultsWe identified a transition point of 7% estimated tumor fraction to stratify patients into different categories of progression risk using ichorCNA estimates and a time-dependent Cox model, validated across different breast cancer subtypes and treatments, outperforming the alternative methods. We then developed a Bayesian learning model to predict subsequent treatment response with a sensitivity of 0.75 and a specificity of 0.66. ConclusionIn patients with metastatic breast cancer, sWGS of ctDNA and ichorCNA provide prognostic and predictive real-time valuable information on treatment response across subtypes and therapies. A prospective large-scale clinical trial to evaluate clinical benefit of early treatment changes based on ctDNA levels is now warranted.

genomics↗

bioRxiv2022

Gene signature for predicting homologous recombination deficiency in triple-negative breast cancer

Triple-negative breast cancers (TNBCs) are a subset of breast cancers that have remained difficult to treat. Roughly 1 in 10 of TNBCs arise in individuals with pathogenic variants in BRCA1 or BRCA2, and treating BRCA-associated TNBCs with PARP inhibitors results in improved survival. A proportion of TNBCs arising in non-carriers of BRCA pathogenic variants have genomic features that are similar to BRCA carriers, and we postulated that gene expression may identify individuals with such features who might also benefit from PARP inhibitor treatment. Using genomic data from 129 TNBC samples from the Malaysian Breast Cancer (MyBrCa) cohort, we classified tumours as having high or low homologous recombination deficiency (HRD) and developed a gene expression-based machine learning classifier for HRD in TNBCs. The classifier identified samples with HRD mutational signature at an AUROC of 0.94 in the MyBrCa validation dataset, and strongly segregated HRD-associated genomic features in TNBCs from TCGA and METABRIC. Further validation of the classifier using the NanoString nCounter platform showed that the RNA-seq results correlated strongly with NanoString results (r = 0.90) from fresh frozen tissue as well as NanoString results from FFPE tissue (r = 0.84). Thus, our gene expression classifier may identify triple-negative breast cancer patients with homologous recombination deficiency, suggesting an alternative method to identify individuals who may benefit from treatment with PARP inhibitors or platinum chemotherapy. Novelty/Impact statementWe developed a gene expression-based classifier for homologous recombination deficiency (HRD) in breast cancer patients using WES and RNA-seq data obtained from 129 TNBC samples from a Malaysian hospital-based cohort (MyBrCa). This classifier was able to predict for HRD status at an AUC of 0.94 in the MyBrCa cohort, and was also able to segregate HRD-associated features in TNBCs from TCGA. We also validated the classifier on a NanoString platform with both fresh frozen and FFPE tissue.

cancer biology↗

bioRxiv2021

Preferential allelic expression of PIK3CA mutations is frequent in breast cancer and is prognostically significant

PIK3CA mutations are the most common in breast cancer, particularly in the estrogen receptor positive cohort, but the benefit of PI3K inhibitors has had limited success compared with approaches targeting other less common mutations. We found allelic imbalances in the expression of PIK3CA in normal breast tissue and mapped a germline candidate regulatory variant. An imbalance was also frequently observed in the expression of the missense mutant and wild-type PIK3CA alleles in breast tumors from METABRIC and TCGA projects. Moreover, although 60% of tumors preferentially expressed the mutant allele, 10% did preferentially express the wild-type allele. Mechanistically, we show that these imbalances are more frequently due to regulatory variants in cis than altered copy-number and predict that somatic variants have a more significant role than germline ones. We further found that imbalanced allelic expression between mutant and wild-type alleles due to cis-regulatory variants associated with poor prognosis (p=0.0081). Interestingly, ER+, PR+, and Her2- tumors expressing very low levels of the mutant allele had the poorest prognosis (DSS <7.5yrs for ER+ and PR+ tumors and <5yrs for Her2- tumors). Hence, our work provides compelling evidence to support the clinical utility of PIK3CA allelic expression in breast cancer in identifying this cohort of low mutant allele expressing patients of poorer prognosis, who will unlikely benefit from PI3K inhibitors. Furthermore, our work establishes a new model of differential regulation of critical cancer-promoting genes.

cancer biology↗

bioRxiv2020

Germline APOBEC3B deletion in Asian women increases somatic hypermutation in breast cancer that is associated with Her2 subtype, PIK3CA mutations, immune activation, and increased survival

A 30-kb deletion that eliminates the coding region of APOBEC3B (A3B) is >5 times more common in women of Asian compared to European descent. This polymorphism creates a chimera with the APOBEC3A (A3A) coding region and A3B 3UTR, and is associated with an increased risk for breast cancer in Asian women. Here, we explored the relationship between the A3B deletion polymorphism with tumour characteristics in Asian women. Using whole exome and whole transcriptome sequencing data of 527 breast tumours, we report that germline A3B deletion polymorphism leads to expression of the A3A-B hybrid isoform and increased APOBEC-associated somatic hypermutation. Hypermutated tumours, regardless of A3B germline status, were associated with the Her2 molecular subtype and PIK3CA mutations. Compared to non-hypermutated tumours, hypermutated tumours also had higher neoantigen burden, tumour heterogeneity and immune activation. Taken together, our results suggest that the germline A3B deletion polymorphism, via the A3A-B hybrid isoform, contributes to APOBEC-mutagenesis in a significant proportion of Asian breast cancers. In addition, APOBEC somatic hypermutation, regardless of A3B background, may be an important clinical biomarker for Asian breast cancers. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=181 SRC="FIGDIR/small/135251v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@45b329org.highwire.dtl.DTLVardef@1f5770corg.highwire.dtl.DTLVardef@5ac017org.highwire.dtl.DTLVardef@1f939ad_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2020

Transcriptional profiling reveals a subset of human breast tumors that retain wt TP53 but display mutant p53-associated features

TP53 gene mutations are very common in human cancer. While such mutations abrogate the tumor suppressive activities of the wild type (wt) p53 protein, some of them also endow the mutant protein with oncogenic gain-of-function (GOF), facilitating cancer progression. Yet, p53 may acquire altered functionality even without being mutated; in particular, experiments with cultured cells revealed that wt p53 can be rewired to adopt mutant-like features in response to growth factors or cancer-mimicking genetic manipulations. To assess whether such rewiring also occurs in human tumors, we interrogated gene expression profiles and pathway deregulation patterns in the METABRIC breast cancer (BC) dataset as a function of TP53 gene mutation status. Harnessing the power of machine learning, we optimized a gene expression classifier for ER+Her2- patients that distinguishes tumors carrying TP53 mutations from those retaining wt TP53. Interestingly, a small subset of wt TP53 tumors displayed gene expression and pathway deregulation patterns markedly similar to those of TP53-mutated tumors. Moreover, similar to TP53 mutated tumors, these "pseudomutant" cases displayed a signature for enhanced proliferation and had worse prognosis than typical wt p53 tumors. Notably, these tumors revealed upregulation of genes which, in BC cell lines, were reported to be positively regulated by p53 GOF mutants. Thus, such tumors may benefit from mutant p53-associated activities without having to accrue TP53 mutations.

cancer biology↗

bioRxiv2020

The Molecular Landscape of Asian Breast Cancers Reveals Clinically Relevant Population-Specific Differences

Molecular profiles of breast cancer have contributed to an improved understanding of the disease, enabled development of molecular prognostic signatures to guide treatment decisions and unveiled new or more accurate therapeutic options for breast cancer patients. However, the extent to which differences in genetic, environmental and lifestyle factors influence molecular profiles in different populations remains poorly characterised, as relatively few large-scale molecular studies of breast tumours in non-Caucasian populations have hitherto been reported. Here, we present the molecular profiles of 560 Asian breast tumours and a comparative analysis of breast cancers arising in Asian and Caucasian women. Compared to the breast tumours in predominantly Caucasian women reported in TCGA and METABRIC, we show an increased prevalence of Her2-enriched molecular subtypes and higher prevalence of TP53 somatic mutations in ER+ Asian breast tumours. Using gene expression and immunohistochemistry, we observed elevated immune scores in Asian breast tumours, suggesting potential clinical response to immune checkpoint inhibitors. Whilst Her2-subtype and enriched immune score are associated with improved survival, presence of TP53 somatic mutations is associated with poorer survival in ER+ tumours. Taken together, these population differences unveil new opportunities to improve the understanding of this disease and lay the foundation for precision medicine in different populations.

cancer biology↗

bioRxiv2019

The GATA3 X308_Splice breast cancer mutation is a hormone context-dependent oncogenic driver

As the catalogue of oncogenic driver mutations is expanding, it is becoming clear that alterations in a given gene should not be lumped into one single class, since they might have different functions. The transcription factor GATA3 is a paradigm of this. Here, we address the functions of the most common GATA3 mutation (X308_Splice) which generates a neoprotein that we designate as neoGATA3, associated with good patient prognosis. Based on extensive analyses of molecular and clinical data from approximately 3000 breast cancer patients, supported by mechanistic studies in vitro, we show that neoGATA3 interferes with the transcriptional programs controlled by estrogen and progesterone receptors, without fully abrogating them. This has opposite outputs in the pre- or post-menopausal hormonal context, having pro- or anti-proliferative effects, respectively. NeoGATA3 is an example of a context- and stage-dependent driver mutation. Our data call for functional analyses of putative cancer drivers to guide clinical application.

cancer biology↗

bioRxiv2019

A reference map of the human protein interactome

Global insights into cellular organization and function require comprehensive understanding of interactome networks. Similar to how a reference genome sequence revolutionized human genetics, a reference map of the human interactome network is critical to fully understand genotype-phenotype relationships. Here we present the first human \"all-by-all\" binary reference interactome map, or \"HuRI\". With ~53,000 high-quality protein-protein interactions (PPIs), HuRI is approximately four times larger than the information curated from small-scale studies available in the literature. Integrating HuRI with genome, transcriptome and proteome data enables the study of cellular function within essentially any physiological or pathological cellular context. We demonstrate the use of HuRI in identifying specific subcellular roles of PPIs and protein function modulation via splicing during brain development. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms underlying tissue-specific phenotypes of Mendelian diseases. HuRI thus represents an unprecedented, systematic reference linking genomic variation to phenotypic outcomes.

systems biology↗

bioRxiv2018

Detection of residual disease after neoadjuvant therapy in breast cancer using personalized circulating tumor DNA analysis

Accurate detection of minimal residual disease (MRD) can guide individualized management of early stage cancer patients, but current diagnostic approaches lack adequate sensitivity. Circulating tumor DNA (ctDNA) analysis has shown promise for recurrence monitoring but MRD detection immediately after neoadjuvant therapy or surgical resection has remained challenging. We have developed TARgeted DIgital Sequencing (TARDIS) to simultaneously analyze multiple patient-specific cancer mutations in plasma and improve sensitivity for minute quantities of residual tumor DNA. In 77 reference samples at 0.03%-1% mutant allele fraction (AF), we observed 93.5% sensitivity. Using TARDIS, we analyzed ctDNA in 34 samples from 13 patients with stage II/III breast cancer treated with neoadjuvant therapy. Prior to treatment, we detected ctDNA in 12/12 patients at 0.002%-1.04% AF (0.040% median). After completion of neoadjuvant therapy, we detected ctDNA in 7/8 patients with residual disease observed at surgery and in 1/5 patients with pathological complete response (odds ratio, 18.5, Fishers exact p=0.032). These results demonstrate high accuracy for a personalized blood test to detect residual disease after neoadjuvant therapy. With additional clinical validation, TARDIS could identify patients with molecular complete response after neoadjuvant therapy who may be candidates for nonoperative management.\n\nOne Sentence SummaryA personalized ctDNA test achieves high accuracy for residual disease.

genomics↗

bioRxiv2018

Next Generation-Targeted Amplicon Sequencing (NG-TAS): An optimised protocol and computational pipeline for cost-effective profiling of circulating tumour DNA

Circulating tumour DNA (ctDNA) detection and monitoring has enormous potential clinical utility in oncology. We describe here a fast, flexible and cost-effective method to profile multiple genes simultaneously in low input cell-free DNA (cfDNA): Next Generation-Targeted Amplicon Sequencing (NG-TAS). We designed a panel of 377 amplicons spanning 20 cancer genes and tested the NG-TAS pipeline using cell-free DNA from two hapmap lymphoblastoid cell lines. NG-TAS consistently detected mutations in cfDNA when mutation allele fraction was >1%. We applied NG-TAS to a clinical cohort of metastatic breast cancer patients, demonstrating its potential in monitoring the disease. The computational pipeline is available at: https://github.com/cclab-brca/NGTAS_pipeline.

genomics↗