Systemic immune reaction in axillary lymph nodes adds to tumor infiltrating lymphocytes in triple-negative breast cancer prognostication

The level of stromal tumor-infiltrating lymphocytes (sTILs) in triple negative (TNBC) and HER2-positive breast cancers convey prognostic information. The importance of systemic immunity to local immunity is unknown in breast cancer. We previously demonstrated that histological alterations in axillary lymph nodes (LNs) carry clinical relevance. Here, we capture local immune responses by scoring TILs at the primary tumor and systemic immune responses by recording the formation of secondary follicles, also known as germinal centers, in 2,857 cancer-free and involved axillary LNs on haematoxylin and eosin (H&E) stained sections from a retrospective cohort of 161 LN-positive triple-negative and HER2-positive breast cancer patients. Our data demonstrate that the number of germinal center formations across all cancer-free LNs, similar to high levels of TILs, is associated with a good prognosis in low TILs TNBC. This highlights the importance of assessing both primary and LN immune responses for prognostication and for future breast cancer research

Mouse mammary stem cells express prognostic markers for triple-negative breast cancer

Introduction Triple negative breast cancer (TNBC) is a heterogeneous group of tumours in which chemotherapy, the current mainstay of systemic treatment, is often initially beneficial but with a high risk of relapse and metastasis. There is currently no means of predicting which TNBC will relapse. We tested the hypothesis that the biological properties of normal stem cells are re-activated in tumour metastasis and that, therefore, the activation of normal mammary stem cell-associated gene sets in primary TNBC would be highly prognostic for relapse and metastasis. Methods Mammary basal stem and myoepithelial cells were isolated by flow cytometry and tested in low dose transplant assays. Gene expression microarrays were used to establish expression profiles of the stem and myoepithelial populations; these were compared to each other and to our previously established mammary epithelial gene expression profiles. Stem cell genes were classified by Gene Ontology (GO) analysis and the expression of a subset analysed in the stem cell population at single cell resolution. Activation of stem cell genes was interrogated across different breast cancer cohorts and within specific subtypes and tested for clinical prognostic power. Results A set of 323 genes was identified that was expressed significantly more highly in the purified basal stem cells compared to all other cells of the mammary epithelium. 109 out of 323 genes had been associated with stem cell features in at least one other study in addition to our own, providing further support for their involvement in the biology of this cell type. GO analysis demonstrated an enrichment of these genes for an association with cell migration, cytoskeletal regulation and tissue morphogenesis, consistent with a role in invasion and metastasis. Single cell resolution analysis showed that individual cells co-expressed both epithelial- and mesenchymal-associated genes/proteins. Most strikingly, we demonstrated that strong activity of this stem cell gene set in TNBCs identified those tumours most likely to rapidly progress to metastasis. Conclusions Our findings support the hypothesis that the biological properties of normal stem cells are drivers of metastasis and that these properties can be used to stratify patients with a highly heterogeneous disease such as TNBC

Random forest modelling of high-dimensional mixed-type data for breast cancer classification

Advances in high-throughput technologies encourage the generation of large amounts of multiomics data to investigate complex diseases, including breast cancer. Given that the aetiologies of such diseases extend beyond a single biological entity, and that essential biological information can be carried by all data regardless of data type, integrative analyses are needed to identify clinically relevant patterns. To facilitate such analyses, we present a permutation-based framework for random forest methods which simultaneously allows the unbiased integration of mixed-type data and assessment of relative feature importance. Through simulation studies and machine learning datasets, the performance of the approach was evaluated. The results showed minimal multicollinearity and limited overfitting. To further assess the performance, the permutation-based framework was applied to high-dimensional mixed-type data from two independent breast cancer cohorts. Reproducibility and robustness of our approach was demonstrated by the concordance in relative feature importance between the cohorts, along with consistencies in clustering profiles. One of the identified clusters was shown to be prognostic for clinical outcome after standard-of-care adjuvant chemotherapy and outperformed current intrinsic molecular breast cancer classifications

PAK6 acts downstream of IQGAP3 to promote contractility in triple negative breast cancer cells

Breast cancer is a heterogeneous disease that remains the most common malignancy among women worldwide. During genomic analysis of breast tumours, mRNA levels of IQGAP3 were found to be upregulated in triple negative tumours. IQGAP3 was subsequently found to be expressed across a panel of triple negative breast cancer (TNBC) cell lines. Depleting expression levels of IQGAP3 delivered elongated cells, disrupted cell migration, and inhibited the ability of cells to form specialised invasive adhesion structures, termed invadopodia. The morphological changes induced by IQGAP3 depletion were found to be dependent on RhoA. Indeed, reduced expression of IQGAP3 disrupted RhoA activity and actomyosin contractility. Interestingly, IQGAP3 was also found to interact with p-21 activated kinase 6 (PAK6); a protein already associated with the regulation of cell morphology. Moreover, PAK6 depletion phenocopied IQGAP3 depletion in these cells. Whereas PAK6 overexpression rescued the IQGAP3 depletion phenotype. Our work points to an important PAK6-IQGAP3-RhoA pathway that drives the cellular contractility of breast cancer cells promoting both cell migration and adhesive invasion of these cells. As this phenotype is relevant to the process of metastasis and re-seeding of metastasis, the pharmacological targeting of PAK6 could lead to clinical benefit in TNBC patient

Do Genetic Susceptibility Variants Associate With Disease Severity In Early Active Rheumatoid Arthritis?

Objective.Genetic variants affect both the development and severity of rheumatoid arthritis (RA). Recent studies have expanded the number of RA susceptibility variants. We tested the hypothesis that these associated with disease severity in a clinical trial cohort of patients with early, active RA.Methods.We evaluated 524 patients with RA enrolled in the Combination Anti-Rheumatic Drugs in Early RA (CARDERA) trials. We tested validated susceptibility variants — 69 single-nucleotide polymorphisms (SNP), 15 HLA-DRB1 alleles, and amino acid polymorphisms in 6 HLA molecule positions — for their associations with progression in Larsen scoring, 28-joint Disease Activity Scores, and Health Assessment Questionnaire (HAQ) scores over 2 years using linear mixed-effects and latent growth curve models.Results.HLA variants were associated with joint destruction. The *04:01 SNP (rs660895, p = 0.0003), *04:01 allele (p = 0.0002), and HLA-DRβ1 amino acids histidine at position 13 (p = 0.0005) and valine at position 11 (p = 0.0012) significantly associated with radiological progression. This association was only significant in anticitrullinated protein antibody (ACPA)-positive patients, suggesting that while their effects were not mediated by ACPA, they only predicted joint damage in ACPA-positive RA. Non-HLA variants did not associate with radiograph damage (assessed individually and cumulatively as a weighted genetic risk score). Two SNP — rs11889341 (STAT4, p = 0.0001) and rs653178 (SH2B3-PTPN11, p = 0.0004) — associated with HAQ scores over 6–24 months.Conclusion.HLA susceptibility variants play an important role in determining radiological progression in early, active ACPA-positive RA. Genome-wide and HLA-wide analyses across large populations are required to better characterize the genetic architecture of radiological progression in RA.</jats:sec

Adipose-enriched peri-tumoral stroma, in contrast to myofibroblast-enriched stroma, prognosticates poorer survival in breast cancers

Despite our understanding of the genetic basis of intra-tumoral heterogeneity, the role of stromal heterogeneity arising from an altered tumor microenvironment in affecting tumorigenesis is poorly understood. In particular, extensive study on the peri-tumoral stroma in the morphologically normal tissues surrounding the tumor is lacking. Here, we examine the heterogeneity in tumors and peri-tumoral stroma from 8 ER+/PR+/HER2- invasive breast carcinomas, through multi-region transcriptomic profiling by microarray. We describe the regional heterogeneity observed at the intrinsic molecular subtype, pathway enrichment, and cell type composition levels within each tumor and its peri-tumoral region, up to 7 cm from the tumor margins. Moreover, we identify a pro-inflammatory adipose-enriched peri-tumoral subtype which was significantly associated with poorer overall survival in breast cancer patients, in contrast to an adaptive immune cell- and myofibroblast-enriched subtype. These data together suggest that peri-tumoral heterogeneity may be an important determinant of the evolution and treatment of breast cancers.National Medical Research Council (NMRC)Published versionThis research was supported by the: National Medical Research Council Singapore; NCC Cancer Fund (all to K.S.); and NCC Research Fund (NCCSPG-YR2015-JAN-7) (to K.S. and V.K.M.T.). H.S.H.L. is supported by the NUS Research Scholarship and NUS Medicine Graduate Studies Award. We thank Breast Cancer Now as well as Cancer Research UK [CRUK/07/012, KCL-BCN-Q3]. We thank Breast Cancer Now [KCL-BCN-Q3], the Medical Research Council [MR/X012476/1], as well as the Cancer Research UK City of London Centre Award [CTRQQR-2021/100004] in funding this project