Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer.

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Computational pathology in cancer diagnosis, prognosis, and prediction - present day and prospects.

Computational pathology refers to applying deep learning techniques and algorithms to analyse and interpret histopathology images. Advances in artificial intelligence (AI) have led to an explosion in innovation in computational pathology, ranging from the prospect of automation of routine diagnostic tasks to the discovery of new prognostic and predictive biomarkers from tissue morphology. Despite the promising potential of computational pathology, its integration in clinical settings has been limited by a range of obstacles including operational, technical, regulatory, ethical, financial, and cultural challenges. Here, we focus on the pathologists' perspective of computational pathology: we map its current translational research landscape, evaluate its clinical utility, and address the more common challenges slowing clinical adoption and implementation. We conclude by describing contemporary approaches to drive forward these techniques. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Multiscale deep learning framework captures systemic immune features in lymph nodes predictive of triple negative breast cancer outcome in large-scale studies.

The suggestion that the systemic immune response in lymph nodes (LNs) conveys prognostic value for triple-negative breast cancer (TNBC) patients has not previously been investigated in large cohorts. We used a deep learning (DL) framework to quantify morphological features in haematoxylin and eosin-stained LNs on digitised whole slide images. From 345 breast cancer patients, 5,228 axillary LNs, cancer-free and involved, were assessed. Generalisable multiscale DL frameworks were developed to capture and quantify germinal centres (GCs) and sinuses. Cox regression proportional hazard models tested the association between smuLymphNet-captured GC and sinus quantifications and distant metastasis-free survival (DMFS). smuLymphNet achieved a Dice coefficient of 0.86 and 0.74 for capturing GCs and sinuses, respectively, and was comparable to an interpathologist Dice coefficient of 0.66 (GC) and 0.60 (sinus). smuLymphNet-captured sinuses were increased in LNs harbouring GCs (p < 0.001). smuLymphNet-captured GCs retained clinical relevance in LN-positive TNBC patients whose cancer-free LNs had on average ≥2 GCs, had longer DMFS (hazard ratio [HR] = 0.28, p = 0.02) and extended GCs' prognostic value to LN-negative TNBC patients (HR = 0.14, p = 0.002). Enlarged smuLymphNet-captured sinuses in involved LNs were associated with superior DMFS in LN-positive TNBC patients in a cohort from Guy's Hospital (multivariate HR = 0.39, p = 0.039) and with distant recurrence-free survival in 95 LN-positive TNBC patients of the Dutch-N4plus trial (HR = 0.44, p = 0.024). Heuristic scoring of subcapsular sinuses in LNs of LN-positive Tianjin TNBC patients (n = 85) cross-validated the association of enlarged sinuses with shorter DMFS (involved LNs: HR = 0.33, p = 0.029 and cancer-free LNs: HR = 0.21 p = 0.01). Morphological LN features reflective of cancer-associated responses are robustly quantifiable by smuLymphNet. Our findings further strengthen the value of assessment of LN properties beyond the detection of metastatic deposits for prognostication of TNBC patients. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Spatial analyses of immune cell infiltration in cancer: current methods and future directions: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer.

Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.

Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Inducible localized delivery of an anti-PD-1 scFv enhances anti-tumor activity of ROR1 CAR-T cells in TNBC.

BACKGROUND: Chimeric antigen receptor (CAR)-T cells can induce powerful immune responses in patients with hematological malignancies but have had limited success against solid tumors. This is in part due to the immunosuppressive tumor microenvironment (TME) which limits the activity of tumor-infiltrating lymphocytes (TILs) including CAR-T cells. We have developed a next-generation armored CAR (F i-CAR) targeting receptor tyrosine kinase-like orphan receptor 1 (ROR1), which is expressed at high levels in a range of aggressive tumors including poorly prognostic triple-negative breast cancer (TNBC). The F i-CAR-T is designed to release an anti-PD-1 checkpoint inhibitor upon CAR-T cell activation within the TME, facilitating activation of CAR-T cells and TILs while limiting toxicity. METHODS: To bolster potency, we developed a F i-CAR construct capable of IL-2-mediated, NFAT-induced secretion of anti-PD-1 single-chain variable fragments (scFv) within the tumor microenvironment, following ROR1-mediated activation. Cytotoxic responses against TNBC cell lines as well as levels and binding functionality of released payload were analyzed in vitro by ELISA and flow cytometry. In vivo assessment of potency of F i-CAR-T cells was performed in a TNBC NSG mouse model. RESULTS: F i-CAR-T cells released measurable levels of anti-PD-1 payload with 5 h of binding to ROR1 on tumor and enhanced the cytotoxic effects at challenging 1:10 E:T ratios. Treatment of established PDL1 + TNBC xenograft model with F i-CAR-T cells resulted in significant abrogation in tumor growth and improved survival of mice (71 days), compared to non-armored CAR cells targeting ROR1 (F CAR-T) alone (49 days) or in combination with systemically administered anti-PD-1 antibody (57 days). Crucially, a threefold increase in tumor-infiltrating T cells was observed with F i-CAR-T cells and was associated with increased expression of genes related to cytotoxicity, migration and proliferation. CONCLUSIONS: Our next-generation of ROR1-targeting inducible armored CAR platform enables the release of an immune stimulating payload only in the presence of target tumor cells, enhancing the therapeutic activity of the CAR-T cells. This technology provided a significant survival advantage in TNBC xenograft models. This coupled with its potential safety attributes merits further clinical evaluation of this approach in TNBC patients.

Pan-cancer transcriptomic analysis dissects immune and proliferative functions of APOBEC3 cytidine deaminases.

APOBEC3 cytidine deaminases are largely known for their innate immune protection from viral infections. Recently, members of the family have been associated with a distinct mutational activity in some cancer types. We report a pan-tissue, pan-cancer analysis of RNA-seq data specific to the APOBEC3 genes in 8,951 tumours, 786 cancer cell lines and 6,119 normal tissues. By deconvolution of levels of different cell types in tumour admixtures, we demonstrate that APOBEC3B (A3B), the primary candidate as a cancer mutagen, shows little association with immune cell types compared to its paralogues. We present a pipeline called RESPECTEx (REconstituting SPecific Cell-Type Expression) and use it to deconvolute cell-type specific expression levels in a given cohort of tumour samples. We functionally annotate APOBEC3 co-expressing genes, and create an interactive visualization tool which 'barcodes' the functional enrichment (http://fraternalilab.kcl.ac.uk/apobec-barcodes/). These analyses reveal that A3B expression correlates with cell cycle and DNA repair genes, whereas the other APOBEC3 members display specificity for immune processes and immune cell populations. We offer molecular insights into the functions of individual APOBEC3 proteins in antiviral and proliferative contexts, and demonstrate the diversification this family of enzymes displays at the transcriptomic level, despite their high similarity in protein sequences and structures.

An RNAi screen of Rho signalling networks identifies RhoH as a regulator of Rac1 in prostate cancer cell migration.

BACKGROUND: Cell migration is essential for development and tissue repair, but it also contributes to disease. Rho GTPases regulate cell migration, but a comprehensive analysis of how each Rho signalling component affects migration has not been carried out. RESULTS: Through an RNA interference screen, and using a prostate cancer cell line, we find that approximately 25% of Rho network components alter migration. Some genes enhance migration while others decrease basal and/or hepatocyte growth factor-stimulated migration. Surprisingly, we identify RhoH as a screen hit. RhoH expression is normally restricted to haematopoietic cells, but we find it is expressed in multiple epithelial cancer cell lines. High RhoH expression in samples from prostate cancer patients correlates with earlier relapse. RhoH depletion reduces cell speed and persistence and decreases migratory polarity. Rac1 activity normally localizes to the front of migrating cells at areas of dynamic membrane movement, but in RhoH-depleted cells active Rac1 is localised around the whole cell periphery and associated with membrane regions that are not extending or retracting. RhoH interacts with Rac1 and with several p21-activated kinases (PAKs), which are Rac effectors. Similar to RhoH depletion, PAK2 depletion increases cell spread area and reduces cell migration. In addition, RhoH depletion reduces lamellipodium extension induced by PAK2 overexpression. CONCLUSIONS: We describe a novel role for RhoH in prostate cancer cell migration. We propose that RhoH promotes cell migration by coupling Rac1 activity and PAK2 to membrane protrusion. Our results also suggest that RhoH expression levels correlate with prostate cancer progression.

Molecular patterns of cancer colonisation in lymph nodes of breast cancer patients.

Lymph node (LN) metastasis is an important prognostic parameter in breast carcinoma, a crucial site for tumour-immune cell interaction and a gateway for further dissemination of tumour cells to other metastatic sites. To gain insight into the underlying molecular changes from the pre-metastatic, via initial colonisation to the fully involved LN, we reviewed transcriptional research along the evolving microenvironment of LNs in human breast cancers patients. Gene expression studies were compiled and subjected to pathway-based analyses, with an emphasis on immune cell-related genes. Of 366 studies, 14 performed genome-wide gene expression comparisons and were divided into six clinical-biological scenarios capturing different stages of the metastatic pathway in the LN, as follows: metastatically involved LNs are compared to their patient-matched primary breast carcinomas (scenario 1) or the normal breast tissue (scenario 2). In scenario 3, uninvolved LNs were compared between LN-positive patients and LN-negative patients. Scenario 4 homed in on the residual uninvolved portion of involved LNs and compared it to the patient-matched uninvolved LNs. Scenario 5 contrasted uninvolved and involved LNs, whilst in scenario 6 involved (sentinel) LNs were assessed between patients with other either positive or negative LNs (non-sentinel).Gene lists from these chronological steps of LN metastasis indicated that gene patterns reflecting deficiencies in dendritic cells and hyper-proliferation of B cells parallel to tumour promoting pathways, including cell adhesion, extracellular matrix remodelling, cell motility and DNA repair, play key roles in the changing microenvironment of a pro-metastatic to a metastatically involved LN. Similarities between uninvolved LNs and the residual uninvolved portion of involved LNs hinted that LN alterations expose systemic tumour-related immune responses in breast cancer patients. Despite the diverse settings, gene expression patterns at different stages of metastatic colonisation in LNs were recognised and may provide potential avenues for clinical interventions to counteract disease progression for breast cancer patients.

Identification of a gene regulatory network associated with prion replication.

Prions consist of aggregates of abnormal conformers of the cellular prion protein (PrP(C)). They propagate by recruiting host-encoded PrP(C) although the critical interacting proteins and the reasons for the differences in susceptibility of distinct cell lines and populations are unknown. We derived a lineage of cell lines with markedly differing susceptibilities, unexplained by PrP(C) expression differences, to identify such factors. Transcriptome analysis of prion-resistant revertants, isolated from highly susceptible cells, revealed a gene expression signature associated with susceptibility and modulated by differentiation. Several of these genes encode proteins with a role in extracellular matrix (ECM) remodelling, a compartment in which disease-related PrP is deposited. Silencing nine of these genes significantly increased susceptibility. Silencing of Papss2 led to undersulphated heparan sulphate and increased PrP(C) deposition at the ECM, concomitantly with increased prion propagation. Moreover, inhibition of fibronectin 1 binding to integrin α8 by RGD peptide inhibited metalloproteinases (MMP)-2/9 whilst increasing prion propagation. In summary, we have identified a gene regulatory network associated with prion propagation at the ECM and governed by the cellular differentiation state.

Functional and prognostic significance of the genomic amplification of frizzled 6 (FZD6) in breast cancer.

Frizzled receptors mediate Wnt ligand signalling, which is crucially involved in regulating tissue development and differentiation, and is often deregulated in cancer. In this study, we found that the gene encoding the Wnt receptor frizzled 6 (FZD6) is frequently amplified in breast cancer, with an increased incidence in the triple-negative breast cancer (TNBC) subtype. Ablation of FZD6 expression in mammary cancer cell lines: (1) inhibited motility and invasion; (2) induced a more symmetrical shape of organoid three-dimensional cultures; and (3) inhibited bone and liver metastasis in vivo. Mechanistically, FZD6 signalling is required for the assembly of the fibronectin matrix, interfering with the organization of the actin cytoskeleton. Ectopic delivery of fibronectin in FZD6-depleted, triple-negative MDA-MB-231 cells rearranged the actin cytoskeleton and restored epidermal growth factor-mediated invasion. In patients with localized, lymph node-negative (early) breast cancer, positivity of tumour cells for FZD6 protein identified patients with reduced distant relapse-free survival. Multivariate analysis indicated an independent prognostic significance of FZD6 expression in TNBC tumours, predicting distant, but not local, relapse. We conclude that the FZD6-fibronectin actin axis identified in our study could be exploited for drug development in highly metastatic forms of breast cancer, such as TNBC. © 2016 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Gene expression modules in primary breast cancers as risk factors for organotropic patterns of first metastatic spread: a case control study.

BACKGROUND: Metastases from primary breast cancers can involve single or multiple organs at metastatic disease diagnosis. Molecular risk factors for particular patterns of metastastic spread in a clinical population are limited. METHODS: A case-control design including 1357 primary breast cancers was used to study three distinct clinical patterns of metastasis, which occur within the first six months of metastatic disease: bone and visceral metasynchronous spread, bone-only, and visceral-only metastasis. Whole-genome expression profiles were obtained using whole genome (WG)-DASL assays from formalin-fixed paraffin-embedded (FFPE) samples. A systematic protocol was developed for handling FFPE samples together with stringent data quality controls to identify robust expression profiling data. A panel of published and novel gene sets were tested for association with these specific patterns of metastatic spread and odds ratios (ORs) were calculated. RESULTS: Metasynchronous metastasis to bone and viscera was found in all intrinsic breast cancer subtypes, while immunohistochemically (IHC)-defined receptor status and specific IntClust subgroups were risk factors for visceral-only or bone-only first metastases. Among gene modules, those related to proliferation increased the risk of metasynchronous metastasis (OR (95% CI) = 2.3 (1.1-4.8)) and visceral-only first metastasis (OR (95% CI) = 2.5 (1.2-5.1)) but not bone-only metastasis (OR (95% CI) = 0.97 (0.56-1.7)). A 21-gene module (BV) was identified in estrogen-receptor-positive breast cancers with metasynchronous metastasis to bone and viscera (area under the curve = 0.77), and its expression increased the risk of bone and visceral metasynchronous spread in this population. BV was further orthogonally validated with NanoString nCounter in primary breast cancers, and was reproducible in their matched lymph nodes metastases and an external cohort. CONCLUSION: This case-control study of WG-DASL global expression profiles from FFPE tumour samples, after careful quality control and RNA selection, revealed that gene modules in the primary tumour have differing risks for clinical patterns of metasynchronous first metastases. Moreover, a novel gene module was identified as a putative risk factor for metasynchronous bone and visceral first metastatic spread, with potential implications for disease monitoring and treatment planning.

PIK3CA mutations are common in lobular carcinoma in situ, but are not a biomarker of progression.

BACKGROUND: Lobular carcinoma in situ (LCIS) is a non-invasive breast lesion that is typically found incidentally on biopsy and is often associated with invasive lobular carcinoma (ILC). LCIS is considered by some to be a risk factor for future breast cancer rather than a true precursor lesion. The aim of this study was to identify genetic changes that could be used as biomarkers of progression of LCIS to invasive disease using cases of pure LCIS and comparing their genetic profiles to LCIS which presented contemporaneously with associated ILC, on the hypothesis that the latter represents LCIS that has already progressed. METHODS: Somatic copy number aberrations (SCNAs) were assessed by SNP array in three subgroups: pure LCIS, LCIS associated with ILC and the paired ILC. In addition exome sequencing was performed on seven fresh frozen samples of LCIS associated with ILC, to identify recurrent somatic mutations. RESULTS: The copy number profiles of pure LCIS and LCIS associated with ILC were almost identical. However, four SCNAs were more frequent in ILC than LCIS associated with ILC, including gain/amplification of CCND1. CCND1 protein over-expression assessed by immunohistochemical analysis in a second set of samples from 32 patients with pure LCIS and long-term follow up, was associated with invasive recurrence (P = 0.02, Fisher's exact test). Exome sequencing revealed that PIK3CA mutations were as frequent as CDH1 mutations in LCIS, but were not a useful biomarker of LCIS progression as they were as frequent in pure LCIS as in LCIS associated with ILC. We also observed heterogeneity of PIK3CA mutations and evidence of sub-clonal populations in LCIS irrespective of whether they were associated with ILC. CONCLUSIONS: Our data shows that pure LCIS and LCIS co-existing with ILC have very similar SCNA profiles, supporting the hypothesis that LCIS is a true precursor lesion. We have provided evidence that over-expression of CCND1 may identify a subgroup of patients with pure LCIS who are more likely to develop invasive disease, in contrast to PIK3CA mutations, which occur too early in lobular tumorigenesis to be informative.

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. A total of 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.

Big Data: the challenge for small research groups in the era of cancer genomics.

In the past decade, cancer research has seen an increasing trend towards high-throughput techniques and translational approaches. The increasing availability of assays that utilise smaller quantities of source material and produce higher volumes of data output have resulted in the necessity for data storage solutions beyond those previously used. Multifactorial data, both large in sample size and heterogeneous in context, needs to be integrated in a standardised, cost-effective and secure manner. This requires technical solutions and administrative support not normally financially accounted for in small- to moderate-sized research groups. In this review, we highlight the Big Data challenges faced by translational research groups in the precision medicine era; an era in which the genomes of over 75,000 patients will be sequenced by the National Health Service over the next 3 years to advance healthcare. In particular, we have looked at three main themes of data management in relation to cancer research, namely (1) cancer ontology management, (2) IT infrastructures that have been developed to support data management and (3) the unique ethical challenges introduced by utilising Big Data in research.

Selection and evolution in the genomic landscape of copy number alterations in ductal carcinoma in situ (DCIS) and its progression to invasive carcinoma of ductal/no special type: a meta-analysis.

Ductal carcinoma in situ (DCIS) is a pre-invasive malignancy detected with an increasing frequency through screening mammography. One of the primary aims of therapy is to prevent local recurrence, as in situ or as invasive carcinoma, the latter arising in half of the recurrent cases. Reliable biomarkers predictive of its association with recurrence, particularly as invasive disease, are however lacking. In this study, we perform a meta-analysis of 26 studies which report somatic copy number aberrations (SCNAs) in 288 cases of 'pure' DCIS and 328 of DCIS associated with invasive carcinoma, along with additional unmatched cases of 145 invasive carcinoma of ductal/no special type (IDC) and 50 of atypical ductal hyperplasia (ADH). SCNA frequencies across the genome were calculated at cytoband resolution (UCSC genome build 19) to maximally utilize the available information in published literature. Fisher's exact test was used to identify significant differences in the gain-loss distribution in each cytoband in different group comparisons. We found synchronous DCIS to be at a more advanced stage of genetic aberrations than pure DCIS and was very similar to IDC. Differences in gains and losses in each disease process (i.e. invasive or in situ) at each cytoband were used to infer evidence of selection and conservation for each cytoband and to define an evolutionary conservation scale (ECS) as a tool to identify and distinguish driver SCNA from the passenger SCNA. Using ECS, we have identified aberrations that show evidence of selection from the early stages of neoplasia (i.e. in ADH and pure DCIS) and persist in IDC; we postulate these to be driver aberrations and that their presence may predict progression to invasive disease.

Digital imaging in the immunohistochemical evaluation of the proliferation markers Ki67, MCM2 and Geminin, in early breast cancer, and their putative prognostic value.

BACKGROUND: Immunohistochemical assessment of proliferation may provide additional prognostic information in early breast cancer. However, due to a lack of methodological standards proliferation markers are still not routinely used for determining therapy. Even for Ki67, one of the most widely-studied markers, disagreements over the optimal cutoff exist. Improvements in digital microscopy may provide new avenues to standardise and make data more reproducible. METHODS: We studied the immunohistochemical expression of three markers of proliferation: Ki67, Mini-Chromosome Maintenance protein 2 and Geminin, by conventional light microscope and digital imaging on triplicate TMAs from 309 consecutive cases of primary breast cancers. Differences between the average and the maximum percentage reactivity in tumour cell nuclei from the three TMA cores were investigated to assess the validity of the approach. Time-dependent Receiver Operating Characteristic curves were utilized to obtain optimal expression level cut-offs, which were then correlated with clinico-pathological features and survival. RESULTS: High concordance between conventional and digital scores was observed for all 3 markers (Ki67: rs = 0.87, P < 0.001; MCM2: rs = 0.94, P < 0.001; and Geminin: rs = 0.86, P < 0.001; Spearman's rank). There was no significant difference according to the number of TMA cores included for either Ki67 or MCM2; analysis of two or three cores produced comparable results. Higher levels of all three proliferation markers were significantly associated with higher grade (P < 0.001) and ER-negativity (P < 0.001). Optimal prognostic cut-offs for percentage expression in the tumour were 8 %, 12 and 2.33 % for Ki67, MCM2 and Geminin respectively. All 3 proliferation marker cutoffs were predictive of 15-year breast cancer-specific survival in univariable Cox regression analyses. In multivariable analysis only lymph node status (HR = 3.9, 95 % CI = 1.79-8.5, P = 0.0006) and histological grade (HR = 1.84, 95 % CI = 1-3.38, P = 0.05) remained significantly prognostic. CONCLUSIONS: Here we show that. MCM2 is a more sensitive marker of proliferation than Ki67 and should be examined in future studies, especially in the lymph node-negative, hormone receptor-positive subgroup. Further, digital microscopy can be used effectively as a high-throughput method to evaluate immunohistochemical expression.

Genomic scars as biomarkers of homologous recombination deficiency and drug response in breast and ovarian cancers.

Poly (ADP-ribose) polymerase (PARP) inhibitors and platinum-based chemotherapies have been found to be particularly effective in tumors that harbor deleterious germline or somatic mutations in the BRCA1 or BRCA2 genes, the products of which contribute to the conservative homologous recombination repair of DNA double-strand breaks. Nonetheless, several setbacks in clinical trial settings have highlighted some of the issues surrounding the investigation of PARP inhibitors, especially the identification of patients who stand to benefit from such drugs. One potential approach to finding this patient subpopulation is to examine the tumor DNA for evidence of a homologous recombination defect. However, although the genomes of many breast and ovarian cancers are replete with aberrations, the presence of numerous factors able to shape the genomic landscape means that only some of the observed DNA abnormalities are the outcome of a cancer cell's inability to faithfully repair DNA double-strand breaks. Consequently, recently developed methods for comprehensively capturing the diverse ways in which homologous recombination deficiencies may arise beyond BRCA1/2 mutation have used DNA microarray and sequencing data to account for potentially confounding features in the genome. Scores capturing telomeric allelic imbalance, loss of heterozygosity (LOH) and large scale transition score, as well as the total number of coding mutations are measures that summarize the total burden of certain forms of genomic abnormality. By contrast, other studies have comprehensively catalogued different types of mutational pattern and their relative contributions to a given tumor sample. Although at least one study to explore the use of the LOH scar in a prospective clinical trial of a PARP inhibitor in ovarian cancer is under way, limitations that result in a relatively low positive predictive value for these biomarkers remain. Tumors whose genome has undergone one or more events that restore high-fidelity homologous recombination are likely to be misclassified as double-strand break repair-deficient and thereby sensitive to PARP inhibitors and DNA damaging chemotherapies as a result of prior repair deficiency and its genomic scarring. Therefore, we propose that integration of a genomic scar-based biomarker with a marker of resistance in a high genomic scarring burden context may improve the performance of any companion diagnostic for PARP inhibitors.

Natural History of Germline BRCA1 Mutated and BRCA Wild-type Triple-negative Breast Cancer.

We report a deep next-generation sequencing analysis of 13 sequentially obtained tumor samples, eight sequentially obtained circulating tumor DNA (ctDNA) samples and three germline DNA samples over the life history of 3 patients with triple-negative breast cancer (TNBC), 2 of whom had germline pathogenic BRCA1 mutation, to unravel tumor evolution. Tumor tissue from all timepoints and germline DNA was subjected to whole-exome sequencing (WES), custom amplicon deep sequencing (30,000X) of a WES-derived somatic mutation panel, and SNP arrays for copy-number variation (CNV), while whole transcriptome sequencing (RNA-seq) was performed only on somatic tumor.There was enrichment of homologous recombination deficiency signature in all tumors and widespread CNV, which remained largely stable over time. Somatic tumor mutation numbers varied between patients and within each patient (range: 70-216, one outlier). There was minimal mutational overlap between patients with TP53 being the sole commonly mutated gene, but there was substantial overlap in sequential samples in each patient. Each patient's tumor contained a founding ("stem") clone at diagnosis, which persisted over time, from which all other clones ("subclone") were derived ("branching evolution"), which contained mutations in well-characterized cancer-related genes like PDGFRB, ARID2, TP53 (Patient_02), TP53, BRAF, BRIP1, CSF3R (Patient_04), and TP53, APC, EZH2 (Patient_07). Including stem and subclones, tumors from all patients were polyclonal at diagnosis and during disease progression. ctDNA recapitulated most tissue-derived stem clonal and subclonal mutations while detecting some additional subclonal mutations. RNA-seq revealed a stable basal-like pattern, with most highly expressed variants belonging to stem clone. SIGNIFICANCE: In germline BRCA1 mutated and BRCA wild-type patients, TNBC shows a branching evolutionary pattern of mutations with a single founding clone, are polyclonal throughout their disease course, and have widespread copy-number aberrations. This evolutionary pattern may be associated with treatment resistance or sensitivity and could be therapeutically exploited.