Abstract: This paper discusses the influence of process parameters on the degradation and the mechanical properties of laser-sintered polylactide (PLA) microspheres obtained using the novel dual beam laser sintering method (DBLS). DBLS is a technique developed by our team that is a modification of standard polymer laser sintering (pLS), with the potential to reduce polymer degradation during the process. The PLA microspheres were produced using the standard emulsion-solvent evaporation method. The laser sintering process was carried out in a wide range of process parameters to obtain samples with various degrees of sintering. Next a number of tests were conducted to assess the physicochemical properties of these samples, including visualization techniques (SEM, digital microscopy and photography), gel permeation chromatogrphy (GPC), differential scanning calorimetry (DSC), Fourier transform infrared spectroscopy (FTIR), dynamic mechanical thermal analysis (DMTA) and static compression tests. The work shows that for different sets of process parameters, it is possible to obtain a product with similar mechanical properties, but at the same time with a completely different degree of polymer degradation. Hence, the hypothesis that when assessing the sinter quality one should take into account not only the mechanical properties of the detail, but also the degree of polymer degradation, which is of great importance, for example, in biomedical applications. It has also been shown that the DBLS method has a potential to reduce the degree of degradation of the sintered polymers and the post-process material outside the sintering zone.

Abstract: 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.

Abstract: Aristolochic acid (AA) has, in the last decade, become widely promoted as the cause of the Balkan endemic nephropathy and associated renal or urothelial tumours, although without substantial focal evidence of the quantitative dietary exposure via bread in specific households in hyperendemic villages. Occasional ethnobotanical use of Aristolochia clematitis might be a source of AA, and Pliocene lignite contamination of well-water is also a putative health risk factor. The aim of this study was two-fold: to verify if extracts of A. clematitis and Pliocene, or AA by itself, could induce the development of renal or urothelial tumours, and to test the utility of the ribosomal protein p-S6 to identify preneoplastic transformation. Rats were given extracts of A. clematitis in drinking water or AA I, by gavage.  After seven months, renal morphology was studied using conventional haematoxylin and eosin and immunohistochemistry for ribosomal p-S6 protein.  Plant extracts (cumulative AA approximately 1.8 g/kg b.w.) were tolerated and caused no gross pathology or renal histopathological change, with only faint diffuse p-S6 protein (except in the papilla) as in controls. Cumulative AA I (150 mg/kg b.w. given over 3 days) was also tolerated for seven months by all recipients, without gross pathology or kidney tumours. However, p-S6 protein over-expression was consistent particularly within the renal papilla. In one case given AA I, intense p-S6 protein staining of a proximal tubule fragment crucially matched the pre-neoplastic histology in an adjacent kidney section.  We briefly discuss these findings, which compound uncertainty concerning the cause of the renal or upper urinary tract tumours of the Balkan endemic nephropathy.

Abstract: Systemic immune responses in lymph nodes (LN) convey significant prognostic value for breast cancer patients, which can inform disease progression and optimal treatment management. However, have, so far, not been assessed in large patient cohorts. We have previously shown that morphological alterations in axillary LNs, namely the formation of germinal centres (GCs) in cancer-free LNs, add prognostic value to tumour infiltrating lymphocytes (TILs) in triple-negative breast cancer patients (TNBC) for the development of distant metastasis. Extending manual assessment of LNs beyond the detection of cancer requires the integration of robust deep learning pipelines into the digital pathology workflow. Here, we propose a supervised multiscale deep learning framework named smuLymphNet to capture and quantify GCs and sinuses within LNs from digitised Haematoxylin and Eosin-stained (H & E) whole slide images (WSIs) and show good concordance compared with an inter-pathologist Dice coefficient of manual annotations from four pathologists. The smuLymphNet framework consists of (i) a detection algorithm to determine the boundaries of each LN section on the WSI, using an Otsu-based thresholding method and contouring algorithm; (ii) a supervised multiscale deep learning module for the segmentation of GCs and sinuses; and (iii) quantification of the number, size, and shape of the predicted features. We applied smuLymphNet to a total of 1,800 H & E-stained WSI of & gt;4,000 cancer-free and involved LNs from a retrospectively collected breast cancer cohort collected at Guy’s Hospital (London, UK) from 177 patients (122 N+) enriched for the triple-negative phenotype. A subset of 114 WSI and five breast cancer LN WSIs from each Barts Hospital (London, UK) and Tianjin University Hospital (Tianjin, China) were used to train and evaluate the supervised deep learning module. For training Fully Convolutional Networks (FCNs), WSIs manually annotated for both GCs and sinuses formed a ground-truth set and three FCNs were implemented: (i) a standard U-Net architecture; (ii) a U-Net model with an attention gate mechanism; and (iii) a multiscale-U-Net network (MS U-Net) that encodes, in parallel, a feature representation of the image at multiple resolutions. The MS U-Net achieved the best performance with an average dice score of 0.86 for GCs and 0.74 for sinuses. In comparison, the average dice score amongst four pathologists assessing 24 LN WSI for GCs and sinuses was 0.67 and 0.61, respectively, demonstrating the robustness of the smuLymphNet framework. To establish associations between morphometric immune features and patients’ outcomes, we assessed smuLymphNet captured GCs and sinuses from 686 WSIs from 96 TNBC patients with extensive longitudinal outcome data. We found significant morphological differences in involved and cancer-free LNs between N0 and N+ patients, with the latter displaying larger GCs with more irregular shapes, especially in their involved LNs. Moreover, in alignment with our previously published studies, our multiscale smuLymphNet framework recapitulated and extended the prognostic value of the assessment of GC formation in TNBC N0 patients. We further revealed, for the first time, the prognostic significance of the intranodal lymphatic sinuses when measured in their totality in involved LNs, and the association of alterations in subcapsular sinus areas with superior distant metastasis-free survival in cancer-free and involved LNs in TNBC N+ patients. In summary, smuLymphNet presents a robust multiscale deep learning framework to automatically detect, localise and quantify histopathological immune features in WSI of LNs. By applying smuLymphNet to LNs of TNBC patients from clinical trials, and thereby further evaluating its clinical utility, smuLymphNet could be implemented into the diagnostic digital pathology workflow and, as such, aid in informing on a patient’s disease trajectory. Citation Format: Gregory Verghese, Mengyuan Li, Fangfang Liu, Amit Lohan, Nikhil Cherian, Patrycja Gazinska, Aekta Shah, Aasiyah Oozeer, Cheryl Gillett, Elena Alberts, Thomas Hardiman, Roberto Salgado, Samantha Jones, Louise Jones, Selvam Thavaraj, Sarah E. Pinder, Swapni Rane, Amit Sethi, Anita Grigoriadis. Multiscale Deep Learning framework to capture systemic immune features in lymph nodes predictive of triple negative breast cancer outcome [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-01-01.

Abstract: Background: Heterozygous hotspot mutations in the RNA splicing factor SF3B1, occur in 3% of unselected breast cancers and are associated with oestrogen receptor (ER+) breast cancer (BC) where they are enriched in metastatic disease and are associated with a poor clinical outcome. SF3B1 mutations drive distinct signatures of alternative splicing through cryptic 3’ splice site selection leading to global transcriptomic and proteomic changes. The functional consequences of the mis-splicing events and resultant genetic vulnerabilities are poorly understood and precision medicine approaches that exploit these characteristics are not clinically available (Table 1). Methods: To understand the role of SF3B1 mutations in ER+ BC, we generated a series of SF3B1 mutant (SF3B1MUT) isogenic cell lines which were characterised using RNA-sequencing and high content mass-spectrometry proteomic profiling. SF3B1 interactome analysis was also performed using immunoprecipitation of SF3B1 followed by mass-spectrometry. The molecular consequences of aberrant splicing were investigated using a targeted screening approach of 280 genes predicted to be alternatively spliced in SF3B1MUT BC, while high-throughput drug screens were used to identify novel therapeutic options for patients with SF3B1MUT breast cancer using isogenic cells. Hits were validated in vitro and in vivo using cell line and patient derived xenografts. Results: Transcriptomic and proteomic profiling of SF3B1MUT cells identified global alternative 3’ splice site selection and subsequent proteomic changes induced by the mutations. Investigation of the SF3B1K700E interactome identified an enrichment of SF3B1K700E binding with ER, aberrant splicing of ER target genes, global rewiring of ER chromatin binding and resistance to endocrine therapy. Silencing of the aberrantly spliced candidate genes PPIH, TRIM37, HIGD1A, BRD9, and PHKG2 significantly enhanced the growth of the SF3B1 mutant cells, suggestive of a dose dependent tumour suppressive effect. Through synthetic-lethal drug screens we found that SF3B1MUT cells are selectively sensitive to PARP inhibitors. SF3B1MUT cells display a defective response to PARPi induced replication stress. Mechanistically, this occurs via defective ATR signalling in SF3B1MUT cells, which upon PARPi exposure leads to increased replication origin firing and loss of pChk1 (S317) induction. The resultant replication stress leads to failure to resolve DNA replication intermediates via the endonuclease MUS81 and cell cycle stalling at the G2/M checkpoint. These defects can be further targeted by ATM, CDK7 or FACT inhibition, when used in combination with PARPi treatment. This SF3B1MUT selective PARPi sensitivity is preserved across multiple cell lines and patient derived tumour models. In vivo, PARPi produce profound anti-tumour effects in multiple SF3B1MUT cancer models and eliminate distant metastases. Conclusions: Our integrative analysis reveals mechanistic insight into the role of SF3B1 mutations in endocrine therapy response in ER+ breast cancers, where altered SF3B1 induces ER-transcriptional re-programming. We further identified a robust synthetic-lethal relationship of mutant SF3B1 with PARP inhibition that is caused by a defective response to PARPi induced replication stress. Furthermore, we identified several potential selective combination strategies together with PARPi that are selective for SF3B1MUT cells. Together, these data provide the pre-clinical and mechanistic rationale for assessing already-approved PARPi in a biomarker-defined subset of advanced ER+ BC. Table 1. Identified potential therapies for SF3B1 mutant cancers from this study and the literature Citation Format: Phil Bland, Harry Saville, Abigail Read, Patty Wai, Gareth Muirhead, Lucinda Curnow, Jadwiga Nieminuszczy, Nivedita Ravindran, Marie John, Somaieh Hedayat, Holly Barker, James Wright, Lu Yu, Ioanna Mavrommati, Barrie Peck, Mark Allen, Patrycja Gazinska, Helen Pemberton, Aditi Gulati, Sarah Nash, Farzana Noor, Naomi Guppy, Ioannis Roxanis, Samantha Barlow, Helen Kalirai, Sarah Coupland, Ronan Broderick, Samar Alsafadi, Alexandre Houy, Marc-Henri Stern, Stephen Pettit, Jyoti Choudhary, Syed Haider, Wojciech Niedzwiedz, Christopher Lord, Rachael Natrajan. Mutations in the RNA Splicing Factor SF3B1 drive endocrine therapy resistance and confer a targetable replication stress response defect through PARP inhibition. [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-10-05.

Abstract: Purpose: To assess the frequency and prognostic relevance of germinal centres (GC) in cancer-free axillary lymph nodes (ALNs), in relation to stromal tumour-infiltrating lymphocytes (sTILs) and the presence of tertiary lymphoid structures (TLS) in the primary carcinoma, in LN-positive Hormone Receptor (HR)-negative invasive breast cancer patients. Patients and methods: A cohort of 161 patients with HR-negative invasive breast cancer of no special type (NST) and LN-positive status treated between 2005-10 at Tianjin Medical University (China) was identified. sTILs and TLS at the primary tumour site and GC in 2,841 involved and cancer-free ALNs were evaluated on H & E stained sections. Markers were tested for prognostic value for invasive Disease-Free Survival (iDFS), distant Disease-Free Survival (dDFS) and Overall Survival (OS), using Cox regression models adjusted for clinico-pathological factors. Results: Among the 161 HR-negative breast cancers, 47% (n=75) had & gt;=20% sTILs and 24% (n=38) peritumoural TLS. 75% (121/161) and 76% (122/161), respectively, displayed GCs in their cancer-free and involved ALNs. Significantly higher numbers of GCs were seen in both cancer-free and involved ALNs when the primary tumours showed & gt;=20% sTILs. The presence of TLS was significantly associated with increased GC numbers in involved but to a lesser extend in cancer-free ALNs (Kruskal-Wallis rank sum test, p & lt;0.001 and P_value=0.07, respectively). As expected, increased sTILs and presence of TLS were associated with improved outcome for all endpoints. Using an iterative process to determine an optimal cut off point by a minimal P value approach, a non-monotonic relationship between the frequency of GC in cancer-free ALNs and all endpoints was observed. Patients with & gt;2 GC but less than the top 5% (= 62 GC) in cancer-free ALNs showed improved iDFS, dDFS and OS, whilst patients with & lt;=2 GC or & gt;62 GC across all assessed cancer-free ALNs had poorer iDFS, dDFS and OS (see Table). In the multivariate models, the frequency of GC in cancer-free ALNs added independent prognostic information for all endpoints across all patients. In patients with & gt;=20% sTILS, cancer-free ALNs within the top 5% for GC remained associated with a worse dDFS and iDFS (see Table). Cancer-free ALNs with & lt;=2 GC in total identified a subgroup of patients with & lt;20% sTILs tumours having the worst iDFS, dDFS and OS in multivariate models. Five-year iDFS, dDFS and OS in patients with & lt;20% sTILs were 39%, 39% and 48% respectively for those with & lt;=2 GC in total, in comparison those with & gt;2 GC whose five-year iDFS, dDFS and OS were 65%, 65% and 69%, respectively. Conclusions: The prognostic importance of GC assessment in cancer-free ALNs in women with LN-positive HR-negative breast cancers is demonstrated. A better outcome in patients with GC formation in their cancer-free ALNs, despite low sTILs in the primary carcinoma, may suggest a systemic anticancer immune response. High sTILs but with extreme GC formation in the cancer-free ALNs could potentially reflect an overdriving but less effective immune response. The assessment of the combination of primary and nodal immune response in HR-negative breast cancers is imperative in these high-risk patients. Table 1. Univariate and Multivariate Cox Regression Analysis of Outcome by GC in Cancer-Free ALNsiDFSUnivariateAll cases & lt;20% sTIL & gt;=20% sTILTotal GCs number - binnedModel PHRCIModel PHRCIModel PHRCI & lt;=23.581.95 - 6.572.871.48 - 5.571.310.15 - 11.262 & gt;GC & lt;624.86E-05reference7.64E-03reference4.66E-03reference & gt;624.631.75 - 12.41.930.26 - 14.5612.793.34 - 48.97MultivariateCorrected for: pNstage, sTILS & TLSCorrected for: pTstage & TLSCorrected for: pNstageTotal GCs number - binnedCovariate PModel PHRCICovariate PModel PHRCICovariate PModel PHRCI & lt;=22.90E-022.00E-082.102.08 - 4.103.13E-037.00E-042.831.42 - 5.658.45E-011.00E-031.240.14 - 10.622 & gt;GC & lt;62NAreferenceNAreferenceNAreference & gt;624.15E-059.583.25 - 28.201.94E-014.070.49 - 33.876.62E-038.861.83 - 42.82dDFSUnivariateAll cases & lt;20% sTIL & gt;=20% sTILTotal GCs number - binnedModel PHRCIModel PHRCIModel PHRCI & lt;=24.762.48 - 9.143.681.82 - 7.432,130.22 - 20.442 & gt;GC & lt;622.46E-06reference1.10E-03reference2.19E-03reference & gt;625.872.14 - 16.082.490.32 - 19.0718.434.04 - 84.03MultivariateCorrected for: pTstage, pNstage, sTILS & TLSCorrected for: Age, pTstage, TLSCorrected for: pNstageTotal GCs number - binnedCovariate PModel PHRCICovariate PModel PHRCICovariate PModel PHRCI & lt;=24.30E-033.00E-092.911.40 - 6.059.01E-042.00E-053.451.66 - 7.165.51E-011.00E-031.990.21 - 19.132 & gt;GC & lt;62NAreferenceNAreferenceNAreference & gt;622.49E-0615.304.91 - 47.635.19E-028.610.98 - 75.553.11E-0313.302.39 - 73.89OSUnivariateAll cases & lt;20% sTIL & gt;=20% sTILTotal GCs number - binnedModel PHRCIModel PHRCIModel PHRCI & lt;=24.142.03 - 8.412.931.38 - 6.223.130.28 - 34.512 & gt;GC & lt;622.62E-04reference1.78E-02reference7.52E-02reference & gt;624.131.18 - 14.42.570.33 - 19.8311.891.65 - 85.45MultivariateCorrected for: Age, pTstage, pNstage, sTILS & TLSCorrected for: Age & TLSCorrected for: pNstage, LVI & TLSTotal GCs number - binnedCovariate PModel PHRCICovariate PModel PHRCICovariate PModel PHRCI & lt;=21.50E-013.00E-091.820.80 - 4.122.28E-024.00E-042.411.13 - 5.12*3.00E-04**2 & gt;GC & lt;62NAreferenceNAreferenceNAreference & gt;628.62E-0516.064.02 - 64.247.01E-027.050.85 - 58.342.80E-012.970.41 - 21.43*too few events Citation Format: Fangfang Liu, Thomas Hardiman, Patrycja Gazinska, Jelmar Quist, Sarah Pinder, Anita Grigoriadis. The formation of GCs in cancer-free ALNs, a non-monotonic prognostic factor in HR-negative invasive breast cancer patients [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS6-36.