Morphometrical malignancy grading is a valuable prognostic factor in invasive ductal breast cancer

The aim of the present study is to augment the prognostic power of breast cancer grading by elaboration of quantitative histopathological methods. We focus on the recently introduced morphometrical grading system in which the three grading sub-features of the WHO grading system are evaluated with the help of computerised nuclear morphometry, and quantitative methods for assessing mitotic activity and tubular differentiation. The prognostic value of the morphometrical grading system is now confirmed in a material of 159 cases of invasive ductal breast cancer. In the current material the morphometrical grading system very efficiently predicted the prognosis of breast cancer by dividing the patients into favourable (grade I), intermediate (grade II), and unfavourable (grade III) outcome (P<0.0001). The morphometrical grading system was especially efficient in identifying patients with the most unfavourable outcome. In our material the morphometrical grade III was associated with a 5.4-fold risk of breast cancer death. In light of the present results, the morphometrical grading can be applied to clinical use as an aid in treatment decisions of patients with invasive ductal breast cancer

Method for solving generalized convex nonsmooth mixed-integer nonlinear programming problems

In this paper, we generalize the extended supporting hyperplane algorithm for a convex continuously differentiable mixed-integer nonlinear programming problem to solve a wider class of nonsmooth problems. The generalization is made by using the subgradients of the Clarke subdifferential instead of gradients. Consequently, all the functions in the problems are assumed to be locally Lipschitz continuous. The algorithm is shown to converge to a global minimum of an MINLP problem if the objective function is convex and the constraint functions are f degrees-pseudoconvex. With some additional assumptions, the constraint functions may be f degrees-quasiconvex

Correlation of computed tomography with carotid plaque transcriptomes associates calcification with lesion-stabilization

Background and aims: Unstable carotid atherosclerosis causes stroke, but methods to identify patients and lesions at risk are lacking. We recently found enrichment of genes associated with calcification in carotid plaques from asymptomatic patients. Here, we hypothesized that calcification represents a stabilising feature of plaques and investigated how macro-calcification, as estimated by computed tomography (CT), correlates with gene expression profiles in lesions. Methods: Plaque calcification was measured in pre-operative CT angiographies. Plaques were sorted into high- and lowcalcified, profiled with microarrays, followed by bioinformatic analyses. Immunohistochemistry and qPCR were performed to evaluate the findings in plaques and arteries with medial calcification from chronic kidney disease patients. Results: Smooth muscle cell (SMC) markers were upregulated in high-calcified plaques and calcified plaques from symptomatic patients, whereas macrophage markers were downregulated. The most enriched processes in high-calcified plaques were related to SMCs and extracellular matrix (ECM) organization, while inflammation, lipid transport and chemokine signaling were repressed. These findings were confirmed in arteries with high medial calcification. Proteoglycan 4 (PRG4) was identified as the most upregulated gene in association with plaque calcification and found in the ECM, SMA+ and CD68+/TRAP + cells. Conclusions: Macro-calcification in carotid lesions correlated with a transcriptional profile typical for stable plaques, with altered SMC phenotype and ECM composition and repressed inflammation. PRG4, previously not described in atherosclerosis, was enriched in the calcified ECM and localized to activated macrophages and smooth muscle-like cells. This study strengthens the notion that assessment of calcification may aid evaluation of plaque phenotype and stroke risk.The European Union’s Horizon 2020/Marie Sklodowska-Curie grant agreement No 722609 (INTRICARE);Swedish Heart and Lung FoundationSwedish Research Council (K2009-65X-2233-01-3, K2013- 65X-06816-30-4, 349-2007-8703)Uppdrag Besegra Stroke (P581/ 2011-123)Stockholm County Council (ALF2011-0260, ALF-2011- 0279)Swedish Society for Medical ResearchTore Nilsson’s FoundationMagnus Bergvall’s FoundationKarolinska Institutet FoundationEuropean Commission (722609)Publishe

Engineering Bispecificity into a Single Albumin-Binding Domain

Bispecific antibodies as well as non-immunoglobulin based bispecific affinity proteins are considered to have a very high potential in future biotherapeutic applications. In this study, we report on a novel approach for generation of extremely small bispecific proteins comprised of only a single structural domain. Binding to tumor necrosis factor-α (TNF-α) was engineered into an albumin-binding domain while still retaining the original affinity for albumin, resulting in a bispecific protein composed of merely 46 amino acids. By diversification of the non albumin-binding side of the three-helix bundle domain, followed by display of the resulting library on phage particles, bispecific single-domain proteins were isolated using selections with TNF-α as target. Moreover, based on the obtained sequences from the phage selection, a second-generation library was designed in order to further increase the affinity of the bispecific candidates. Staphylococcal surface display was employed for the affinity maturation, enabling efficient isolation of improved binders as well as multiparameter-based sortings with both TNF-α and albumin as targets in the same selection cycle. Isolated variants were sequenced and the binding to albumin and TNF-α was analyzed. This analysis revealed an affinity for TNF-α below 5 nM for the strongest binders. From the multiparameter sorting that simultaneously targeted TNF-α and albumin, several bispecific candidates were isolated with high affinity to both antigens, suggesting that cell display in combination with fluorescence activated cell sorting is a suitable technology for engineering of bispecificity. To our knowledge, the new binders represent the smallest engineered bispecific proteins reported so far. Possibilities and challenges as well as potential future applications of this novel strategy are discussed

PTTG1-interacting protein (PTTG1IP/PBF) predicts breast cancer survival

Background: PTTG1-interacting protein (PTTG1IP) is an oncogenic protein, which participates in metaphase-anaphase transition of the cell cycle through activation of securin (PTTG1). PTTG1IP promotes the shift of securin from the cell cytoplasm to the nucleus, allowing the interaction between separase and securin. PTTG1IP overexpression has been previously observed in malignant disease, e.g. in breast carcinoma. However, the prognostic value of PTTG1IP in breast carcinoma patients has not previously been revealed.Methods: A total of 497 breast carcinoma patients with up to 22-year follow-up were analysed for PTTG1IP and securin immunoexpression. The results were evaluated for correlations with the clinical prognosticators and patient survival.Results: In our material, negative PTTG1IP immunoexpression predicted a 1.5-fold risk of breast cancer death (p = 0.02). However, adding securin immunoexpression to the analysis indicated an even stronger and independent prognostic power in the patient material (HR = 2.5, p < 0.0001). The subcellular location of securin was found with potential prognostic value also among the triple-negative breast carcinomas (n = 96, p = 0.052).Conclusions: PTTG1IP-negativity alone and in combination with high securin immunoexpression indicates a high risk of breast cancer death, resulting in up to 14-year survival difference in our material

CIP2A Interacts with TopBP1 and Drives Basal-Like Breast Cancer Tumorigenesis

Basal-like breast cancers (BLBC) are characterized by defects in homologous recombination (HR), deficient mitotic checkpoint, and high-proliferation activity. Here, we discover CIP2A as a candidate driver of BLBC. CIP2A was essential for DNA damage-induced initiation of mouse BLBC-like mammary tumors and for survival of HR-defective BLBC cells. CIP2A was dispensable for normal mammary gland development and for unperturbed mitosis, but selectively essential for mitotic progression of DNA damaged cells. A direct interaction between CIP2A and a DNA repair scaffold protein TopBP1 was identified, and CIP2A inhibition resulted in enhanced DNA damage-induced TopBP1 and RAD51 recruitment to chromatin in mammary epithelial cells. In addition to its role in tumor initiation, and survival of BRCA-deficient cells, CIP2A also drove proliferative MYC and E2F1 signaling in basal-like triple-negative breast cancer (BL-TNBC) cells. Clinically, high CIP2A expression was associated with poor patient prognosis in BL-TNBCs but not in other breast cancer subtypes. Small-molecule reactivators of PP2A (SMAP) inhibited CIP2A transcription, phenocopied the CIP2A-deficient DNA damage response (DDR), and inhibited growth of patient-derived BLBC xenograft. In summary, these results demonstrate that CIP2A directly interacts with TopBP1 and coordinates DNAdamage-induced mitotic checkpoint and proliferation, thereby driving BLBC initiation and progression. SMAPs could serve as a surrogate therapeutic strategy to inhibit the oncogenic activity of CIP2A in BLBCs. Significance: These results identify CIP2A as a nongenetic driver and therapeutic target in basal-like breast cancer that regulates DNA damage-induced G2-M checkpoint and proliferative signaling.Peer reviewe

Ratings of age of acquisition of 299 words across 25 languages: Is there a cross-linguistic order of words?

We present a new set of subjective age-of-acquisition (AoA) ratings for 299 words (158 nouns, 141 verbs) in 25 languages from five language families (Afro-Asiatic: Semitic languages; Altaic: one Turkic language: Indo-European: Baltic, Celtic, Germanic, Hellenic, Slavic, and Romance languages; Niger-Congo: one Bantu language; Uralic: Finnic and Ugric languages). Adult native speakers reported the age at which they had learned each word. We present a comparison of the AoA ratings across all languages by contrasting them in pairs. This comparison shows a consistency in the orders of ratings across the 25 languages. The data were then analyzed (1) to ascertain how the demographic characteristics of the participants influenced AoA estimations and (2) to assess differences caused by the exact form of the target question (when did you learn vs. when do children learn this word); (3) to compare the ratings obtained in our study to those of previous studies; and (4) to assess the validity of our study by comparison with quasi-objective AoA norms derived from the MacArthur–Bates Communicative Development Inventories (MB-CDI). All 299 words were judged as being acquired early (mostly before the age of 6 years). AoA ratings were associated with the raters’ social or language status, but not with the raters’ age or education. Parents reported words as being learned earlier, and bilinguals reported learning them later. Estimations of the age at which children learn the words revealed significantly lower ratings of AoA. Finally, comparisons with previous AoA and MB-CDI norms support the validity of the present estimations. Our AoA ratings are available for research or other purposes

High-level expression of Rad51 is an independent prognostic marker of survival in non-small-cell lung cancer patients

High-level expression of Rad51, a key factor in homologous recombination, has been observed in a variety of human malignancies. This study was aimed to evaluate Rad51 expression to serve as prognostic marker in non-small-cell lung cancer (NSCLC). A total of 383 non-small-cell lung tumours were analysed immunohistochemically on NSCLC tissue microarrays. High-level Rad51 expression was observed in 29.4% (100 out of 340) of cases. Patients whose tumours displayed high-level Rad51 expression showed a significantly shorter median survival time of 19 vs 68 months (P<0.0001, log-rank test). Similarly T status, N status, M status, clinical stage and histological tumour grade were significant prognostic markers in univariate Cox survival analysis. Importantly, Rad51 expression (P<0.0001) together with tumour differentiation (P<0.009), clinical stage (P=0.004) and N status (P=0.0001) proved to be independent prognostic parameters in multivariate analysis. Rad51 expression predicted the outcome of squamous cell cancer as well as adenocarcinoma of the lung. Our results suggest that Rad51 expression provides additional prognostic information for surgically treated NSCLC patients. We hypothesise that the decreased survival of NSCLC patients with high-level expression of Rad51 is related to an enhanced propensity of tumour cells for survival, antiapoptosis and chemo-/radioresistance

Breast cancer in neurofibromatosis type 1 : overrepresentation of unfavourable prognostic factors

Background: An increased breast cancer incidence and poor survival have been reported for women with neurofibromatosis 1 (NF1). To explain the poor survival, we aimed to link the histopathology and clinical characteristics of NF1-associated breast cancers. Methods: The Finnish Cancer Registry and the Finnish NF Registry were cross-referenced to identify the NF1 patients with breast cancer. Archival NF1 breast cancer specimens were retrieved for histopathological typing and compared with matched controls. Results: A total of 32 breast cancers were diagnosed in 1404 NF1 patients during the follow-up. Women with NF1 had an estimated lifetime risk of 18.0% for breast cancer, and this is nearly two-fold compared with that of the general Finnish female population (9.74%). The 26 successfully retrieved archival NF1 breast tumours were more often associated with unfavourable prognostic factors, such as oestrogen and progesterone receptor negativity and HER2 amplification. However, survival was worse in the NF1 group (P = 0.053) even when compared with the control group matched for age, diagnosis year, gender and oestrogen receptor status. Scrutiny of The Cancer Genome Atlas data set showed that NF1 mutations and deletions were associated with similar characteristics in the breast cancers of the general population. Conclusions: These results emphasise the role of the NF1 gene in the pathogenesis of breast cancer and a need for active follow-up for breast cancer in women with NF1.Peer reviewe

Isotropic 3D Nuclear Morphometry of Normal, Fibrocystic and Malignant Breast Epithelial Cells Reveals New Structural Alterations

Grading schemes for breast cancer diagnosis are predominantly based on pathologists' qualitative assessment of altered nuclear structure from 2D brightfield microscopy images. However, cells are three-dimensional (3D) objects with features that are inherently 3D and thus poorly characterized in 2D. Our goal is to quantitatively characterize nuclear structure in 3D, assess its variation with malignancy, and investigate whether such variation correlates with standard nuclear grading criteria.We applied micro-optical computed tomographic imaging and automated 3D nuclear morphometry to quantify and compare morphological variations between human cell lines derived from normal, benign fibrocystic or malignant breast epithelium. To reproduce the appearance and contrast in clinical cytopathology images, we stained cells with hematoxylin and eosin and obtained 3D images of 150 individual stained cells of each cell type at sub-micron, isotropic resolution. Applying volumetric image analyses, we computed 42 3D morphological and textural descriptors of cellular and nuclear structure.We observed four distinct nuclear shape categories, the predominant being a mushroom cap shape. Cell and nuclear volumes increased from normal to fibrocystic to metastatic type, but there was little difference in the volume ratio of nucleus to cytoplasm (N/C ratio) between the lines. Abnormal cell nuclei had more nucleoli, markedly higher density and clumpier chromatin organization compared to normal. Nuclei of non-tumorigenic, fibrocystic cells exhibited larger textural variations than metastatic cell nuclei. At p<0.0025 by ANOVA and Kruskal-Wallis tests, 90% of our computed descriptors statistically differentiated control from abnormal cell populations, but only 69% of these features statistically differentiated the fibrocystic from the metastatic cell populations.Our results provide a new perspective on nuclear structure variations associated with malignancy and point to the value of automated quantitative 3D nuclear morphometry as an objective tool to enable development of sensitive and specific nuclear grade classification in breast cancer diagnosis