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Purpose: There is an urgent need for developing new biomarker tools to accurately predict treatment response of breast cancer, especially the deadly triple-negative breast cancer. We aimed to develop gene-mutation-based machine learning (ML) algorithms as biomarker classifiers to predict treatment response of first-line chemotherapy with high precision. Methods: Random Forest ML was applied to screen the algorithms of various combinations of gene mutation profiles of primary tumors at diagnosis using a TCGA Cohort (n = 399) with up to 150 months follow-up as a training set and validated in a MSK Cohort (n = 807) with up to 220 months follow-up. Subtypes of breast cancer including triple-negative and luminal A (ER+, PR+ and HER2−) were also assessed. The predictive performance of the candidate algorithms as classifiers was further assessed using logistic regression, Kaplan−Meier progression-free survival (PFS) plot, and univariate/multivariate Cox proportional hazard regression analyses. Results: A novel algorithm termed the 12-Gene Algorithm based on mutation profiles of KRAS, PIK3CA, MAP3K1, MAP2K4, PTEN, TP53, CDH1, GATA3, KMT2C, ARID1A, RunX1, and ESR1, was identified. The performance of this algorithm to distinguish non-progressed (responder) vs. progressed (non-responder) to treatment in the TCGA Cohort as determined using AUC was 0.96 (95% CI 0.94−0.98). It predicted progression-free survival (PFS) with hazard ratio (HR) of 21.6 (95% CI 11.3−41.5) (p < 0.0001) in all patients. The algorithm predicted PFS in the triple-negative subgroup with HR of 19.3 (95% CI 3.7−101.3) (n = 42, p = 0.000). The 12-Gene Algorithm was validated in the MSK Cohort with a similar AUC of 0.97 (95% CI 0.96−0.98) to distinguish responder vs. non-responder patients, and had a HR of 18.6 (95% CI 4.4−79.2) to predict PFS in the triple-negative subgroup (n = 75, p < 0.0001). Conclusions: The novel 12-Gene algorithm based on multitude gene-mutation profiles identified through ML has a potential to predict breast cancer treatment response to therapies, especially in triple-negative subgroups patients, which may assist personalized therapies and reduce mortality.

Cells adhering onto surfaces sense and respond to chemical and physical surface features. The control over cell adhesion behavior influences cell migration, proliferation, and differentiation, which are important considerations in biomaterial design for cell culture, tissue engineering, and regenerative medicine. Here, we report on a supramolecular-based approach to prepare reversible self-assembled monolayers (rSAMs) with tunable lateral mobility and dynamic control over surface composition to regulate cell adhesion behavior. These layers were prepared by incubating oxoacid-terminated thiol SAMs on gold in a pH 8 HEPES buffer solution containing different mole fractions of ω-(ethylene glycol) 2-4 - and ω-(GRGDS)-, α-benzamidino bolaamphiphiles. Cell shape and morphology were influenced by the strength of the interactions between the amidine-functionalized amphiphiles and the oxoacid of the underlying SAMs. Dynamic control over surface composition, achieved by the addition of inert filler amphiphiles to the RGD-functionalized rSAMs, reversed the cell adhesion process. In summary, rSAMs featuring mobile bioactive ligands offer unique capabilities to influence and control cell adhesion behavior, suggesting a broad use in biomaterial design, tissue engineering, and regenerative medicine.

Low-affinity immunoglobulin gamma Fc region receptor III-A (FcγRIIIa) is a cell surface protein that belongs to a family of Fc receptors that facilitate the protective function of the immune system against pathogens. However, the role of FcγRIIIa in prostate cancer (PCa) progression remained unknown. In this study, we found that FcγRIIIa expression was present in PCa cells and its level was significantly higher in metastatic lesions than in primary tumors from the PCa cohort (P = 0.006). PCa patients with an elevated level of FcγRIIIa expression had poorer biochemical recurrence (BCR)-free survival compared with those with lower FcγRIIIa expression, suggesting that FcγRIIIa is of clinical importance in PCa. We demonstrated that overexpression of FcγRIIIa increased the proliferative ability of PCa cell line C4-2 cells, which was accompanied by the upregulation of androgen receptor (AR) and phosphatidylinositol-4-phosphate 5-kinase alpha (PIP5Kα), which are the key players in controlling PCa progression. Conversely, targeted inhibition of FcγRIIIa via siRNA-mediated knockdown or using its inhibitory antibody suppressed growth of xenograft PC-3 and PC-3M prostate tumors and reduced distant metastasis in xenograft mouse models. We further showed that elevated expression of AR enhanced FcγRIIIa expression, whereas inhibition of AR activity using enzalutamide led to a significant downregulation of FcγRIIIa protein expression. Similarly, inhibition of PIP5K1α decreased FcγRIIIa expression in PCa cells. FcγRIIIa physically interacted with PIP5K1α and AR via formation of protein-protein complexes, suggesting that FcγRIIIa is functionally associated with AR and PIP5K1α in PCa cells. Our study identified FcγRIIIa as an important factor in promoting PCa growth and invasion. Further, the elevated activation of FcγRIII and AR and PIP5K1α pathways may cooperatively promote PCa growth and invasion. Thus, FcγRIIIa may serve as a potential new target for improved treatment of metastatic and castration-resistant PCa., (© 2022 The Authors. Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)

Purpose: Despite the high mortality of metastatic colorectal cancer (mCRC), no new biomarker tools are available for predicting treatment response. We developed gene-mutation-based algorithms as a biomarker classifier to predict treatment response with better precision than the current predictive factors. Methods: Random forest machine learning (ML) was applied to identify the candidate algorithms using the MSK Cohort (n = 471) as a training set and validated in the TCGA Cohort (n = 221). Logistic regression, progression-free survival (PFS), and univariate/multivariate Cox proportional hazard analyses were performed and the performance of the candidate algorithms was compared with the established risk parameters. Results: A novel 7-Gene Algorithm based on mutation profiles of seven KRAS-associated genes was identified. The algorithm was able to distinguish non-progressed (responder) vs. progressed (non-responder) patients with AUC of 0.97 and had predictive power for PFS with a hazard ratio (HR) of 16.9 (p < 0.001) in the MSK cohort. The predictive power of this algorithm for PFS was more pronounced in mCRC (HR = 16.9, p < 0.001, n = 388). Similarly, in the TCGA validation cohort, the algorithm had AUC of 0.98 and a significant predictive power for PFS (p < 0.001). Conclusion: The novel 7-Gene Algorithm can be further developed as a biomarker model for prediction of treatment response in mCRC patients to improve personalized therapies.

Sialic acid (SA) is a monosaccharide usually linked to the terminus of glycan chains on the cell surface. It plays a crucial role in many biological processes, and hypersialylation is a common feature in cancer. Lectins are widely used to analyze the cell surface expression of SA. However, these protein molecules are usually expensive and easily denatured, which calls for the development of alternative glycan-specific receptors and cell imaging technologies. In this study, SA-imprinted fluorescent core-shell molecularly imprinted polymer particles (SA-MIPs) were employed to recognize SA on the cell surface of cancer cell lines. The SA-MIPs improved suspensibility and scattering properties compared with previously used core-shell SA-MIPs. Although SA-imprinting was performed using SA without preference for the α2,3- and α2,6-SA forms, we screened the cancer cell lines analyzed using the lectins Maackia Amurensis Lectin I (MAL I, α2,3-SA) and Sambucus Nigra Lectin (SNA, α2,6-SA). Our results show that the selected cancer cell lines in this study presented a varied binding behavior with the SA-MIPs. The binding pattern of the lectins was also demonstrated. Moreover, two different pentavalent SA conjugates were used to inhibit the binding of the SA-MIPs to breast, skin, and lung cancer cell lines, demonstrating the specificity of the SA-MIPs in both flow cytometry and confocal fluorescence microscopy. We concluded that the synthesized SA-MIPs might be a powerful future tool in the diagnostic analysis of various cancer cells.

Molecularly imprinted polymers (MIPs) are currently widely used and further developed for biological applications. The MIP synthesis procedure is a key process, and a wide variety of protocols exist. The templates that are used for imprinting vary from the smallest glycosylated glycan structures or even amino acids to whole proteins or bacteria. The low cost, quick preparation, stability and reproducibility have been highlighted as advantages of MIPs. The biological applications utilizing MIPs discussed here include enzyme-linked assays, sensors, in vivo applications, drug delivery, cancer diagnostics and more. Indeed, there are numerous examples of how MIPs can be used as recognition elements similar to natural antibodies.

In this study, an epitope-imprinting strategy was employed for the dynamic display of bioactive ligands on a material interface. An imprinted surface was initially designed to exhibit specific affinity towards a short peptide (i.e., the epitope). This surface was subsequently used to anchor an epitope-tagged cell-adhesive peptide ligand (RGD: Arg-Gly-Asp). Owing to reversible epitope-binding affinity, ligand presentation and thereby cell adhesion could be controlled. As compared to current strategies for the fabrication of dynamic biointerfaces, for example, through reversible covalent or host-guest interactions, such a molecularly tunable dynamic system based on a surface-imprinting process may unlock new applications in in situ cell biology, diagnostics, and regenerative medicine., (© 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Sialic acid (SA) is normally expressed on the cell membranes and is located at the terminal position of the sugar chains. SA plays an important role for regulation of the innate immunity, function as markers of the cells and can be recognized by a variety of receptors. Interestingly, the level of SA expression is increased on metastatic cancer cells. The availability of specific antibodies against SA is limited and, therefore, biomarker tools for detection of SA are lacking. We have recently presented a novel method for specific fluorescence labeling of SA molecular imprinted polymers (MIP). Here, we have performed an extended screening of SA expression by using SA-MIP and included four different chronic lymphocytic leukemia (CLL) cell lines, conveniently analyzed by flow cytometry and fluorescence microscopy. SA expression was detected in four cell lines at different levels, and the SA expression were verified with lectin-FITC. These results show that SA-MIP can be used as a plastic antibody for detection of SA using both flow cytometry and fluorescence microscopy. We suggest that SA-MIP can be used for screening of different tumor cells of various stages, including CLL cells.

Background: We introduce the combination of digital holographic microscopy (DHM) and antibody microarrays as a powerful tool to measure morphological changes in specifically antibody-captured cells. The aim of the study was to develop DHM for analysis of cell death of etoposide-treated suspension cells., Results/methodology: We demonstrate that the cell number, mean area, thickness and volume were noninvasively measured by using DHM. The cell number was stable over time, but the two cell lines showed changes of cell area and cell irregularity after treatment. The cell volume in etoposide-treated cells was decreased, whereas untreated cells showed stable volume., Conclusion: Our results provide proof of concept for using DHM combined with antibody-based microarray technology for detecting morphological changes in captured cells., Competing Interests: Financial & competing interests disclosureThe authors would like to thank Malmö University, the Crafoord foundation, the Swedish Research Council (VR-NT) and The Cancer Foundation at Malmö University Hospital for support. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.No writing assistance was utilized in the production of this manuscript.

It remains poorly understood how the haematopoietic stem/progenitor cells (HSPC) are attracted to their niches and the functional consequences of such interaction. In the present study, we show that the cell cycle regulator cyclin A1 in association with vascular endothelial growth factor receptor 1 (VEGFR1), is required for HSPC and their niches to maintain their function and proper interaction. In the absence of cyclin A1, the HSPC in the BM are increased in their frequency and display an increased migratory and homing ability. Concomitantly, the ability of the endosteal and central BM niche zones to attract and home the wild-type HSPC is significantly reduced in cyclin A1-null mice as compared to the wild-type controls. The impaired proliferation and homing of HSPC in the BM of cyclin A1-null mice are attributed to the increased density of microvessels in the endosteal and central BM niche zones, which is associated with the increased VEGFR1 expression. Thus, modulation of cyclin A1 and VEGFR1 in HSPC and their niches may provide new insights into therapeutic approaches.

Src homology 2 domain-containing tyrosine phosphatase-2 (SHP-2) is an important regulator of cell signaling because of its ability to dephosphorylate receptors of growth factors as well as the cytokines and tyrosine-phosphorylated proteins associated with these receptors. In the current study, we used four different prostate cancer cell lines: PC3, DU145, LNCaP and LNCaP-IL6+. Tumor specimens from 122 patients with prostate cancer were analyzed using a tissue microarray. Our data demonstrate that all four prostate cancer cell lines express the SHP-2 protein. Additionally, low staining intensity and SHP-2 expression in the cytoplasm of cancer cells in prostate tumor specimens was inversely correlated with prostate volume (p = 0.041 and p = 0.042, respectively) whereas nuclear staining was positively correlated with extracapsular extension (p = 0.039). In our post-prostatectomy specimens, we found that patients with low SHP-2 expression had less favorable outcomes with respect to biochemical recurrence and clinical progression (p = 0.005 and p = 0.018, respectively). The loss of cytoplasmic SHP-2 expression is associated with increased growth and prostatic cancer progression.

Background: Interleukin-6 (IL-6) is a multifunctional cytokine that has been implicated in the modulation of growth and progression of prostate cancer. Decreased expression of the tyrosine phosphatase SHP-1, involved in regulation of cytokine and tyrosine kinase receptor signaling, has been shown to be associated with less favorable outcome among prostate cancer patients., Methods: Parental LNCaP cells and an LNCaP-IL6+ subline, derived from parental LNCaP cells by continuous culture of the cells in the presence of recombinant IL-6 were used in the study. Expression of STAT3, pSTAT3, ERK, pERK, AKT, pAKT, PTEN, and SHP-1 was analyzed by immunohistochemistry, Western blots, cDNA microarray, quantitative PCRs, and reverse transcriptase PCRs. Proliferation and apoptosis of transfected cells were analyzed by caspase3/7 assay and flow cytometry., Results: Phosphorylation of ERK and STAT3 was increased in the LNCaP-IL6+ subline compared with LNCaP cells, whereas pAKT was decreased. Overexpression and inhibition experiments with SHP-1 siRNA showed that SHP-1 reduced proliferation and increased apoptosis in both cell lines. Microarray analysis revealed 80 up-regulated and 87 down-regulated SHP-1-related genes in the LNCaP-IL6+ cell line compared with LNCaP cells., Conclusions: SHP-1 suppresses growth and increases apoptosis in both LNCaP and LNCaP-IL6+ cells, which suggests that SHP-1 could be a therapeutic target in prostate cancer, even when there is an IL-6-related growth advantage., ((c) 2010 Wiley-Liss, Inc.)

The protein tyrosine kinase (PTK) receptors and cytosolic signaling proteins as well as the protein tyrosine phosphatases (PTPs) have important roles in regulation of growth of the benign and malignant prostate gland. Here, we studied expression of the protein tyrosine phosphatase SHP-1 in prostate cancer cell lines and in human prostatic tissues. SHP-1 is expressed at a high level in LNCaP prostate cancer cells compared with PC3 cells. Silencing of SHP-1 expression with siRNA in LNCaP cells led to an increased rate of proliferation, whereas overexpression of SHP-1 by means of transient and stable transfection in PC3 cells led to a decrease in proliferation. Corresponding changes were observed in cyclin D1 expression. We further demonstrate that LNCaP and PC3 cells respond differently to IL-6 stimulation. SHP-1 overexpression in PC3 cells reversed IL-6 stimulation of proliferation, whereas in SHP-1-silenced LNCaP cells, IL-6 inhibition of proliferation was not affected. In addition, IL-6 treatment led to higher levels of phosphorylated STAT3 in SHP-1-silenced LNCaP cells than in control cells. Next, SHP-1 expression in human prostate cancer was analyzed by immunohistochemical staining of tissue microarrays comprising tumor specimens from 100 prostate cancer patients. We found an inverse correlation between the tumor level of SHP-1 expression and time to biochemical recurrence and clinical progression among prostate cancer patients. In conclusion, our results suggest that a decreased level of SHP-1 expression in prostate cancer cells is associated with a high proliferation rate and an increased risk of recurrence or clinical progression after radical prostatectomy for localized prostate cancer.

PTEN and SHP1 are tumor suppressor genes involved in the regulation of cell cycle control and apoptosis. The authors investigated the protein expression of PTEN and SHP1, by immunohistochemistry in tissue microarrays from bone marrow samples in children, diagnosed with acute lymphoblastic leukaemia and nonmalignant controls. PTEN was overexpressed in diagnostic ALL samples, while SHP1 showed a low expression. Both proteins showed a significant difference in expression compared to nonmalignant controls. The roles of PTEN and SHP1 are not well investigated in pediatric leukemia and could in the future play a role as prognostic factors.

Although many pediatric B-cell lymphoma patients are being cured today, much is still unknown about the pathogenesis of this disease. Protein tyrosine phosphatases are involved in the control of survival, growth, and differentiation of cells. The authors have analyzed 26 pediatric B-cell lymphoma cases for the expression of a panel of phosphatases and report a statistically significant lower expression intensity of PTEN and HePTP and higher nuclear SHP2 expression in B-cell lymphoma cases compared to lymphoid tissue. Knowledge about the expression of key regulatory proteins in pediatric B-cell lymphomas is necessary for revealing the complex molecular background of this disease.

Patients diagnosed with diffuse large B-cell lymphoma (DLBCL) show varying responses to conventional therapy, and this might be contributed to the differentiation stage of the tumor B-cells. The aim of the current study was to evaluate a panel of kinases (ZAP70, PKC-beta I and II and phosphorylated PKB/Akt) and phosphatases (PTEN, SHP1 and SHP2) known to be frequently deregulated in lymphoid malignancies. De novo DLBCL cases were divided into two subgroups, the germinal center (GC) group (14/28) and the non-germinal center (non-GC) or activated B-cell (ABC) group (14/28). ZAP70 and PKC-beta II were expressed in a significantly higher percentage of tumor cells in the clinically more aggressive non-GC group compared with the prognostically favourable GC group. Also, the subcellular localization of PKC-beta I and II differed in DLBCL cells, with the PKC-beta I isoform being expressed in both the cytoplasm and nucleus, while PKC-beta II was found exclusively in the cytoplasm. Loss of nuclear PTEN correlated with poor survival in cases from both subgroups. In addition, five cell lines of DLBCL origin were analyzed for protein expression and for mRNA levels of PTEN and SHP1. For the first time, we show that ZAP70 is expressed in a higher percentage of tumor cells in the aggressive non-GC subgroup of DLBCL and that PKC-beta I and II are differently distributed in the two prognostic subgroups of de novo DLBCL.

Alpha1-antitrypsin (AAT) is a major circulating and tissues inhibitor of serine proteinases implicated in the regulation of inflammation and host defence. There is now increasing evidence that AAT may also exhibit anti-inflammatory activities independent of its protease inhibitor function. This study was undertaken to investigate the effects of native (inhibitory) and polymerized (non-inhibitory) forms of AAT on MID (Moraxella IgD binding protein)-induced human tonsillar B cell activation in vitro. We found that 0.5 microg/ml MID induces B cell proliferation and stimulates IL-6 release (p<0.001) relative to non-stimulated controls. Both native and polymerized AAT (0.5 mg/ml) inhibited MID-stimulated B cell proliferation in a similar manner (by 70%, p<0.001), whereas MID-induced IL-6 release was more strongly suppressed by polymerized (9.9-fold, p<0.001) as compared to native AAT (2.8-fold, p<0.01). Electrophoretic analysis of cell culture media did not indicate any interaction between AAT and MID, and flow cytometry data showed no competition for the same receptor. The effects of AATs were observed whether added together with MID or 2h after MID-addition to cell cultures. Thus, our data demonstrate that AAT inhibits MID-induced B cell activation in vitro that is unrelated to its protease inhibitory activity and is not dependent on MID binding to the cell surface.